<?xml version="1.0" encoding="UTF-8" ?>	
            <rss version="2.0" xmlns:media="http://search.yahoo.com/mrss/">
               	<channel>
                  	<title><![CDATA[Recent Videos tagged 'Networks' on MIT Video]]></title>
                  	<link>http://video.mit.edu/tagged/networks/</link>
                  	<description></description>
                  	<language>en-us</language>
                  	<pubDate>Wed, 28 Nov 2012 15:30:17 GMT</pubDate>
                  	<lastBuildDate>Wed, 22 May 2013 13:47:25 EDT</lastBuildDate>					
					                    	
                        <item>
                         	<title><![CDATA[Moving Beyond Materiality: MIT Visiting Artist Tomas Saraceno]]></title>                         
                         	<link>http://video.mit.edu/watch/moving-beyond-materiality-mit-visiting-artist-tomas-saraceno-13262/</link>
                         	<description><![CDATA[In this public lecture, MIT Visiting Artist Tomas Saraceno discussed the speculative context and experimental materials of his Cloud Cities with Nader Tehrani and Anton Garcia-Abril]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20121128103017-4191351697.jpg" height="100" width="165" />                         
                        	<pubDate>Wed, 28 Nov 2012 15:30:17 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/moving-beyond-materiality-mit-visiting-artist-tomas-saraceno-13262/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[The role of U.S. airports in disease epidemics]]></title>                         
                         	<link>http://video.mit.edu/watch/the-role-of-us-airports-in-disease-epidemics-12013/</link>
                         	<description><![CDATA[Researchers at MIT are using a new mathematical model to better understand how contagious diseases are spread by air travel.]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120720165002.jpg" height="100" width="165" />                         
                        	<pubDate>Fri, 20 Jul 2012 20:41:40 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/the-role-of-us-airports-in-disease-epidemics-12013/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Creative Experimentation: Developing a Skill Critical for Managing Complex Operating Systems (2 of 2)]]></title>                         
                         	<link>http://video.mit.edu/watch/creative-experimentation-developing-a-skill-critical-for-managing-complex-operating-systems-2-of-2-9996/</link>
                         	<description><![CDATA[A broad-based capacity for experimentation is critical for organizations to succeed because the systems in which people are embedded are increasingly complex and fast.]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120131163006-3080479654.jpg" height="100" width="165" />                         
                        	<pubDate>Tue, 31 Jan 2012 21:30:06 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/creative-experimentation-developing-a-skill-critical-for-managing-complex-operating-systems-2-of-2-9996/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[RLE Investigator Profile Video Series: Vincent W.S. Chan]]></title>                         
                         	<link>http://video.mit.edu/watch/rle-investigator-profile-video-series-vincent-ws-chan-8980/</link>
                         	<description><![CDATA[Chan discusses research and education in his group.]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120127030354-9-1_t0hl8btw.jpg" height="100" width="165" />                         
                        	<pubDate>Wed, 25 Jan 2012 23:17:53 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/rle-investigator-profile-video-series-vincent-ws-chan-8980/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[BLOSSOMS - Selfish Drivers: Braess's Paradox and Traffic Planning (English Subtitles)]]></title>                         
                         	<link>http://video.mit.edu/watch/blossoms-selfish-drivers-braesss-paradox-and-traffic-planning-english-subtitles-8874/</link>
                         	<description><![CDATA[The idea of this lesson is to introduce, in a simplified manner, the so-called Braess's Paradox]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135854-9-1_0trr6cif.jpg" height="100" width="165" />                         
                        	<pubDate>Mon, 09 Jan 2012 20:01:21 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/blossoms-selfish-drivers-braesss-paradox-and-traffic-planning-english-subtitles-8874/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Meet 2011 TR35 Winner Bhaskar Krishnamachar]]></title>                         
                         	<link>http://video.mit.edu/watch/meet-2011-tr35-winner-bhaskar-krishnamachar-19/</link>
                         	<description><![CDATA[Krishnamachari describes his work at EmTech 2011: Smarter wireless networks

University of Southern California

By creating smarter wireless networks that can handle mobile devices and interference more efficiently than today's Wi-Fi and cellular]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125134448-1-1283621899001.jpg" height="100" width="165" />                         
                        	<pubDate>Wed, 30 Nov 2011 05:00:00 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/meet-2011-tr35-winner-bhaskar-krishnamachar-19/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[MIT Red Balloons social spread]]></title>                         
                         	<link>http://video.mit.edu/watch/mit-red-balloons-social-spread-9747/</link>
                         	<description><![CDATA[This video illustrates how referral between participants of the MIT team spread on the continental U.S. before and during the DARPA challenge. Each white line represents a referral from an existing participant's location of the MIT team to the the location of a new team participant. ~36 hours before the competition, under the incentive described in the paper, people actively signed up with the MIT team and referred friends from all different areas, as the white lines expanded rapidly across the U.S. in the animation. 

The lines highlighted in yellow represents referrals leading to locations where the balloons were actually launched. The social diffusion process started by the MIT team naturally led us to all ten balloon locations in an efficient manner for this time-critical task.]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120128154605-8-6Ga_EJWLzHA.jpg" height="100" width="165" />                         
                        	<pubDate>Thu, 27 Oct 2011 20:46:01 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/mit-red-balloons-social-spread-9747/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Networks Understanding Networks, Pt. 14: Sep Kamvar]]></title>                         
                         	<link>http://video.mit.edu/watch/networks-understanding-networks-pt-14-sep-kamvar-10096/</link>
                         	<description><![CDATA[Search and the Social Web: Sep Kamvar]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120209030255-479183163.jpg" height="100" width="165" />                         
                        	<pubDate>Thu, 20 Oct 2011 01:21:41 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/networks-understanding-networks-pt-14-sep-kamvar-10096/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Networks Understanding Networks, Pt. 16: Wadah Khanfar and Closing Remarks]]></title>                         
                         	<link>http://video.mit.edu/watch/networks-understanding-networks-pt-16-wadah-khanfar-and-closing-remarks-10097/</link>
                         	<description><![CDATA[Wadah Khanfar on the Arab Spring and Closing remarks]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120209030256-402341278.jpg" height="100" width="165" />                         
                        	<pubDate>Tue, 18 Oct 2011 15:07:31 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/networks-understanding-networks-pt-16-wadah-khanfar-and-closing-remarks-10097/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Networks Understanding Networks, Pt. 15: Ethan Zuckerman]]></title>                         
                         	<link>http://video.mit.edu/watch/networks-understanding-networks-pt-15-ethan-zuckerman-10098/</link>
                         	<description><![CDATA[Civic Media and Networks — Understanding Media as an Ecosystem: Ethan Zuckerman]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120209030256-2821367615.jpg" height="100" width="165" />                         
                        	<pubDate>Tue, 18 Oct 2011 14:58:47 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/networks-understanding-networks-pt-15-ethan-zuckerman-10098/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Networks Understanding Networks, Pt. 13: Panel on Open Innovation and Creativity]]></title>                         
                         	<link>http://video.mit.edu/watch/networks-understanding-networks-pt-13-panel-on-open-innovation-and-creativity-10099/</link>
                         	<description><![CDATA[Open Innovation and Creativity Panel. Moderator, Joi Ito; Panelists: Larry Lessig, John Seely Brown, Yochai Benkler, Chris DiBona]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120209030257-1179020956.jpg" height="100" width="165" />                         
                        	<pubDate>Tue, 18 Oct 2011 14:15:12 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/networks-understanding-networks-pt-13-panel-on-open-innovation-and-creativity-10099/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Networks Understanding Networks, Pt. 12: Neri Oxman]]></title>                         
                         	<link>http://video.mit.edu/watch/networks-understanding-networks-pt-12-neri-oxman-10100/</link>
                         	<description><![CDATA[Fabricating Networks: Notes on Biologically Inspired Design — Neri Oxman]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120209030257-3759271056.jpg" height="100" width="165" />                         
                        	<pubDate>Mon, 17 Oct 2011 18:22:41 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/networks-understanding-networks-pt-12-neri-oxman-10100/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Networks Understanding Networks, Pt. 11: John Moore]]></title>                         
                         	<link>http://video.mit.edu/watch/networks-understanding-networks-pt-11-john-moore-10101/</link>
                         	<description><![CDATA[Healthcare that Heals Itself — John Moore]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120209030258-258616335.jpg" height="100" width="165" />                         
                        	<pubDate>Mon, 17 Oct 2011 18:21:00 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/networks-understanding-networks-pt-11-john-moore-10101/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Networks Understanding Networks, Pt. 10: Nicholas Christakis]]></title>                         
                         	<link>http://video.mit.edu/watch/networks-understanding-networks-pt-10-nicholas-christakis-10102/</link>
                         	<description><![CDATA[The Evolutionary Significance of Human Social Networks — Nicholas Christakis]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120209030258-1134808904.jpg" height="100" width="165" />                         
                        	<pubDate>Mon, 17 Oct 2011 18:13:52 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/networks-understanding-networks-pt-10-nicholas-christakis-10102/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Networks Understanding Networks, Pt. 9: Day 2 Welcome, Joi Ito and César Hidalgo]]></title>                         
                         	<link>http://video.mit.edu/watch/networks-understanding-networks-pt-9-day-2-welcome-joi-ito-and-cesar-hidalgo-10103/</link>
                         	<description><![CDATA[Day 2 Welcome and Introduction — Joi Ito and César Hidalgo]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120209030259-4130008373.jpg" height="100" width="165" />                         
                        	<pubDate>Mon, 17 Oct 2011 18:13:17 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/networks-understanding-networks-pt-9-day-2-welcome-joi-ito-and-cesar-hidalgo-10103/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Networks Understanding Networks, Pt. 8: Wrap-Up, Day One]]></title>                         
                         	<link>http://video.mit.edu/watch/networks-understanding-networks-pt-8-wrap-up-day-one-10104/</link>
                         	<description><![CDATA[Wrap-Up, Day One with Joi Ito and César Hidalgo.]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120209030259-1114132642.jpg" height="100" width="165" />                         
                        	<pubDate>Mon, 17 Oct 2011 17:38:08 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/networks-understanding-networks-pt-8-wrap-up-day-one-10104/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Networks Understanding Networks, Pt. 7: Kent Larson]]></title>                         
                         	<link>http://video.mit.edu/watch/networks-understanding-networks-pt-7-kent-larson-10105/</link>
                         	<description><![CDATA[Kent Larson: New Networks and Urban Transformation]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120209030300-1235376755.jpg" height="100" width="165" />                         
                        	<pubDate>Mon, 17 Oct 2011 17:35:24 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/networks-understanding-networks-pt-7-kent-larson-10105/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Networks Understanding Networks, Pt. 6: Albert-László Barabási]]></title>                         
                         	<link>http://video.mit.edu/watch/networks-understanding-networks-pt-6-albert-laszlo-barabasi-10106/</link>
                         	<description><![CDATA[Albert-László Barabási: Network Science: From the Web to the Cell]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120209030300-780228853.jpg" height="100" width="165" />                         
                        	<pubDate>Mon, 17 Oct 2011 17:27:18 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/networks-understanding-networks-pt-6-albert-laszlo-barabasi-10106/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Networks Understanding Networks: Pt. 5, Joi Ito on Meeting Mechanics]]></title>                         
                         	<link>http://video.mit.edu/watch/networks-understanding-networks-pt-5-joi-ito-on-meeting-mechanics-10107/</link>
                         	<description><![CDATA[Joi Ito on how this meeting is structured.]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120209030301-1899446326.jpg" height="100" width="165" />                         
                        	<pubDate>Mon, 17 Oct 2011 17:25:46 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/networks-understanding-networks-pt-5-joi-ito-on-meeting-mechanics-10107/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Networks Understanding Networks, Pt. 4: Ricardo Hausmann]]></title>                         
                         	<link>http://video.mit.edu/watch/networks-understanding-networks-pt-4-ricardo-hausmann-10108/</link>
                         	<description><![CDATA[Ricardo Hausmann — How to Infer What Countries Know from What They Produce and Why It Matters]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120209030301-4257310383.jpg" height="100" width="165" />                         
                        	<pubDate>Mon, 17 Oct 2011 17:18:06 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/networks-understanding-networks-pt-4-ricardo-hausmann-10108/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Networks Understanding Networks, Pt. 3: Sandy Pentland]]></title>                         
                         	<link>http://video.mit.edu/watch/networks-understanding-networks-pt-3-sandy-pentland-10109/</link>
                         	<description><![CDATA[Sandy Pentland — Influence Networks]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120209030301-4217703756.jpg" height="100" width="165" />                         
                        	<pubDate>Mon, 17 Oct 2011 17:16:41 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/networks-understanding-networks-pt-3-sandy-pentland-10109/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Networks Understanding Networks, Pt. 2: Ed Boyden]]></title>                         
                         	<link>http://video.mit.edu/watch/networks-understanding-networks-pt-2-ed-boyden-10110/</link>
                         	<description><![CDATA[Ed Boyden: &quot;Neural Networks Understanding Neural Networks&quot;]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120209030302-4202741746.jpg" height="100" width="165" />                         
                        	<pubDate>Mon, 17 Oct 2011 17:12:37 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/networks-understanding-networks-pt-2-ed-boyden-10110/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Networks Understanding Networks, Pt. 1: Welcome by Nicholas Negroponte, Joi Ito, and César Hidalgo]]></title>                         
                         	<link>http://video.mit.edu/watch/networks-understanding-networks-pt-1-welcome-by-nicholas-negroponte-joi-ito-and-cesar-hidalgo-10111/</link>
                         	<description><![CDATA[Economies are networks of businesses, just as businesses are networks of people, and people are networks of cells. Welcome by Nicholas Negroponte, Joi Ito, and César Hidalgo.]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120209030303-2225395613.jpg" height="100" width="165" />                         
                        	<pubDate>Mon, 17 Oct 2011 17:04:56 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/networks-understanding-networks-pt-1-welcome-by-nicholas-negroponte-joi-ito-and-cesar-hidalgo-10111/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[MITEF-NYC: Whats Next for U.S. Wireless Broadband?]]></title>                         
                         	<link>http://video.mit.edu/watch/mitef-nyc-whats-next-for-us-wireless-broadband-8344/</link>
                         	<description><![CDATA[
        Our panelists include representatives from service providers, application developers, and sources of capital. They will share their experience and offer their views on the future of wireless broadband and how it may impact today`s business models.  
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135818-9-0_i9m2anmz.jpg" height="100" width="165" />                         
                        	<pubDate>Fri, 14 Oct 2011 23:06:54 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/mitef-nyc-whats-next-for-us-wireless-broadband-8344/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[RLE Investigator Profile Video Series: Gregory W. Wornell]]></title>                         
                         	<link>http://video.mit.edu/watch/rle-investigator-profile-video-series-gregory-w-wornell-8101/</link>
                         	<description><![CDATA[
        Professor Gregory W. Wornell of MIT discusses research and education in his group, and the intellectual challenges facing engineers at the frontiers of information encoding, extraction, and manipulation.
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135802-9-1_uzut61bh.jpg" height="100" width="165" />                         
                        	<pubDate>Mon, 22 Aug 2011 18:37:18 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/rle-investigator-profile-video-series-gregory-w-wornell-8101/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[&quot;Social networks that balance themselves&quot; by Steven Strogatz]]></title>                         
                         	<link>http://video.mit.edu/watch/social-networks-that-balance-themselves-by-steven-strogatz-7653/</link>
                         	<description><![CDATA[
        The second of Steven Strogatz's Simons Lectures, given in the MIT Department of Mathematics in April, 2011.
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135724-9-1_zke5h4hx.jpg" height="100" width="165" />                         
                        	<pubDate>Thu, 12 May 2011 15:50:53 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/social-networks-that-balance-themselves-by-steven-strogatz-7653/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Academic Leaders: Perspectives and Current Challenges]]></title>                         
                         	<link>http://video.mit.edu/watch/academic-leaders-perspectives-and-current-challenges-9675/</link>
                         	<description><![CDATA[
        03/28/2011 10:30 AM KresgeDr. Ian A. Waitz, Jerome C. Hunsaker Professor and Department Head, Department of Aeronautics and Astronautics, MIT ;  Shirley Ann Jackson, '68, PhD '73, President, Rensselaer Polytechnic Institute;  Charles M. Vest, HM, MIT President Emeritus and President, National Academy of EngineeringDescription: Two influential academic leaders, both holding a significant place in MIT's history, reflect on efforts to achieve gender equity in science and engineering at MIT and other institutions of higher learning. 

&quot;In spite of steps to promote diversity, underrepresentation of women at all faculty levels persists,&quot; says Shirley Ann Jackson.  She admires MIT's decade&quot;plus work on these issues, which spurred much broader self&quot; scrutiny and policy changes among research universities, yet notes that &quot;we're still a long way from gender equity in science and engineering.&quot;  Jackson says, &quot;Not knowing, not understanding and not intending do not get us off the hook. We're still responsible for bias that puts obstacles in front of talented, capable people.&quot; This is not merely a moral problem, Jackson says, but a practical one, too, because society cannot afford to deny itself the expertise of so many competent people &quot;when we face immense global challenges.&quot;

At every step of the way, from entering college as a science or engineering major, sticking with a course of studies through graduate school,  and then attaining tenure, women need &quot;bridges&quot; to help them get to the next level, whether through mentors, flexible tenure clocks or childcare. Jackson notes that the &quot;unequal burden of family turns gaps in the road into chasms.&quot;  She detects new hurdles on the horizon as well: family and gender issues are still viewed as &quot;women's issues,&quot; at least beyond MIT; and economic pressures may create resistance to gender bias measures. Jackson also points to the phenomenon of &quot;pink collar discrimination,&quot; where salary levels drop in some fields such as biomedical engineering as women's numbers approach men's, suggesting that women may be undervalued, or lack tough salary negotiating skills. Jackson believes social networks may be key to introducing the next generation to science and engineering, and helping women establish and maintain careers.

Speaking &quot;as a white male,&quot; Charles Vest says men of his generation in academia assumed that &quot;if you filled the undergraduate pipeline,&quot; you'd solve the problem of underrepresentation of women in science and engineering professions. The reality was different, admits Vest, because even if 50% of the undergraduates in these fields were women, many fewer ended up with careers in science and engineering. Vest describes the data&quot;driven studies conducted at MIT, and the groundbreaking policies that followed, which led to advances in bolstering and retaining numbers of women graduates and faculty. He points to similar ventures at other universities.

But for all the work to address gender issues in academia, major leaks persist in the pipeline. He displays national data showing how the number of women Ph.D.'s has grown enormously in life sciences in the past decade, but lags greatly in physical sciences and especially in engineering. A recent study showed that only 1.6% of all female university graduates are engineers, which greatly disturbs Vest: &quot;This is not a number that can sustain our society going into the future.&quot;  Ultimately, he says, &quot;Numbers really do matter,&quot; because &quot;we have to achieve critical mass before the culture starts to change.&quot;
About the Speaker(s): Ian A. Waitz was named Dean of Engineering in February 2011. He also serves as the Director of the Partnership for AiR Transportation Noise and Emissions Reduction (PARTNER), an FAA/NASA/Transport Canada&quot;sponsored Center of Excellence. His principal areas of interest are the modeling and evaluation of climate, local air quality and noise impacts of aviation.
Waitz has written approximately 75 technical publications, including a report to the U.S. Congress on aviation and the environment. He holds three patents and has consulted for many organizations. During 2002&quot;2005 he was Deputy Head of the Department of Aeronautics and Astronautics. He has also served as an associate editor of the AIAA Journal of Propulsion and Power. In 2003, Waitz received a NASA Turning Goals Into Reality Award for Noise Reduction. He was awarded the FAA 2007 Excellence in Aviation Research Award. He is a Fellow of the AIAA, and an ASME and ASEE member. He was honored with the 2002 MIT Class of 1960 Innovation in Education Award and appointment as an MIT MacVicar Faculty Fellow in 2003.
Waitz received his B.S. in 1986 from the Pennsylvania State University; his M.S. in 1988, from George Washington University; and his Ph.D.in 1991, from the California Institute of Technology.Host(s): Office of the President, MIT150 Inventional Wisdom
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120127222236-9-1_evx26dy4.jpg" height="100" width="165" />                         
                        	<pubDate>Mon, 28 Mar 2011 04:00:00 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/academic-leaders-perspectives-and-current-challenges-9675/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Data-driven Traffic Modeling, Prediction, and Planning]]></title>                         
                         	<link>http://video.mit.edu/watch/data-driven-traffic-modeling-prediction-and-planning-9707/</link>
                         	<description><![CDATA[
        03/15/2011 4:00 PM 3&quot;270Daniela Rus, MIT Electrical Engineering and Computer Science Associate Director of CSAIL;  Description: Some professors work primarily in labs, and others mainly at desks.  Daniela Rus conducts her research on the bustling streets of Singapore, where she is helping to design a &quot;future mobility project&quot; whose goal is to &quot;marry information technology with the transportation industry.&quot;  This venture aims to improve urban passenger and freight transportation, addressing issues of gridlock and other traffic frustrations _ a giant step toward a more rational, sustainable travel system. 

Rus's work, part of the Singapore&quot;MIT Alliance for Research and Technology, involves piloting a &quot;mobility on demand&quot; transport network on a campus springing up to host foreign research groups.  Part of this vision involves creating autonomous robot vehicles (golf carts with brains) that can sense their way with laser scanners and GPS to pick people up at one point, and drop them off at another. These robots must navigate their way through a densely populated human environment, avoiding collisions and timing departures and arrivals with precision. Fleets of lightweight vehicles figure in the dream of making cities greener by decreasing private vehicle use.

In addition, as part of this multi&quot;phase project, Rus and her collaborators are collecting and analyzing vast amounts of data on current traffic patterns in Singapore, with the goal of &quot;maximizing the experience in traffic.&quot;  Accessing GPS information from Singapore's 16 thousand taxis, her group gathered data logged at one&quot;minute intervals on taxi speed, location, and occupancy. &quot;This rich data set for the entire country is a source of joy for me and my colleagues,&quot; says Rus. This information showed traffic spikes, and the most frequent origins and destinations _ &quot;an interesting way of seeing what everyone in Singapore is up to.&quot; 

With data gathered from roadbed detectors as well, Rus built up predictions about how taxi and general traffic moved from day to day, and then came up with algorithms for mapping &quot;congestion aware routing,&quot; not just for single users, but for the entire city. Says Rus, &quot;The system computes different paths according to different times of day,&quot; and can&quot; help cars get from one point to another without getting stuck.&quot;  Rus proudly relates that her algorithm works better &quot;than the simple searches Google supports.&quot;

In the final phase of the project, says Rus, autonomous robot cars will be deployed carrying onboard navigation systems for sensing and predicting traffic patterns, picking up and dropping off riders at stations so as to minimize wait times, and generally moving where needed &quot;in a congestion aware way.&quot;  
About the Speaker(s): Daniela Rus is also the co&quot;director of the CSAIL Center for Robotics, and an associate director of CSAIL.  Her research interests include distributed robotics, mobile computing, and programmable matter. She has several research activities in environmental robotics. She is the recipient of an NSF Career award and an Alfred P. Sloan Foundation fellowship. She is a class of 2002 MacArthur Fellow, and a fellow of AAAI.
Previously, she was an assistant professor, associate professor, and professor in the Computer Science Department at Dartmouth. She holds a Ph.D. in computer science from Cornell University. Host(s): School of Engineering, Transportation@MIT
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120127222239-9-1_43fcbnq9.jpg" height="100" width="165" />                         
                        	<pubDate>Tue, 15 Mar 2011 04:00:00 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/data-driven-traffic-modeling-prediction-and-planning-9707/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Unsupervised learning for perceptrons]]></title>                         
                         	<link>http://video.mit.edu/watch/unsupervised-learning-for-perceptrons-6718/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135615-9-1_un7wfdg4.jpg" height="100" width="165" />                         
                        	<pubDate>Fri, 21 Jan 2011 21:04:13 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/unsupervised-learning-for-perceptrons-6718/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Lecture 23]]></title>                         
                         	<link>http://video.mit.edu/watch/lecture-23-6708/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135614-9-1_x5gbejhj.jpg" height="100" width="165" />                         
                        	<pubDate>Thu, 20 Jan 2011 23:21:05 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/lecture-23-6708/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Gradient learning of trajectories]]></title>                         
                         	<link>http://video.mit.edu/watch/gradient-learning-of-trajectories-6690/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135613-9-1_b0q6emge.jpg" height="100" width="165" />                         
                        	<pubDate>Fri, 14 Jan 2011 21:51:02 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/gradient-learning-of-trajectories-6690/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Final Review]]></title>                         
                         	<link>http://video.mit.edu/watch/final-review-6688/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135612-9-1_xctzg4ii.jpg" height="100" width="165" />                         
                        	<pubDate>Fri, 14 Jan 2011 21:36:41 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/final-review-6688/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Final Exam Review Part II]]></title>                         
                         	<link>http://video.mit.edu/watch/final-exam-review-part-ii-6686/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135612-9-1_xot6ahci.jpg" height="100" width="165" />                         
                        	<pubDate>Fri, 14 Jan 2011 21:03:54 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/final-exam-review-part-ii-6686/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Lateral excitation and global inhibition]]></title>                         
                         	<link>http://video.mit.edu/watch/lateral-excitation-and-global-inhibition-6685/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135612-9-1_yyq39vhh.jpg" height="100" width="165" />                         
                        	<pubDate>Fri, 14 Jan 2011 19:34:34 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/lateral-excitation-and-global-inhibition-6685/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Self-excitation and global inhibition]]></title>                         
                         	<link>http://video.mit.edu/watch/self-excitation-and-global-inhibition-6679/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135612-9-1_qk8lnrxu.jpg" height="100" width="165" />                         
                        	<pubDate>Thu, 13 Jan 2011 23:38:44 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/self-excitation-and-global-inhibition-6679/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[REINFORCE algorithms &amp; Hedonistic neurons]]></title>                         
                         	<link>http://video.mit.edu/watch/reinforce-algorithms-a-hedonistic-neurons-6678/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135612-9-1_grjml5hw.jpg" height="100" width="165" />                         
                        	<pubDate>Thu, 13 Jan 2011 23:32:52 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/reinforce-algorithms-a-hedonistic-neurons-6678/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Reinforcement learning. Hedonistic synapses]]></title>                         
                         	<link>http://video.mit.edu/watch/reinforcement-learning-hedonistic-synapses-6677/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135612-9-1_hue7h52x.jpg" height="100" width="165" />                         
                        	<pubDate>Thu, 13 Jan 2011 23:18:32 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/reinforcement-learning-hedonistic-synapses-6677/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Neural integrators]]></title>                         
                         	<link>http://video.mit.edu/watch/neural-integrators-6675/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135612-9-1_zys660t3.jpg" height="100" width="165" />                         
                        	<pubDate>Thu, 13 Jan 2011 22:41:03 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/neural-integrators-6675/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Neural network models of the retina]]></title>                         
                         	<link>http://video.mit.edu/watch/neural-network-models-of-the-retina-6674/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135612-9-1_o8ioy3r3.jpg" height="100" width="165" />                         
                        	<pubDate>Thu, 13 Jan 2011 22:23:26 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/neural-network-models-of-the-retina-6674/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[The capacity of the perceptron]]></title>                         
                         	<link>http://video.mit.edu/watch/the-capacity-of-the-perceptron-6672/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135611-9-1_8fwg1xyu.jpg" height="100" width="165" />                         
                        	<pubDate>Thu, 13 Jan 2011 20:55:45 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/the-capacity-of-the-perceptron-6672/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Backpropagation applications]]></title>                         
                         	<link>http://video.mit.edu/watch/backpropagation-applications-6670/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135611-9-1_4bkxnoy7.jpg" height="100" width="165" />                         
                        	<pubDate>Thu, 13 Jan 2011 20:05:53 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/backpropagation-applications-6670/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Multilayer perceptrons and backpropagation]]></title>                         
                         	<link>http://video.mit.edu/watch/multilayer-perceptrons-and-backpropagation-6669/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135611-9-1_v0tvgkrz.jpg" height="100" width="165" />                         
                        	<pubDate>Thu, 13 Jan 2011 20:02:36 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/multilayer-perceptrons-and-backpropagation-6669/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Perceptron as feature detector]]></title>                         
                         	<link>http://video.mit.edu/watch/perceptron-as-feature-detector-6668/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135611-9-1_09yjpusd.jpg" height="100" width="165" />                         
                        	<pubDate>Thu, 13 Jan 2011 19:49:21 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/perceptron-as-feature-detector-6668/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Midterm Review]]></title>                         
                         	<link>http://video.mit.edu/watch/midterm-review-6661/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135611-9-1_x460uzhp.jpg" height="100" width="165" />                         
                        	<pubDate>Tue, 11 Jan 2011 22:38:19 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/midterm-review-6661/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Hybrid analog-digital computation]]></title>                         
                         	<link>http://video.mit.edu/watch/hybrid-analog-digital-computation-6660/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135611-9-1_35caqx25.jpg" height="100" width="165" />                         
                        	<pubDate>Tue, 11 Jan 2011 22:25:02 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/hybrid-analog-digital-computation-6660/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Feedback in linear networks]]></title>                         
                         	<link>http://video.mit.edu/watch/feedback-in-linear-networks-6657/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135610-9-1_rimman63.jpg" height="100" width="165" />                         
                        	<pubDate>Tue, 11 Jan 2011 21:58:30 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/feedback-in-linear-networks-6657/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Griniasty-Tsodyks-Amit model]]></title>                         
                         	<link>http://video.mit.edu/watch/griniasty-tsodyks-amit-model-6655/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135610-9-1_hf43gzsp.jpg" height="100" width="165" />                         
                        	<pubDate>Tue, 11 Jan 2011 20:58:09 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/griniasty-tsodyks-amit-model-6655/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Models of associative memory]]></title>                         
                         	<link>http://video.mit.edu/watch/models-of-associative-memory-6649/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135610-9-1_wyeaa9fb.jpg" height="100" width="165" />                         
                        	<pubDate>Mon, 10 Jan 2011 22:11:48 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/models-of-associative-memory-6649/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Vector quantization and Principal component analysis]]></title>                         
                         	<link>http://video.mit.edu/watch/vector-quantization-and-principal-component-analysis-6648/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135610-9-1_19fk55ay.jpg" height="100" width="165" />                         
                        	<pubDate>Mon, 10 Jan 2011 21:59:39 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/vector-quantization-and-principal-component-analysis-6648/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Rehash of midterm exam]]></title>                         
                         	<link>http://video.mit.edu/watch/rehash-of-midterm-exam-6646/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135610-9-1_q6q01dcx.jpg" height="100" width="165" />                         
                        	<pubDate>Mon, 10 Jan 2011 21:02:29 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/rehash-of-midterm-exam-6646/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Intra-group excitation and global inhibition]]></title>                         
                         	<link>http://video.mit.edu/watch/intra-group-excitation-and-global-inhibition-6645/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135610-9-1_vdz4zr0f.jpg" height="100" width="165" />                         
                        	<pubDate>Mon, 10 Jan 2011 20:43:17 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/intra-group-excitation-and-global-inhibition-6645/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Manipulating the MNIST database in MATLAB]]></title>                         
                         	<link>http://video.mit.edu/watch/manipulating-the-mnist-database-in-matlab-6644/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135609-9-1_anv7hlzx.jpg" height="100" width="165" />                         
                        	<pubDate>Mon, 10 Jan 2011 19:55:56 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/manipulating-the-mnist-database-in-matlab-6644/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Definitions of computational neuroscience and neural networks]]></title>                         
                         	<link>http://video.mit.edu/watch/definitions-of-computational-neuroscience-and-neural-networks-6642/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135609-9-1_07jtt6ri.jpg" height="100" width="165" />                         
                        	<pubDate>Mon, 10 Jan 2011 19:00:40 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/definitions-of-computational-neuroscience-and-neural-networks-6642/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Perceptron learning rule and Convergence theorem.]]></title>                         
                         	<link>http://video.mit.edu/watch/perceptron-learning-rule-and-convergence-theorem-6641/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135609-9-1_hjjmheaj.jpg" height="100" width="165" />                         
                        	<pubDate>Mon, 10 Jan 2011 18:54:32 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/perceptron-learning-rule-and-convergence-theorem-6641/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Bifurcation theory]]></title>                         
                         	<link>http://video.mit.edu/watch/bifurcation-theory-6632/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135609-9-1_pobznlkp.jpg" height="100" width="165" />                         
                        	<pubDate>Thu, 06 Jan 2011 20:57:18 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/bifurcation-theory-6632/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Ion channels and Markov processes]]></title>                         
                         	<link>http://video.mit.edu/watch/ion-channels-and-markov-processes-6630/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135608-9-1_njubj4vk.jpg" height="100" width="165" />                         
                        	<pubDate>Thu, 06 Jan 2011 18:37:53 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/ion-channels-and-markov-processes-6630/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Review]]></title>                         
                         	<link>http://video.mit.edu/watch/review-6605/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135607-9-1_61kjk3z1.jpg" height="100" width="165" />                         
                        	<pubDate>Tue, 04 Jan 2011 00:09:36 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/review-6605/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Nernst equation and passive electrical properties of neurons]]></title>                         
                         	<link>http://video.mit.edu/watch/nernst-equation-and-passive-electrical-properties-of-neurons-6604/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135607-9-1_jll638x0.jpg" height="100" width="165" />                         
                        	<pubDate>Mon, 03 Jan 2011 21:34:29 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/nernst-equation-and-passive-electrical-properties-of-neurons-6604/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Synaptic transmission]]></title>                         
                         	<link>http://video.mit.edu/watch/synaptic-transmission-6585/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135605-9-1_ckkm52gt.jpg" height="100" width="165" />                         
                        	<pubDate>Tue, 21 Dec 2010 19:11:05 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/synaptic-transmission-6585/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Cable theory]]></title>                         
                         	<link>http://video.mit.edu/watch/cable-theory-6579/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135605-9-1_1yqvuin4.jpg" height="100" width="165" />                         
                        	<pubDate>Mon, 20 Dec 2010 21:49:29 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/cable-theory-6579/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Diffusion and calcium dynamics]]></title>                         
                         	<link>http://video.mit.edu/watch/diffusion-and-calcium-dynamics-6577/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	                         
                        	<pubDate>Mon, 20 Dec 2010 21:28:17 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/diffusion-and-calcium-dynamics-6577/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Final review]]></title>                         
                         	<link>http://video.mit.edu/watch/final-review-6576/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135605-9-1_0avnum7g.jpg" height="100" width="165" />                         
                        	<pubDate>Mon, 20 Dec 2010 20:51:15 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/final-review-6576/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Synaptic plasticity]]></title>                         
                         	<link>http://video.mit.edu/watch/synaptic-plasticity-6574/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135604-9-1_gmelygnj.jpg" height="100" width="165" />                         
                        	<pubDate>Mon, 20 Dec 2010 20:46:21 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/synaptic-plasticity-6574/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Phase plane analysis of the Morris-Lecar model]]></title>                         
                         	<link>http://video.mit.edu/watch/phase-plane-analysis-of-the-morris-lecar-model-6572/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135604-9-1_t97xdgi4.jpg" height="100" width="165" />                         
                        	<pubDate>Fri, 17 Dec 2010 21:29:07 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/phase-plane-analysis-of-the-morris-lecar-model-6572/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Visual receptive fields II]]></title>                         
                         	<link>http://video.mit.edu/watch/visual-receptive-fields-ii-6571/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135604-9-1_lguuq5af.jpg" height="100" width="165" />                         
                        	<pubDate>Fri, 17 Dec 2010 19:59:54 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/visual-receptive-fields-ii-6571/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Hodgkin-Huxley model]]></title>                         
                         	<link>http://video.mit.edu/watch/hodgkin-huxley-model-6570/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135604-9-1_i9dbzxpc.jpg" height="100" width="165" />                         
                        	<pubDate>Fri, 17 Dec 2010 19:41:55 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/hodgkin-huxley-model-6570/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Midterm post-mortem]]></title>                         
                         	<link>http://video.mit.edu/watch/midterm-post-mortem-6569/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135604-9-1_qpuynyts.jpg" height="100" width="165" />                         
                        	<pubDate>Fri, 17 Dec 2010 19:25:17 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/midterm-post-mortem-6569/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[More about convolution and correlation.]]></title>                         
                         	<link>http://video.mit.edu/watch/more-about-convolution-and-correlation-6565/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135604-9-1_qkq4b3l9.jpg" height="100" width="165" />                         
                        	<pubDate>Thu, 16 Dec 2010 19:16:26 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/more-about-convolution-and-correlation-6565/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Convolution, correlation, Weiner-Hopf equations]]></title>                         
                         	<link>http://video.mit.edu/watch/convolution-correlation-weiner-hopf-equations-6564/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135604-9-1_ggxz1k8q.jpg" height="100" width="165" />                         
                        	<pubDate>Thu, 16 Dec 2010 18:24:10 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/convolution-correlation-weiner-hopf-equations-6564/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Introduction]]></title>                         
                         	<link>http://video.mit.edu/watch/introduction-6563/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135604-9-1_0rbr00r0.jpg" height="100" width="165" />                         
                        	<pubDate>Wed, 15 Dec 2010 21:58:57 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/introduction-6563/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Poisson processes and spike train statistics.]]></title>                         
                         	<link>http://video.mit.edu/watch/poisson-processes-and-spike-train-statistics-6551/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135603-9-1_xbr680vj.jpg" height="100" width="165" />                         
                        	<pubDate>Mon, 13 Dec 2010 20:36:10 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/poisson-processes-and-spike-train-statistics-6551/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Probability theory and Bernoulli processes.]]></title>                         
                         	<link>http://video.mit.edu/watch/probability-theory-and-bernoulli-processes-6549/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135603-9-1_dznk4dan.jpg" height="100" width="165" />                         
                        	<pubDate>Mon, 13 Dec 2010 18:59:42 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/probability-theory-and-bernoulli-processes-6549/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Features and filters in vision]]></title>                         
                         	<link>http://video.mit.edu/watch/features-and-filters-in-vision-6548/</link>
                         	<description><![CDATA[
        
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135603-9-1_o5sca5i2.jpg" height="100" width="165" />                         
                        	<pubDate>Mon, 13 Dec 2010 18:39:14 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/features-and-filters-in-vision-6548/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Autism Research: Progress and Promises]]></title>                         
                         	<link>http://video.mit.edu/watch/autism-research-progress-and-promises-9632/</link>
                         	<description><![CDATA[
        10/14/2010 4:45 PM 46Gerald Fischbach, Scientific Director, The Simons FoundationDescription: &quot;Imagine what it's like to go through life without understanding what people you are with are thinking,&quot; poses Gerald Fischbach.  &quot;You have no way of gauging whether they are angry, sad or happy.&quot;  At the core of the group of disorders known as autism, says Fischbach, is damaged social cognition, a kind of prison of the mind.  First defined in 1943, autism has not readily yielded its secrets to scientists, but in the past decade, says Fischbach, there has been &quot;remarkable progress&quot; in working out the disorder's likely causes and mechanisms.

As many as one in 100 people are now said to live with autism, up from one in 1000 a few years ago, but Fischbach believes the increasing numbers are more likely due to broadening public awareness and continually expanding definitions of the disorder, rather than an &quot;epidemic.&quot;  Research on this pervasive problem proceeds on several fronts: genetic risk factors, molecular mechanisms, and neural circuits, cognition and behavior.  Fischbach notes a plethora of genetic approaches to autism but says, &quot;We researchers feel we are on to something&quot; focusing on a type of genetic change called a copy number variant.  

Ordinarily, individuals inherit a gene from each parent, but sometimes this process goes awry, leading to variances in the number of copies of genes. Studies show that deletions in copy numbers that occur in a certain region of DNA correspond to a &quot;big risk factor&quot; for autism.  But these clues are just the start, says Fischbach. Now researchers must begin &quot;figuring out precisely which gene is at fault, and what it is doing in the nervous system.&quot;

Fischbach's Simons Foundation is assembling a research pool of families with autistic members to serve as a long&quot;term resource for scientists investigating not just copy number variants, but also other disorders with autistic features, including Rett syndrome and Fragile X syndrome.  McGovern Institute research is revealing the central role of the synapse in these disorders, and imaging work is helping to point out regions of the brain central to the performance of social tasks and possibly to autistic behaviors. 

Fischbach hopes in the next decade science will figure out not just gene factors, but the neural circuitry at play in autism.  Says Fischbach, &quot;In the end, we need to develop theories and models to account for the link between genes and behavior  It's not enough to say autism is a disorder of synapses, or of connections. Of course it is. We need more specific hypotheses about autism and how it relates to social behavior.&quot;
About the Speaker(s): Gerald D. Fischbach joined the Simons Foundation in early 2006 to oversee the Simons Foundation Autism Research Initiative. Formerly Dean of the Faculties of Health Sciences at Columbia University, and former Director of the National Institute of Neurological Disorders and Stroke at the N.I.H. from 1998&quot;2001, Fischbach received his M.D. in 1965 from Cornell University Medical School and interned at the University of Washington Hospital in Seattle. He began his research career at the National Institutes of Health, serving from 1966 _ 1973. He subsequently served on the faculty of Harvard Medical School, first as Associate Professor of Pharmacology from 1973 _ 1978 and then as Professor until 1981. From 1981 _ 1990, Fischbach was the Edison Professor of Neurobiology and Head of the Department of Anatomy and Neurobiology at Washington University School of Medicine. In 1990, he returned to Harvard Medical School where he was the Nathan Marsh Pusey Professor of Neurobiology and Chairman of the Neurobiology Departments of Harvard Medical School and Massachusetts General Hospital until 1998.
Throughout his career, Fischbach has studied the formation and maintenance of synapses, the contacts between nerve cells and their targets through which information is transferred in the nervous system. He pioneered the use of nerve cell cultures to study the electrophysiology, morphology, and biochemistry of developing nerve _ muscle and inter&quot;neuronal synapses. His current research is focused on roles that neurotrophic factors play in determination of neural precursor fate, synapse formation, and neuronal survival.
Fischbach is a member of the National Academy of Sciences, the American Academy of Arts and Science, the Institute of Medicine, and a fellow of the American Association for the Advancement of Science and a non&quot;resident Fellow of the Salk Institute.
Host(s): School of Science, McGovern Institute for Brain Research at MIT
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120127222233-9-1_n0npp7ph.jpg" height="100" width="165" />                         
                        	<pubDate>Thu, 14 Oct 2010 04:00:00 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/autism-research-progress-and-promises-9632/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[McGovern Institute: Ten Years of Understanding the Brain in Health and Disease]]></title>                         
                         	<link>http://video.mit.edu/watch/mcgovern-institute-ten-years-of-understanding-the-brain-in-health-and-disease-9610/</link>
                         	<description><![CDATA[
        10/14/2010 4:00 PM 46Robert Desimone, Director, McGovern Institute; The Doris and Don Berkey Professor of NeuroscienceDescription: Psychiatric illness and neurological disorders such as autism, depression, and Alzheimer's disease cause countless families to suffer, and require prodigious economic resources to manage.  Now, thanks to major advances in genomics, systems neuroscience, and human brain imaging, says Robert Desimone, scientists are unlocking key secrets in how the human brain functions, work that may herald new and more effective therapies for neural disorders.

In his keynote address, Desimone pays tribute to McGovern Institute researchers who are tackling a common problem: understanding the neural circuit.  Ed Boyden works with different wavelengths of light to turn targeted cells on and off in living brains, &quot;much the way a conductor controls musicians in an orchestra,&quot; says Desimone.  Boyden has focused in particular on the &quot;straightforward circuit&quot; of the retina, replacing dead photoreceptors with genetically manipulated, light&quot;sensitive molecules so that mice with impaired vision see light again. Someday, this research could help people with similar kinds of blindness.

McGovern researchers are also untangling the more complex neural circuitry associated with psychiatric diseases and developmental disorders.  Michale Fee's model of the neural basis for bird song identified a brain structure that has an exact parallel in mammals -- a loop connecting the cortex and basal ganglia in which motor sequences move through a chain of neurons in precise order,  &quot;like dominoes falling.&quot;  A mistake in this circuit in humans could result in behavioral disorders. Guoping Feng demonstrates that a single malfunctioning synaptic protein can wreak havoc on the basal ganglia, disrupting learning in humans.  He has also determined that related circuits bearing gene mutations create behavior in mice that remarkably mirrors obsessive compulsive disorders in humans.

Yingxi Lin has identified a gene that helps the brain regulate the excitatory and inhibitory synapses, keeping neurons in balance, the way a thermostat regulates temperature in a room. Without this gene, mice &quot;get too much excitation&quot; and develop seizure disorders. She has discovered a comparable gene in autistic people, who also are prone to seizures. Other McGovern researchers are developing next generation diagnostic tools. John Gabrieli has mapped out the circuits central to high level cognitive functions, and will soon be deploying a new kind of imaging that gives a precise picture of dynamic changes in brain states, measured in milliseconds.  And Alan Jasanoff uses genetic engineering techniques to create new molecules that act as sensors, showing the release and flow of chemicals in the brain that can highlight both healthy and diseased circuitry.  Insights from McGovern research, says Desimone, &quot;will lay down the foundation for therapeutics of the future.&quot;
About the Speaker(s): Prior to joining the McGovern Institute in 2004, Robert Desimone was director of the Intramural Research Program at the National Institutes of Mental Health, the largest mental health research center in the world. He is a member of the National Academy of Sciences and the American Academy of Arts and Sciences and a recipient of numerous awards, including the Troland Prize of the National Academy of Sciences, and the Golden Brain Award of the Minerva Foundation. Desimone received his B.A. from Macalester College and his Ph.D. from Princeton University. Host(s): School of Science, McGovern Institute for Brain Research at MIT
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120127222231-9-1_ealqur8b.jpg" height="100" width="165" />                         
                        	<pubDate>Thu, 14 Oct 2010 04:00:00 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/mcgovern-institute-ten-years-of-understanding-the-brain-in-health-and-disease-9610/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Engineering Smarter Drivers]]></title>                         
                         	<link>http://video.mit.edu/watch/engineering-smarter-drivers-9614/</link>
                         	<description><![CDATA[
        10/05/2010 4:00 PM 4&quot;237Alex (Sandy) Pentland, PhD '82, Toshiba Professor of Media Arts and Sciences, and Director of Human Dynamics Research, MIT Media LabDescription: While automakers market increasingly intelligent cars, they may be missing the point.  No matter how sophisticated the vehicle's brain, suggests Alex (Sandy) Pentland, the smartest element on the road is still the human driver.  In search of safe, responsive vehicles, designers should not think of separate components -- machine and operator -- but rather, an integrated system comprised of two, complementary intelligences. 

Tackling this challenge involves analyzing human behavior -- not the traditional purview of engineers who &quot;are scared off by the noise, the randomness of people.&quot;  Pentland, on the other hand, has long explored human decision&quot;making in a variety of settings, including car driving.  Working with an automaker, he outfitted test vehicles with sensors on the steering wheel, brakes and elsewhere, to &quot;determine predictive signals of driving.&quot;  The sensors permitted the analysis of &quot;clusters of behaviors,&quot; so Pentland could figure out with 95% accuracy &quot;what people would do before they did it.&quot;  From developing a model of the driver's behavior, he moved on to neighboring drivers' patterns, to paint a picture of road interactions and signaling.

This research has resulted in a system now deployed in Nissan cars as a &quot;safety shield&quot; -- a computer brain that uses predictive knowledge to help &quot;nudge back&quot; a driver who may be straying into the wrong lane, or gently decelerate if the driver is speeding into the car ahead.  Pentland's &quot;general philosophy&quot; about creating an interface between people and an intelligent vehicular system involves recognizing that the human is in charge, never the vehicle, lest &quot;the human stop paying attention.&quot;  It is about establishing a &quot;joint control mode&quot; so &quot;car and human are cooperating&quot; in a way that feels natural.  Indeed, Pentland notes that there is evidence these sensor systems help people become better drivers.  

Beyond this basic work, Pentland is introducing robot &quot;friends&quot; into cars, to help guide a driver's attention in appropriate ways.  He is also extending his intricate models of driving patterns toward better route navigation technology.  Pentland builds traffic flow maps that are based on the &quot;conditional dependence&quot; among driving decisions made en route, which may prove extremely helpful in alerting drivers to construction obstacles or other hazards.  He has also mapped mobility patterns of certain groups in a city, by monitoring taxi and cell phone use, and can predict where specific groups of people travel, shop and eat. This research could prove useful to urban planners laying out a public transportation grid, and someday, might help in making greener cities or battling epidemics. 
 
About the Speaker(s): Alex (Sandy) Pentland is a pioneer in wearable computers, health systems, smart environments, and technology for developing countries. 
He is a co&quot;founder of the Wearable Computing research community, the Autonomous Mental Development research community, the Center for Future Health, and was the founding director of the Media Lab Asia.  He was formerly the Academic Head of the MIT Media Laboratory. Pentland was chosen by Newsweek as one of the 100 Americans most likely to shape the next century.

Host(s): School of Engineering, Transportation@MIT
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120127222231-9-1_x5m4gdq1.jpg" height="100" width="165" />                         
                        	<pubDate>Tue, 05 Oct 2010 04:00:00 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/engineering-smarter-drivers-9614/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Public-health networks]]></title>                         
                         	<link>http://video.mit.edu/watch/public-health-networks-9788/</link>
                         	<description><![CDATA[Assistant professor at MIT Sloan Damon Centola describes research in which he compared the dissemination of public-health information through social networks with two different structures.]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120128154622-8-Mn9s2rt7PBs.jpg" height="100" width="165" />                         
                        	<pubDate>Thu, 23 Sep 2010 15:53:35 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/public-health-networks-9788/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[A Network Biology Approach to Cancer]]></title>                         
                         	<link>http://video.mit.edu/watch/a-network-biology-approach-to-cancer-5795/</link>
                         	<description><![CDATA[
        James Collins - Boston University
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135510-9-1_ip8qfof6.jpg" height="100" width="165" />                         
                        	<pubDate>Fri, 25 Jun 2010 20:35:25 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/a-network-biology-approach-to-cancer-5795/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[RAS and PI 3-kinase Signaling Networks in Cancer]]></title>                         
                         	<link>http://video.mit.edu/watch/ras-and-pi-3-kinase-signaling-networks-in-cancer-5751/</link>
                         	<description><![CDATA[
        Julian Downward - Cancer Research UK, London Research Center
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135507-9-1_3yhjhhn1.jpg" height="100" width="165" />                         
                        	<pubDate>Tue, 22 Jun 2010 17:16:04 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/ras-and-pi-3-kinase-signaling-networks-in-cancer-5751/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Visual Overviews for Cultural Heritage:  Interactive Exploration for Scholars in the Humanities, Arts, and Beyond]]></title>                         
                         	<link>http://video.mit.edu/watch/visual-overviews-for-cultural-heritage-interactive-exploration-for-scholars-in-the-humanities-art-9597/</link>
                         	<description><![CDATA[
        05/20/2010 6:00 PM Morss Hall Walker Memorial Ben Shneiderman, University of MarylandDescription: A focus on designing technologies that allow the &quot;visualization of things not visible&quot; has been at the center of Ben Shneiderman's work over the past two decades. He advocates the discovery of temporal patterns, relationships and clusters via an empowering user experience which enables discovery at a customizable pace and depth. 

Shneiderman makes a clear distinction between high&quot;resolution presentation (ala Edward Tufte) and discovery, which he defines as &quot;the dynamics of interaction.&quot; Noting that different patterns will be interesting to different people, he suggests that the capacity to quickly test out a viewpoint, to ask a large number of questions in a short amount of timeis an &quot;enriching gift.&quot; 

Shneiderman cites several different projects which utilize various methodologies of user exploration and empowerment, principles applicable to the scientific and technical world, as well as the humanities and arts. The best known of these is Spotfire, a commercial application of visual data mining and information visualization. (User control _ via dynamic query sliders, for example &quot; directs the rapid updating of a display containing color&quot; and size&quot;coded points.) 

He describes other methodologies _ including treemaps (space&quot;constrained visualizations of hierarchical structures), TimeSearcher (a visual analysis tool for time series data), FeatureLens (interactive visualization of text patterns) and Social Action (for social network data, now incorporated into NodeXL) _ as capable of giving &quot;answers to questions you didn't know you had.&quot; 

Questions from the audience address the challenges of visualizing uncertainty and the notion of a &quot;user&quot; as a participant whose contributions and engagement actually reshape the very conditions of the system. Shneiderman emphasizes a desire to not only empower users but to alert them to potential hazards of interpretation and make them more cautious users, readers and/or participants. 

Additionally, Shneiderman encourages an information visualization approach through which selection strategies allow &quot;treasures to rise to the surface&quot; from vast databases. Noting ongoing constraints of time and budget, he emphasizes the processes of categorization and prioritization, and supports courage of ownership for decisions made.
About the Speaker(s): A pioneer of information visualization, human&quot;computer interaction, and user interface design, Ben Shneiderman'swork has focused on database design, human factors in computer systems and information design, and technology&quot;mediated social participation.  

Concepts of information design associated with him include dynamic queries and starfield display (research that led to the development of Spotfire, the user&quot;driven analytical tool), HyperTIES, the treemap concept, the Lifelines project, PatternFinder, TimeSearcher, the Hierarchical Clustering Explorer, and universal usability, among many others. 

His book, Designing the User Interface: Strategies of Effective Human&quot;Computer Interaction, has appeared in numerous editions and had a profound impact as an educational and professional text. 

Founding Director (1983&quot;2000) of the Human&quot;Computer Interaction Laboratory (HCiL) at the University of Maryland, Shneiderman is a member of the National Academy of Engineering, a Fellow of the Association for Computing Machinery and of the American Association for the Advancement of Science, and has received the ACM CHI (Computer Human Interaction) Lifetime Achievement Award. He earned his PHD at SUNY at Stony Brook in 1973. 

Professor, Computer Science and Institute for Advanced Computer Studies, University of Maryland



&gt;http://www.cs.umd.edu/~ben/

Host(s): School of Humanities, Arts &amp; Social Sciences, HyperStudio
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120127222230-9-1_bt1u97sv.jpg" height="100" width="165" />                         
                        	<pubDate>Thu, 20 May 2010 04:00:00 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/visual-overviews-for-cultural-heritage-interactive-exploration-for-scholars-in-the-humanities-art-9597/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Concentrate on Distracted Driving: A Challenge to MIT Students from US Transportation Secretary Ray LaHood]]></title>                         
                         	<link>http://video.mit.edu/watch/concentrate-on-distracted-driving-a-challenge-to-mit-students-from-us-transportation-secretary-ray-9580/</link>
                         	<description><![CDATA[
        05/03/2010 12:00 PM E14&quot;674Ray LaHood, US Secretary of TransportationDescription: From the MIT News Office:

Research has shown that talking on a phone while driving, even with a hands&quot;free cellphone, causes as much of an impairment to driving ability as being drunk. And yet, says U.S. Secretary of Transportation Ray LaHood, while the nation has successfully cracked down on drunk driving, when it comes to cell phone use in cars, nearly everybody does it. 

This dangerous &quot;epidemic&quot; must stop, he said, and he hopes that smart people like the students at MIT will come up with ways - technological, social or political - to help curb the phenomenon, which kills thousands of people every year and causes many thousands more injuries. 

To emphasize the point, LaHood invited a local couple, Jerry Cibley and Jeri Katz of Foxborough, Massachusetts, to come to his talk to share their experience: Three years ago, Jerry was talking on the phone to his son Jordan, who was driving at the time; Jordan dropped the phone during the conversation, bent down to pick it up, and slammed into a tree. He was killed instantly. 

In calling for students to help find solutions to the problem, LaHood said, &quot;Your time at MIT is more than an opportunity, it's a responsibility.&quot; He urged students to devote themselves to helping to find solutions to real&quot;world problems such as the &quot;driving while distracted&quot; issue that he stressed in his talk, or the problem of reducing greenhouse gas emissions that cause climate change. 

&quot;Something needs to be done,&quot; he said. &quot;I challenge all of you to find solutions.&quot;
About the Speaker(s): As Secretary of Transportation, Ray LaHood leads an agency with more than 55,000 employees and a $70 billion budget that oversees air, maritime and surface transportation missions. 

Secretary LaHood's primary goals include safety across all modes, restoring economic health and creating jobs, sustainability _ shaping the economy of the coming decades by building new transportation infrastructure, and assuring that transportation policies focus on people who use the transportation system and their communities. 

Before becoming Secretary of Transportation, LaHood served for 14 years in the U.S. House of Representatives from the 18th District of Illinois (from 1995&quot;2009).  During that time he served on the House Transportation and Infrastructure Committee and, after that, on the House Appropriations Committee.  Prior to his election to the House, he served as Chief of Staff to U.S. Congressman Robert Michel, whom he succeeded in representing the 18th District, and as District Administrative Assistant to Congressman Thomas Railsback.  He also served in the Illinois State Legislature. 

Before his career in government, Secretary LaHood was a junior high school teacher, having received his degree from Bradley University in Peoria, Illinois.  He was also director of the Rock Island County Youth Services Bureau and Chief planner for the Bi&quot;States Metropolitan Planning Commission in Illinois.
Host(s): School of Engineering, Transportation@MIT
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120127222228-9-1_mqvg3dmy.jpg" height="100" width="165" />                         
                        	<pubDate>Mon, 03 May 2010 04:00:00 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/concentrate-on-distracted-driving-a-challenge-to-mit-students-from-us-transportation-secretary-ray-9580/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Government Transparency and Collaborative Journalism]]></title>                         
                         	<link>http://video.mit.edu/watch/government-transparency-and-collaborative-journalism-9717/</link>
                         	<description><![CDATA[What new ways of gathering and presenting information are evolving from the nexus of government openness and digital connectedness?]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120127222240-9-1_hjfyg5wi.jpg" height="100" width="165" />                         
                        	<pubDate>Thu, 18 Mar 2010 04:00:00 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/government-transparency-and-collaborative-journalism-9717/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Blended Learning Revisited]]></title>                         
                         	<link>http://video.mit.edu/watch/blended-learning-revisited-9557/</link>
                         	<description><![CDATA[Even when children are high achievers and facile with new technology, many seem gradually to lose their sense of wonder and curiosity, notes John Seely Brown.]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120127222226-9-1_w88z5vfd.jpg" height="100" width="165" />                         
                        	<pubDate>Wed, 10 Mar 2010 05:00:00 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/blended-learning-revisited-9557/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Transportation in Contemporary Society: A Complex Systems Approach]]></title>                         
                         	<link>http://video.mit.edu/watch/transportation-in-contemporary-society-a-complex-systems-approach-9541/</link>
                         	<description><![CDATA[
        03/09/2010 4:00 PM 3&quot;270Joseph Sussman, J R East Professor of Civil and Environmental EngineeringDescription: In the nineteen fifties and sixties, students of transportation focused on building infrastructure and applied lessons from the physical sciences to designing mobility.  Mobility was facilely linked to the engines of economic growth and expanding GDP.  In time, that perspective was replaced by a focus on transportation systems and networks.  There was a newfound emphasis on environmental impacts, land use, and intermodal freight.  There was also a growing concern on unpriced externalities.  Today, Joseph Sussman explains, with many of those problems still unsolved, transportation has entered a new phase-- a period of immense complexity or CLIOS, which stands for complex, large scale, interconnected, open and sociotechical is an acronym that is becoming the mantra of transportation engineers. While it is not as far&quot;reaching as &quot;chaos&quot; to a physicist, it is an approach with far&quot;reaching consequences for the transportation field. 

To participate in &quot;Complexity 101&quot; engineers must take account of stochastic systems, difficulties relating cause and effect, and non&quot;linear behaviors.  They must also recognize complex feedback loops between macro and micro issues; time scale anomalies, and evaluative complexity brought by new stakeholders.  Sussman observes, &quot; Even if we could wish away behavioral complexity, it would not mean that we know what we should do.&quot;  He says that transportation engineering must now embrace management, the social sciences and planning and he warns us eschew narrow representations of complex systems because they are implicitly easier to solve. 

Sussman walks us through the new tools of math and advanced technology which have evolved with with CLIOS.  In earlier times engineers could not respond with full information, disaggregate demand analysis, or real time operational data. He cites the need to apply these to find new solutions and designs--particularly ones that incorporate flexibility, reliability, and sustainability. Sussman terms these the &quot;bilities&quot;.   Taking flexibility as an example, he notes that some transportation providers, and particularly the airlines, are creating tailored and customized services for users.  Sussman poses whether the concept of flexibility could be extended to highway travel and  &quot; pay as you go&quot;.  Likewise, in automobile design, we are moving away from crash worthiness to a concept of crash avoidance.  At a more macro level, Sussman says that we can now solve problems of a scale that seemed unthinkable 5 or 10 years, i.e., problems that were seen to be beyond our computational scope. 

Sussman observes a growing connection between economics and transportation.  &quot;We are moving toward a period where new technology and mathematical solutions allow us to better recognize and value previously un&quot;priced externalities&quot;.  Increasingly, he views transportation as a regionally scaled enterprise that can be managed at the scale of the metropolitan regional level. That aligns us, he says, with economists who have long talked about metro based regions as the economic engine of society. He also says there is a need for a large national vision on the scale of the one that created the national highway infrastructure. Sussman endorses the view that the American people yearn for a big vision and are tired of cycles of crisis and doom. 
Host(s): School of Engineering, Transportation@MIT
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120127222225-9-1_v3sqmwi5.jpg" height="100" width="165" />                         
                        	<pubDate>Tue, 09 Mar 2010 05:00:00 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/transportation-in-contemporary-society-a-complex-systems-approach-9541/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Death of the News?]]></title>                         
                         	<link>http://video.mit.edu/watch/death-of-the-news-9563/</link>
                         	<description><![CDATA[
        03/02/2010 5:30 PM Wong AuditoriumMaria Balinska, Nieman Fellow, Harvard University (on leave from BBC);  Susan Glasser, Executive Editor, Foreign Policy;  Jason Pontin, Editor in Chief and Publisher, Technology ReviewDescription: While not dead, the U.S. news industry is severely depleted and likely to diminish further, these panelists agree.  But they also believe that something vibrant and enduring might emerge from this period of digital disruption. 

Moderator Jason Pontin sets the stage with his &quot;dolorous and long toll&quot; of newspapers and magazines that have gone bankrupt, or cling to life as their subscriptions and ad revenues fall.  He nevertheless invites panelists to make the case for journalism's survival.   

Susan Glasser declares herself &quot;a total convert to the idea that this transformation heralds potentially an enormous golden age for people who care about informationtransparency, knowledge, about going to places in the world you couldn't get to in the past except with enormous difficulty&quot;  While this shift has just gotten started, with producers adapting print and TV information rather than originating content for digital media, changes are coming rapidly. 

Glasser's own Foreign Policy website grew 500% in a single year (&quot;without spending a single dollar in marketing&quot;), attracting enormous numbers of users &quot;interested at a sophisticated level.&quot; Social media help drive users to the site, and suggest to Glasser an audience of millions for comparable specialized and nuanced content.  But she does not believe that her audience, interactive as it may be, will displace seasoned journalists who labor in difficult circumstances to collect, analyze and report the news.

U.K.&quot;based radio journalist Maria Balinska concurs that reporters are irreplaceable: &quot;Maybe journalism is not rocket science, but to tell a story well, with context, facts, is quite difficult. Good novelists don't walk the streets everywhere, and a good story is something that will engage our audience.&quot;   The key to survival in the digital age will involve using new tools to capture &quot;the many different publics,&quot; especially those who might have been alienated by a partisan or corrupt&quot;appearing media.

Balinska is &quot;convinced there is a hunger for understanding the world around us.&quot;  She wants to engage different audiences through a &quot;partnership model,&quot; where users inform the journalistic process.  She believes journalism should rediscover what is valuable, and look back to small&quot;town newspapers, which helped create community.  She also notes that elsewhere in the world, old and new forms of journalism are thriving: in Britain, daily national newspapers achieve circulations in the millions, and in Colombia, the population consumes its news via mobile phones.

Pontin concludes that &quot;fretfulness about the death of news may be a uniquely American perspective.&quot;  While the current business model is failing in the U.S. -- &quot;news has declining value relative to time&quot; -- Pontin believes there is a &quot;form of journalism people will pay for.&quot;   The criteria for success include offering a unique mission that's uniquely smart (&quot;don't fib to yourself); helping users with a decision &quot;that is core to self&quot;identity;&quot; and being beautifully designed.  &quot;If you say those four things, you can charge for it.&quot; 
About the Speaker(s): Jason Pontin also serves as the publisher of Technology Review, overseeing all aspects of the company's business. In previous posts, he was editor of Red Herring, editor in chief of The Acumen Journal, and wrote a regular column for the Sunday New York Times, &quot;Slipstream,&quot; about new ideas in technology. He has also written for The Economist, The Financial Times, Wired, and The Believer, among others, and is a frequent guest on television and radio, including ABC News, CNN, and NPR.Host(s): School of Humanities, Arts &amp; Social Sciences, Center for International Studies
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120127222226-9-1_cx582izt.jpg" height="100" width="165" />                         
                        	<pubDate>Tue, 02 Mar 2010 05:00:00 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/death-of-the-news-9563/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[The Future of Civic Engagement in a Broadband&quot;Enabled World]]></title>                         
                         	<link>http://video.mit.edu/watch/the-future-of-civic-engagement-in-a-broadbandenabled-world-9555/</link>
                         	<description><![CDATA[
        03/01/2010 4:00 PM Wong AuditoriumEugene J. Huang, Government Operations Director, National Broadband Task Force, Federal Communications CommissionDescription: The digital revolution that brought us Facebook, Twitter and YouTube could help revive participatory democracy in the U.S., says Eugene J. Huang.  He unveils the FCC's plan for providing broadband access to every American, and describes how its recommendations could spur more open government and greater civic engagement.

Huang is leading an FCC taskforce developing a plan to provide every American with high quality broadband internet capability.  Mandated by the Recovery Act, $7.6 billion will soon flow to deploy infrastructure throughout the U.S., by cable, wireless, or satellite; to ensure affordable access for all; and to address a group of national priorities.  Huang describes the process of fact&quot;gathering, analysis and recommendation development as the &quot;most open and transparent&quot; in the FCC's history, involving public workshops, and the use of social media and blogs to encourage citizen input.

This process in many ways has come to shape the larger goals of the broadband plan.  As Huang says, at the end of months of data collection and public discussion, &quot;we came to an obvious conclusionthat civic engagement is the lifeblood of our democracy,&quot;  and that  the broadband plan should play a major role in creating a more informed and engaged citizenry.

Vast numbers of Americans are already online, talking, debating and viewing -- an astonishing 120 million people watch more than 10 billion videos monthly. So Huang, his taskforce, and citizen participants began envisioning ways that universal, high&quot;speed digital communication and interactivity could work for the public sector.

They ended up with five recommendations: building a more open and transparent government, by making all government and judicial records freely available online, and streaming government meetings and hearings; helping public media such as PBS and NPR expand beyond their broadcast models in providing news content, and removing copyright obstacles to sharing historic materials, ultimately leading to a national digital archive; deploying social media in all government agencies; recruiting technological innovators into government, engaging citizen experts from the private sector and starting an innovation corps; and bringing the election process into the digital age, eliminating mistakes in voter registration, standardizing the process across states, and enabling military personnel overseas to cast ballots electronically.

While these measures will require a commitment across all levels of government, Huang feels sure they will lead to a transformation that can &quot;renew democracy in a broadband enabled 21st century.&quot;
About the Speaker(s): Eugene J. Huang is helping to craft the &quot;national purposes&quot; section of the National Broadband Plan, with a specific focus on the topics of government operations and civic engagement.
From 2006 to 2009, Huang served at the US Department of the Treasury.  He covered a wide range of international economic and finance issues with a special responsibility for U.S. bilateral relations with China.
Previously, Huang was a Visiting Scholar at the Stanford Institute for Economic Policy Research at Stanford University. From 2002 to 2006, he served the Commonwealth of Virginia as the Secretary of Technology and previously as the Deputy Secretary of Technology. Huang was responsible for managing the state's award winning information technology reform initiative, fostered the development of advanced broadband communications, and facilitated the growth of emerging technology industries throughout Virginia.
Huang graduated magna cum laude from the University of Pennsylvania, with a B.S. in Economics from the Wharton School, a B.S. in Electrical Engineering, and a M.S. in Telecommunications Engineering. He received a Thouron Award from the University of Pennsylvania and studied at St. John's College, Oxford University, where he received a M.Phil., with distinction, in Economic History. Huang is a term member of the Council on Foreign Relations and a member of the International Institute for Strategic Studies.
Host(s): School of Humanities, Arts &amp; Social Sciences, Center for Future Civic Media
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120127222226-9-1_6wo2ivh9.jpg" height="100" width="165" />                         
                        	<pubDate>Mon, 01 Mar 2010 05:00:00 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/the-future-of-civic-engagement-in-a-broadbandenabled-world-9555/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Rebuilding Haiti]]></title>                         
                         	<link>http://video.mit.edu/watch/rebuilding-haiti-9564/</link>
                         	<description><![CDATA[
        02/23/2010 4:00 PM Bartos theaterCherie Moit Abbanat, Lecture, Department of Urban Studies and Planning and the Department of Architecture, MIT;  Michel DeGraff, Associate Professor of Linguistics, MIT;  Erica James, Associate Professor of Anthropology at MIT;  Dale Joachim, Visiting Scientist, MIT Media LabDescription: In the aftermath of the January 2010 earthquake, four panelists with strong personal and professional ties to Haiti share their insights about the different paths to rebuilding and reconstructing the country. 
Erica James begins with a view of Haiti's history of &quot;ins_curit_&quot;, a term used to describe &quot;cycles of political violence, crime, and economic deterioration that have accompanied periods of political and economic upheaval, foreign occupation, dictatorship, and continued environment decline.&quot; She believes the transition from emergency to reconstruction must deal with the challenges of repeated cycles of psychosocial trauma. 
Her concern is that international organizations, in attempting to alleviate the suffering of earthquake survivors, will give rise to practices that undermine the effectiveness of their interventions and create even more victims and victimization-unintended, and unwanted, consequences of their help. For James, the issues of population management-the regulation and distribution of resources, identity, and accountability-are important considerations in reconstruction and rehabilitation efforts. 
Cheri Miot Abbanat  taps into her American and Haitian networks to find out what survivors need and want immediately to help rebuild their lives and their country. While governments and NGOs bring in traditional support-technology, medicine, food, housing-Abbanat suggests first &quot;seeing it with Haitian eyes.&quot;  She asks that aid organizations respect what is already in place in Haiti: homegrown knowledge, the language, what already works. Although fragile, existing support systems could be bolstered by international aid organizations instead of being replaced by them. 
Dale Joachim  recognizes that &quot;technology doesn't solve everything, but it solves a lot of things.&quot; His vision for rebuilding Haiti focuses on energy, the environment, and communications. By addressing Haiti's serious energy imbalance and by &quot;bootstrapping&quot; the public health, education, and rural enterprise systems with a robust communication infrastructure, the path to reversing the breakdown of the environment-in particular, Haiti's massive deforestation-will lead to far greater long&quot;term recovery for the country overall. 
Using a series of overheads comparing several different countries of similar sizes and densities, he shows how the imbalance in Haiti's energy input/output has a pervasive impact on the Haitian infrastructure. Resolving the energy problem will help resolve issues of education, deforestation, and public health concurrently. 
Michel DeGraff  uses language and linguistics &quot;as a lens on [Haiti's] history.&quot; Without recognizing and resolving the complicated socio political stratifications created by language and economics, Haiti will be &quot;rebuilt for the 5% who have always been well off,&quot; leaving the other 90%-those who speak Creole-no better off than they were before. 
DeGraff asserts that Haiti still suffers under brutal class and race inequities brought about, in part, by the power held by those who speak French over those who speak Creole. He believes that by changing the school system, which has been used to maintain these inequities, and by using Creole as the language of all Haitians, the system of language apartheid would be minimized and allow more Haitians access to economic power.  
A Q&amp;A  session follows. 
Host(s): School of Humanities, Arts &amp; Social Sciences, Center for International Studies
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120127222227-9-1_ta5103sm.jpg" height="100" width="165" />                         
                        	<pubDate>Tue, 23 Feb 2010 05:00:00 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/rebuilding-haiti-9564/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Leading through Adversity]]></title>                         
                         	<link>http://video.mit.edu/watch/leading-through-adversity-9537/</link>
                         	<description><![CDATA[
        02/18/2010 12:00 PM Wong AuditoriumPaul Sagan, President &amp; CEO, Akamai TechnologiesDescription: Few companies have endured such hardship, or risen to such heights in a brief span of time as Akamai Technologies.  Paul Sagantells how he became the CEO of this young firm, and helped it survive and then flourish despite &quot;unimaginable adversity.&quot;

Brought up in a Chicago newspaper family, Sagan trained for a life in journalism.  He cut his teeth as a broadcast news producer and executive in the 1980s, and in the 1990s. He helped launch New York 1, a cable news network pioneering digital video technology, and later, an interactive TV project in Orlando that featured video on demand and customized newscasts.  Over the years, says Sagan, he picked up critical lessons on running a business:  Don't count on the permanence of any customer, job, or venture.   He also &quot;glimpsed the digital future,&quot; realizing that if &quot;you married the interactivity and openness of the web with the bandwidth available from cableyou could change the way the internet worked.&quot; 

In 1997, Sagan met a group of MIT computer scientists, including Tom Leighton and Danny Lewin, who had the &quot;crazy, big idea&quot; of applying mathematics to improve internet performance.  Businesses frustrated with breakdowns of fragile central servers could rely instead on a network of servers coordinated by sophisticated software. It was &quot;air traffic control&quot; for internet packets and routing. Venture capital money poured in, and Akamai Technologies was born in 1998, with Sagan as chief operating officer.  But all was not well: While &quot;everyone wanted a piece&quot; of Akamai, the company was hemorrhaging funds.  Then in early 2001, the internet economy burst, and Akamai's customers vanished.

&quot;We were feeling sorry for ourselves,&quot; says Sagan, who recalls laying off 2/3rds of the employees. &quot;Then the unthinkable happened:&quot; Danny Lewin died in the crash of Flight 11 on 9/11.  &quot;Few believed a business, especially ours, could survive a blow like that.&quot;  Sagan was determined to shepherd the company through the twin disasters of economic collapse, and the loss of the &quot;driving force&quot; of Akamai's culture.

He slowly rebuilt the customer base, focusing on selling services to larger corporations that promised greater stability.  Some clients &quot;turned out to be real businesses,&quot; such as Yahoo and Amazon.   2003 saw Akamai's first positive cash flow, and the first profits came a year later.  As he closes the books on 2009, Sagan proudly cites revenues approaching $900 million.  He's unshaken in his conviction that the &quot;internet is the biggest business idea of our generation.&quot; Akamai, says Sagan, &quot;will hopefully face a little bit less adversity&quot; in its second decade.

About the Speaker(s): Paul Sagan joined Akamai in October 1998.  He was elected to the Akamai Board of Directors in January 2005, and became CEO in April 2005.  Previously Sagan served as a senior advisor to the World Economics Forum, consulting on information technology in the corporate world.
In 1995, Sagan was named President and Editor of New Media at Time Inc.  He was a managing editor of Time Warner's News on Demand project, and a founder of Road Runner, the first broadband cable modem service. In 1991, Sagan developed NY 1 News, a cable network known for its use of digital video technology.
Sagan is a graduate of Northwestern's Medill School of Journalism, and he began his career in broadcast news at WCBS&quot;TV in 1981. He is a three&quot;time Emmy Award winner, a fellow of the American Academy of Arts and Sciences, and a Global Leader for Tomorrow with the World Economic Forum. He is also a director of Massachusetts&quot;based EMC Corporation.
Host(s): Sloan School of Management, MIT Sloan School of Management
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120127222224-9-1_q1qde8b4.jpg" height="100" width="165" />                         
                        	<pubDate>Thu, 18 Feb 2010 05:00:00 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/leading-through-adversity-9537/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Autonomous Vehicles and Urban Mobility]]></title>                         
                         	<link>http://video.mit.edu/watch/autonomous-vehicles-and-urban-mobility-9536/</link>
                         	<description><![CDATA[
        12/08/2009 32&quot;124Emilio Frazzoli, Associate Professor of Aeronautics and AstronauticsDescription: If you had half a million dollars, would you opt for a passenger car that could drive itself (called an autonomous vehicle) or would you choose a new Ferrari?  Emilio Frazzoli provides a number of reasons why autonomous vehicles might be the preferred choice, if not the typical one. Autonomous vehicles, that use electronics in place of human drivers, will offer many improvements for urban mobility. Frazzoli says they will advance the safety and comfort of automotives&quot; and open the doors of mobility for people who cannot or should not drive; as he puts it, &quot;if you had too much to drink, maybe you should let the computer take you home.&quot;    Future autonomous vehicles can also increase the efficiency and throughput of our existing road system and help reduce congestion by coordinating with others cars. The autonomous vehicle will also be a &quot;green vehicle&quot; that can make more fuel&quot;efficient decisions than human drivers.  Future autonomous vehicles might save up to 20 to 50% of emissions and fuel consumption by optimizing speed and stopping. 

In some ways, the autonomous vehicle is already with us.  There are robotic components in the cars we drive today, like ABS (advanced breaking systems) which takes over control from human drivers to stop cars and avoid collisions.  Frazzoli says that when ABS first reached the market it was a novelty and good drivers felt they could stop faster than the system.  Today, it is widely accepted that it performs better than almost everyone except a Formula 401 racer.  More recently, autonomous components enable cars to park themselves, and in the arena of mass transportation, there are autonomous bus demonstrations, and driver&quot;less shuttles. Frazzoli sees the demand for autonomous vehicles as only growing. The autonomous vehicle can address the problem that both drivers and passengers are becoming increasingly distracted on the road with cell phones and electronics.  And, with a growing network of V&quot; 2&quot; V (vehicle to vehicle) communications, autonomous vehicles can coordinate with other cars, beyond the capabilities of individual drivers. Simply put, human drivers can only account for vehicles they can see, while an autonomous vehicle has the advantage of synchronizing with the entire network upstream and downstream.  

Some initial work on autonomous vehicles began in the 1980's. More recently it has captured the imagination of the US Defense Department whose DARPA program has set million dollar prize challenges. Frazzoli gives some firsthand lessons from participating in the highly coveted DARPA vehicle challenge of 2007. Initially there were 89 teams but only 7 teams, including MIT, made the final cut. The road conditions were very realistic and each vehicle team had to navigate as an urban vehicle in regular traffic. In other words, the autonomous vehicle needed to abide by the rules of the road, obey speed limits, merge into traffic, pass safely and avoid obstructions. Frazzoli jokes,&quot; the vehicle had to have enough skills to qualify for a California drivers license&quot;. The MIT team equipped a Land Rover LR3 with state&quot; of _the&quot; art&quot; technology that included more than 40 CPUs, radar, and a myriad of laser like sensors, rotating scanners, and video cameras.  Two main modules were a perception sub system, which figured out where the road was, and a planning control system, which then used a decision tree algorithm to anticipate and adhere to rules&quot; of&quot; the&quot; road.  Only six vehicle teams (including MIT) actually finished the race.  According to Frazzoli, &quot;the race was so successful that the only way you could detect that an autonomous vehicle was driving, was that each robotic driven car had a human driver close behind it with a remote control (in hand).&quot;
About the Speaker(s): Emilio Frazzoli's main research interests are in the general area of planning and control for mobile cyber&quot;physical systems, with a particular emphasis on autonomous vehicles, mobile robotics, and transportation networks.  
He received a Laurea degree in Aerospace Engineering from the University of Rome, &quot;Sapienza&quot;, Italy, in 1994, and a Ph. D. in Navigation and Control Systems from MIT Aero/Astro in 2001. Between 1994 and 1997 he worked as an officer in the Italian Navy, and as a spacecraft dynamics specialist for the European Space Agency Operations Centre (ESOC) in Darmstadt, Germany, and Telespazio, in Rome, Italy. From 2001 to 2004 he was an Assistant Professor of Aerospace Engineering at the University of Illinois at Urbana&quot;Champaign. From 2004 to 2006 he was an Assistant Professor of Mechanical and Aerospace Engineering at the University of California, Los Angeles. He was the recipient of a NSF CAREER award in 2002. He is an Associate Fellow of the American Institute of Aeronautics and Astronautics and a Senior Member of the Institute for Electrical and Electronics Engineers.  He is currently serving as an Associate Editor for the AIAA Journal of Guidance, Control, and Dynamics. 

Associate Professor of Aeronautics and Astronautics
 Laboratory for Information and Decision Systems at MIT.
 
http://ares.lids.mit.edu/
Host(s): School of Engineering, Transportation@MIT
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120127222224-9-1_y2iuz48m.jpg" height="100" width="165" />                         
                        	<pubDate>Tue, 08 Dec 2009 05:00:00 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/autonomous-vehicles-and-urban-mobility-9536/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Traffic Paradoxes and Route Guidance: Effective Ways of Reducing Congestion Effects?]]></title>                         
                         	<link>http://video.mit.edu/watch/traffic-paradoxes-and-route-guidance-effective-ways-of-reducing-congestion-effects-9716/</link>
                         	<description><![CDATA[
        12/01/2009 4:00 PM 32&quot;124Andreas Schulz, Patrick McGovern Professor of Mathematics of Operations Research, Head of Operations Research and Statistics Group at the Sloan School of ManagementDescription: It is well know that we cannot engineer our way out of traffic congestion by building new roads. In fact, expanding the road network may paradoxically attract new traffic, and increase gridlock. Andreas Schulz provides a mathematical explanation for this conundrum.  Using Nash equilibria and related game&quot;theoretic concepts he explores two issues, namely: &quot;how much fuel and time can we save if we route traffic optimally, and secondly, can we save fuel and time by actually closing streets or rearranging vehicle flow on our existing road network?&quot; The answers to these questions have significant value.  It is calculated by the Texas Transportation Institute (TTI) the cost of congestion, in fuel and time losses, is $87 billion annually (in 2007 dollars). Schulz uses the TTI estimate as a launching point, to ask how much we could save if we routed more optimally. 

The optimization is based on a complex set of algorithms with Wardrop's Principle as a theoretical background, and total travel time as the variable. Wardrops principle says that the journey times on all the routes actually used are equal and less than those that would be experienced by a single vehicle on an unused route. From this user optimum/equilibrium, Schulz branches to a key concept called the &quot;price of anarchy&quot;.  Applied to traffic, it is a ratio of the journey time of the individual transport user (represented in the numerator) to the value of a system optimization (in the denominator). The so&quot;called &quot;price of anarchy' relationship, numerically expresses what is lost in terms of travel efficiency when each driver acts on their selfish interests (autonomously) instead of using the optimized network. 

Schulz uses scenarios about traffic delay and travel times and the mathematical proof shows that the price of anarchy can be measured and valued. A simple graphic establishes the relationship between the travel time function for individual actors vis&quot;_&quot;vis those of the collective. An adjustment is made for free&quot;flow versus peak traffic to reflect a steep, non&quot;linear incline between the number of peak hour vehicles and road congestion. Schulz finds that his two initial questions are theoretically linked-- knowing the first optimization helps reach the second one, namely the outcome from closing roads.  He notes that the equations can enumerate savings from closing roads that handle different levels of traffic volumes. But he adds, these equations cannot tell the researcher &quot;which roads to close &quot;. 

While solving for full optimization, Schulz also proposes there can be a different path, namely to provide a constraint system optimization. Here, individual drivers are assigned to paths that are in his words &quot; not too long&quot;. Instead, there is a 'fairness' applied to the path allocation, so that most drivers are generated a travel route within normal driving ranges or boundaries. Using this constraint systems approach, the optimizations reveal that 75% of the road users would experience less travel time in lieu of their individual route choice. 

The take&quot;away, says Schulz, is that we can actually route traffic much better than we currently do and adding additional roadways to a system will not necessarily make it better or alleviate traffic. The simulations made for Boston's Big Dig bear this out, and he proposes that there are many other practical applications, particularly using the constraint systems. Current navigation systems, programmed at a system wide level, show great promise for shortening our travel time, if not occasionally lengthening our travel path.    
About the Speaker(s): Andreas S. Schulz is the Patrick J. McGovern (1959) Professor of Management and Professor of Mathematics of Operations Research at the Massachusetts Institute of Technology (MIT). He is also a faculty member of MIT's Operations Research Center, and he has held visiting research professorships at Maastricht University and ETH Zurich. He received a Ph.D. in Mathematics from the Technische Universit_t Berlin in 1996. His research interests include algorithmic game theory, approximation algorithms, combinatorial optimization, computational complexity, integer programming, network flows, polyhedral combinatorics, and scheduling. In 2000, the German Academy of Sciences Leopoldina and the Berlin&quot;Brandenburg Academy of Sciences and Humanities named him one of 20 founding members of &quot;Die Junge Akademie.&quot; Other honors include the Best Paper Award of the Transportation Science &amp; Logistics Society of INFORMS, the Glover&quot;Klingman Prize, the Carl&quot;Ramsauer&quot;Prize, and awards for excellence in teaching. He has been on the editorial boards of several journals, including ACM Transactions on Algorithms, Discrete Optimization, INFORMS Journal on Computing, and Operations Research. 

http://web.mit.edu/SCHULZ/Host(s): School of Engineering, Transportation@MIT
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120127222240-9-1_vt2hgupt.jpg" height="100" width="165" />                         
                        	<pubDate>Tue, 01 Dec 2009 05:00:00 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/traffic-paradoxes-and-route-guidance-effective-ways-of-reducing-congestion-effects-9716/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Session III: Reality Mining: The End of Personal Privacy?]]></title>                         
                         	<link>http://video.mit.edu/watch/session-iii-reality-mining-the-end-of-personal-privacy-4752/</link>
                         	<description><![CDATA[
        &lt;strong&gt;Anmol Madan, Ben Waber, Margaret Ding, Paul Kominers, Alex (Sandy) Pentland&lt;/strong&gt; (MIT).  10/12/2009
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135354-9-1_0jal7q7w.jpg" height="100" width="165" />                         
                        	<pubDate>Mon, 23 Nov 2009 15:43:17 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/session-iii-reality-mining-the-end-of-personal-privacy-4752/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Session III: Panel]]></title>                         
                         	<link>http://video.mit.edu/watch/session-iii-panel-4748/</link>
                         	<description><![CDATA[
        Discussion with Session III presenters.&lt;br&gt; 
&lt;em&gt;Moderator&lt;/em&gt;: &lt;strong&gt;Leonidas Kontothanassis&lt;/strong&gt;, Senior Staff Engineer, Performance Analysis, Google Boston Labs. 10/12/2009
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135354-9-1_dr6bf8d3.jpg" height="100" width="165" />                         
                        	<pubDate>Mon, 23 Nov 2009 15:36:01 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/session-iii-panel-4748/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Network-Driven Transportation]]></title>                         
                         	<link>http://video.mit.edu/watch/network-driven-transportation-9535/</link>
                         	<description><![CDATA[
        11/03/2009 4:00 PM 32&quot;124Li&quot;Shiuan Peh, Associate Professor of Electrical Engineering and Computer ScienceDescription: Today, cell phones are a menace to safe driving, as they distract operators who should otherwise focus on the road. Tomorrow, cell phones could actually improve our driving, and help drivers avoid traffic congestion, use the road system more effectively, and manage the parking supply.  Li&quot;Shiuan Peh says that the key to these services are future mobile devices that will have the computer power equivalent to today's large servers in data centers. Combined with rapid advances in wireless networking, these mobile devices will be harnessed to provide new apps, like next generation transportation programs. 
We currently use the Internet and Wi&quot;Fi or 3G and then run our programs in the cloud on heavyweight servers. Peh says that an opposite case is likely to emerge, with a move towards collaborative computing, using mobile devices and localized cell phones to replace the heavyweight servers. She envisions a time when advanced cell phones will be &quot;stitched together&quot; to run a single piece or information or a program.  Peh says this grassroots type of computing will appeal to the general public, &quot;the sociology&quot; of users, who like to be involved in transportation activities.  Behind this collaborative computing, engineers are fine&quot;tuning a sophisticated mesh&quot;network of communications. 

One of the key protocols for the mesh network is for dedicated short&quot;range communications (DSRC). It is vital for mobile applications, like accident prevention, because it is micro&quot;seconds faster than current standards. DSRC will have very high local coverage, provide faster and more complete transmissions than existing cell towers, and, in particular, be able to overcome the coverage issues of tunnels and dead&quot;spots. Moore's Law scaling would predict that the computing power needed to advance DSRC applications would be more powerful and more efficient that what we know today. 

Location resident services are quite demanding from a communications point of view. Engineers must design around the fact that the phones must be able to hand&quot;off information and exchange it with each other, since the handsets/cars will move in and out of a cordon. Peh notes that existing intelligent vehicle programs in the United States, Europe, and Singapore are using elements of mesh communications today, and that collaborative computing will become the better solution.  Mesh computing can also have very local and practical applications. Stitching cell phones, cameras, and databases together could provide a real&quot;time tool for Amber Alerts, and help solve problems that require geographic sensing, such as locating missing children.  Similar sets of technologies could be stitched together to reduce congestion and fuel use as they guide drivers to open parking spots. 
Host(s): School of Engineering, Transportation@MIT
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120127222224-9-1_bkbvgp1t.jpg" height="100" width="165" />                         
                        	<pubDate>Tue, 03 Nov 2009 05:00:00 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/network-driven-transportation-9535/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Carbon and Energy Efficient Supply Chains]]></title>                         
                         	<link>http://video.mit.edu/watch/carbon-and-energy-efficient-supply-chains-9534/</link>
                         	<description><![CDATA[
        10/27/2009 4:00 PM 32&quot;124Edgar Blanco, Research Director at the MIT Center for Transportation &amp; LogisticsDescription: Consumers will soon be able to quantify the carbon footprint of products they consume, and that could begin to change consumer behavior. The common banana you buy, say organic or not, is probably labeled by the country or origin. Increasingly, you might see a second sticker adorning your beloved yellow fruit _ it will be a  tally of the banana's total carbon emissions  as it moved from farm to table. That single number is not a simple one. If the bananas you bought this week were transported from Indonesia by boat__they have a different carbon footprint than the bunch you consumed last month grown, say in Mexico, and moved by rail.  Behind this labeling system are a complex supply chain, logistics, and transportation considerations.  And behind the measurement of this network is the research of Edgar Blanco and his colleagues at MIT. He begins with a consumer perspective. 

Beginning in 2006, in reaction to climate change, consumers, many large companies and the media wanted to assess the full environmental impact of  finished products, be they bananas, potato chips, or cars.  Blanco compares the measurement of the carbon trail for consumer goods to, &quot;developing a really large map of what happens behind the product&quot;.  He challenges, &quot; If you have a number (of how much emissions a product creates), what should you do about it?... Partially, the exercise gives consumer information, but it is also vital so that you have information about emissions, so you can do something about redesigning the supply chain.&quot; 
The measurement of the carbon trail is vastly complex, and goes well beyond knowing the CO2 emissions produced by the transport sector.  In one exercise, the research team compared the carbon footprint of bottled water manufactured and shipped in the U.S. versus bottled water originating in Fiji but sold in the U.S. The product imported from Fiji turned out to have a lower carbon footprint. Despite the 4,800 miles of ocean transport, the thermal/solar/wind energy used by the Pacific Islands plant was cleaner than the U.S. plant manufacturing relying on energy from fossil fuels. 

In 2001, the Environmental Protection Agency (EPA) began to explore a measuring system to help mitigate pollution from U.S. shippers and carriers. For trucks the task was daunting because there were more than three million vehicles  and 800,000 separate carriers involved.  However, it was also important because trucks move close to 70% of all U.S. freight and therefore remain a growing contributor of greenhouse gases. 

Blanco's research on supply chains and CO2 emissions helped  the EPA act a broker between shippers and carriers. In 2004 the EPA launched a program called &quot;Smart Way&quot; with 100 firms. Today it has grown to more than 1,200 partners. The EPA hopes that as more shippers and carriers join &quot;Smart Way&quot; there will be positive network effects. And, importantly, system models show that a ton of CO2 reduced by the Smart Way program is a less expensive option than other carbon trading schemes. Smart Way is also among consumer programs that have helped develop a carbon labeling system. 

Blanco says the carbon and energy efficient supply chain analysis develops tools so that shippers have the ability to better select carriers.  In a global world, in which many partners operate using many alternative routes and multiple location points, a single number is a singular achievement.  These research methods are now being diffused internationally. Depending on the societal importance consumers place on C02 and the amount they will pay to reduce it, the models have the potential to change how and what banana reaches your breakfast table, as well as everything else. 
About the Speaker(s): Research Director, MIT Center for Transportation &amp; Logistics
Executive Director, MIT SCALE Latin America

Edgar Blanco is a Research Director at the MIT Center for Transportation &amp; Logistics and is the Executive Director of the MIT SCALE Network in Latin America. His current research focus is the design of environmentally efficient supply chains. He also leads research initiatives on supply chain innovations in emerging markets, disruptive mobile technologies in value chains and optimization of humanitarian operations.

Dr. Blanco has more than thirteen years of experience in designing and improving logistics and supply chain systems, including the application of operations research techniques, statistical methods, GIS technologies and software solutions to deliver significant savings in business operations.

Prior to joining MIT, he was leading the Inventory Optimization practice at Retek (now Oracle Retail). He received his Ph.D. from the School of Industrial and Systems Engineering at the Georgia Institute of Technology. His educational background includes a B.S. and M.S. in Industrial Engineering from Universidad de los Andes (Bogot^, Colombia) and a M.S. in Operations Research from the Georgia Institute of Technology.Host(s): School of Engineering, Transportation@MIT
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120127222224-9-1_0jqtshyi.jpg" height="100" width="165" />                         
                        	<pubDate>Tue, 27 Oct 2009 04:00:00 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/carbon-and-energy-efficient-supply-chains-9534/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[The State of Drupal]]></title>                         
                         	<link>http://video.mit.edu/watch/the-state-of-drupal-9524/</link>
                         	<description><![CDATA[Dries Buytaert relates a synopsis of his life with Drupal from its inception while a &quot;typical geek&quot; undergraduate in Antwerp in 1999 to the upcoming release of Drupal 7.]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120127222223-9-1_ogyhr1mn.jpg" height="100" width="165" />                         
                        	<pubDate>Mon, 26 Oct 2009 04:00:00 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/the-state-of-drupal-9524/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Leadership and Entrepreneurship]]></title>                         
                         	<link>http://video.mit.edu/watch/leadership-and-entrepreneurship-9505/</link>
                         	<description><![CDATA[
        10/20/2009 4:00 PM e51&quot;335David Fialkow, Managing Director, General Catalyst Partners;  Ben Fischman, President and Chief Executive Officer,  Retail Convergence, Inc.;  Alex Laats, 89, President,  BBN Technologies' Delta DivisionDescription: While their ventures couldn't be more dissimilar -- engineering high tech defense gear for soldiers, and running an exclusive online boutique -- this panel's entrepreneurs share some common experiences and lessons. 

Moderator David Fialkowwould &quot;love to tell you I'm wicked brilliant, analytical, clairvoyant, but I'm not.&quot;  As he sees it, a large part of business success depends on &quot;the people you meet, and understanding how relationships lead to other things.&quot;  One member of Fialkow's extensive yet intimate business network is Ben Fischman, who affirms this emphasis on relationships as he recounts his own journey through several enterprises. 

As a Boston University junior, Fischman hungered to channel his energy into business, and with some friends, seized on the idea of a store selling truly comfortable baseball caps.  The scheme earned venture capital funding, and rolled out over several years, five LIDS  stores to hundreds of kiosks countrywide.  During these initial years, Fischman gained the &quot;most important wisdom: to surround myself with people who know a lot of stuff I don't know.&quot;  Another lesson arrived with the hire of a CEO &quot;who within six months, single&quot;handedly destroyed the company's culture&quot; and led it to Chapter 11. Fischman now takes a more leisurely pace vetting candidates before hiring them.  

New opportunities arose, leading to e&quot;commerce ventures and his current company, Rue La La, a &quot;viral&quot; online business that &quot;creates incredible addiction&quot; in its customers.&quot;  Fischman modestly describes himself as &quot;a one&quot;trick pony,&quot; capable of pulling together a team of great people &quot;with thick skin, creativity and guts,&quot; who can adjust when the business plan doesn't unfold as written.

Another Fialkow colleague, Alex Laats, found his way into business in a roundabout way.  An MIT math and physics major with a Harvard law degree, Laats ended up in MIT's Technology Licensing Office, where he seized opportunities &quot;to get close to technology and entrepreneurs.&quot;  By 1996, he was &quot;getting antsy to start his own business.&quot;   He found venture capital for a business phone product that was ultimately acquired by 3Com.  His next enterprise was &quot;not a disaster but not a success,&quot; raising $42 million in a single round of  money&quot;raising, in 1999. But the company &quot;hadn't solved its major problems yet,&quot; and it was a time when the &quot;business world ran into telecom breakdown.&quot; Still, Laats gained from this experience: &quot;It's about not being successful. It's important to know those lessons are often times more valuable than victory lessons.&quot; 

His most recent work involves a new division at famed R&amp;D services company BBN, creating products for the government, among others.  It wasn't the easiest fit at first, admits Laats: &quot;I started with nothing, just me and two guys. They didn't know what to do with me.&quot; But he's already got some major successes under his belt. There's Boomerang, a counter sniper product used by American soldiers in Afghanistan, and another venture that brought in $75 million in revenue last year, profits that prove the viability of his business concept.
About the Speaker(s): David Fialkow is the co&quot;founder and managing director of General Catalyst Partners, a venture capital firm specializing in technology&quot;based companies. Fialkow and General Catalyst co&quot;founded Upromise, a rewards program designed to help parents save for college.

At MIT, Fialkow teaches a Sloan Innovation Period course called Leadership and Entrepreneurship, which explores a range of entrepreneurship issues, from how to attract venture capital to developing the skills needed to lead. . He is also a member of the MIT Leadership Center Advisory Council.

Fialkow previously co&quot;founded and operated numerous businesses focused on building applied technology&quot;based platforms and tools. These include National Leisure Group, Alliance Development Group, Retail Growth ATM Systems and Starboard Cruise Services.

He serves on the boards of several nonprofit organizations, including the Pan&quot;Mass Challenge and the Boys and Girls Club of Boston. He is a graduate of Colgate University and Boston College Law School.Host(s): Sloan School of Management, MIT Leadership Center
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120127222221-9-1_5tflipuo.jpg" height="100" width="165" />                         
                        	<pubDate>Tue, 20 Oct 2009 04:00:00 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/leadership-and-entrepreneurship-9505/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Improving Your Commute]]></title>                         
                         	<link>http://video.mit.edu/watch/improving-your-commute-9532/</link>
                         	<description><![CDATA[Hari Balakrishnan describes three challenges that need to be met in using data to help commuters-pedestrians, bicyclists, drivers-reduce the time (and fuel) spent stuck in traffic.]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120127222224-9-1_m8r3nq1e.jpg" height="100" width="165" />                         
                        	<pubDate>Tue, 06 Oct 2009 04:00:00 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/improving-your-commute-9532/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[The Role of Information Technology in Improving Transit Systems]]></title>                         
                         	<link>http://video.mit.edu/watch/the-role-of-information-technology-in-improving-transit-systems-9531/</link>
                         	<description><![CDATA[
        09/29/2009 4:00 PM 32&quot;124Nigel Wilson, Professor of Civil and Environmental EngineeringDescription: &quot;Punch brothers! Punch with care!
Punch in the presence of the passenjare!...&quot;

This ditty about tram car ticketing made famous by Mark Twain might spring to mind during Nigel Wilson's talk.  Technology unimaginable in Twain's day is spurring a global shift in urban transit, Wilson says, from manual  to automatic systems.  Ticket punching by conductors has given way to fare cards swiped through machines -- not to mention real&quot;time GPS tracking of trains and buses, and network monitoring via computers. As part of MIT's Transit Research Program, Wilson and colleagues have been taking advantage of a trove of data resulting from this digital transformation, working in London, Chicago, Puerto Rico, and Boston on ways to improve urban public transport.

Wilson recounts how cosmopolitan transit systems now have the computer capacity to track their buses or trains, collect fares automatically, count passengers, trace usage over time, and communicate instantaneously between system headquarters and vehicles in motion.  But they haven't typically applied the data or other new technology available to them in a methodical way to improve service and operations and customer experience.  But as pressure mounts to respond meaningfully to climate change, mass transit has taken on increased relevance in many cities, and agencies are seeking ways to attract more riders and achieve greater efficiencies.

Among current projects in Wilson's group: an analysis of preferences among Chicago passengers between bus and rail, which involves plotting the typical commutes of a large group of users.  It turns out that those who are equidistant from bus and train stops overwhelmingly prefer rail.  In London, researchers have come up with a meaningful measure of reliability for tube trains, to determine &quot;what occurs on bad days&quot; and how that might affect customers' perception and use of the service.

Wilson believes fare collection data will permit a better understanding of customer behavior, in terms of trip choices and vehicle preferences, and this will consequently lead to &quot;more robust service and operations planning built on better demand&quot;side understanding.&quot;  Also in the works: cellphone&quot;enabled fare payment, which will generate more information about passengers' habits and needs.  Wilson hopes for the deliberate integration of data for the purpose of tying together the worlds of management, operations and commuters, especially in reaction &quot;to unexpected events on the supply side and unanticipated changes in demand.&quot;
About the Speaker(s): Nigel Wilson's research and teaching focuses on urban public transportation, including topics related to the operation, analysis, planning, and management of transit systems. Currently Wilson directs two major long&quot;term research and education programs between MIT and major transit agencies: the Chicago Transit Authority and Transport for London.
In addition to teaching MIT graduate subjects, Wilson also directs a one&quot;week summer course at MIT on transit operations and service planning, which has served more than 300 mid&quot;career transit planners and managers over the past 20 years. 
He received a B.Sc.(Engineering) in 1965 from Imperial College, London University, an S.M. in 1967, and Ph.D. in 1970, both from MIT.Host(s): School of Engineering, Transportation@MIT
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120127222224-9-1_kn0robok.jpg" height="100" width="165" />                         
                        	<pubDate>Tue, 29 Sep 2009 04:00:00 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/the-role-of-information-technology-in-improving-transit-systems-9531/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[RLE Investigator Profile Video Series: Muriel Medard]]></title>                         
                         	<link>http://video.mit.edu/watch/rle-investigator-profile-video-series-muriel-medard-4155/</link>
                         	<description><![CDATA[
        Professor Muriel Medard of MIT discusses research and education in her group, and the intellectual challenges facing engineers at the frontiers of communications, networks, and coding.
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120125135312-9-1_lqj5xzfv.jpg" height="100" width="165" />                         
                        	<pubDate>Thu, 02 Jul 2009 21:10:44 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/rle-investigator-profile-video-series-muriel-medard-4155/</guid>
                      	</item>
                                          	
                        <item>
                         	<title><![CDATA[Deep Brain Stimulation Therapy for Movement Disorders]]></title>                         
                         	<link>http://video.mit.edu/watch/deep-brain-stimulation-therapy-for-movement-disorders-9488/</link>
                         	<description><![CDATA[
        05/07/2009 10:30 AM 46&quot;3002Andres Lozano, University of TorontoDescription: New tools are enabling neuroscientists to break therapeutic ground against daunting disorders like Parkinson's Disease (PD). Andres Lozano is one &quot;of a small group of heroes,&quot; in Ann Graybiel's estimate, whose work is yielding astonishing advances on a variety of fronts.

Treatments for PD, a progressive, degenerative brain disorder, have until recently dealt primarily with the loss of dopamine&quot;releasing neurons, leading to the classic movement disorders associated with PD:  tremor, rigidity, akinesia.  But Lozano says that by the time these physical problems are diagnosed, &quot;the reality is that the disease started 10&quot;15 years earlier,&quot; and has involved other brain areas.  Lozano determined to focus on three such non&quot;motor symptoms of the disease -- gait and posture, depression (in PD and other patients), and cognitive disorders -- and if possible, &quot;reach these circuits, intervene and help patients.&quot;

PD patients have serious problems controlling balance and posture, and animal studies helped pinpoint an area in the brainstem responsible for these functions.  Lozano got permission to plant electrodes in humans in this area, and mapped out the sensitivities of neurons to voluntary movements such as flexing an ankle or walking. In six PD patients, Lozano sent a mild electric current into these neurons.  He shows videos demonstrating the remarkable improvement in control (a patient pushed no longer falls) with deep brain stimulation (DBS). A serendipitous offshoot of this therapy is that it improves REM sleep, in which PD patients are deficient.

Lozano has been working as well on mapping and targeting areas of the brain involved in depression, which he has found to be hyperactive. He labeled neurons that responded exclusively to sad and disturbing images, and using DBS, he was able to &quot;turn down the hyperactivity,&quot; successfully reversing severe depression in 60% of his 36 subjects.

His final accomplishment emerged by accident: While attempting to treat a patient's morbid obesity through DBS, Lozano was startled to find when stimulating the man's thalamus the patient experienced a vivid sense of d_j_ vu. (He recalled being in a field 30 years earlier with a girlfriend.) The stronger the current, the more details emerged.  When the stimulus ended, the memory ceased. Lozano hopes, via DBS, to help patients with memory disorders.  Another intriguing discovery:  stimulation in the hippocampus, deeply involved in memory, seems to lead to a burst of new neuron development.  These DBS studies suggest, says Lozano, that brain circuits for mood, motor control and cognition can be modulated, and we now &quot;need to determine whether they are safe and beneficial to patients.&quot;
About the Speaker(s): Andres Lozano works on novel surgical approaches to treat Parkinson's disease, depression and Alzheimer's disease. His labs use brain imaging, electrophysiology and surgical techniques. The work in humans is complemented by laboratory work involving cell death in Parkinson's disease, effects of stimulation on hippocampal neurogenesis and animal models of deep brain stimulation.

A graduate of the University of Ottawa, Faculty of Medicine in 1983, Lozano underwent Neurosurgical Training at McGill University. He became a Fellow of the Royal College of Physicians and Surgeons of Canada in 1990. During his residency in Montreal, Lozano earned his Ph.D. in Experimental Medicine in 1989. He joined the Neurosurgical Staff at the Toronto Western Hospital in 1991.
Host(s): School of Science, McGovern Institute for Brain Research at MIT
      ]]></description>                         
                         	<media:thumbnail url="http://video.mit.edu/assets/img/videos/165/20120127222220-9-1_5j0xt19h.jpg" height="100" width="165" />                         
                        	<pubDate>Thu, 07 May 2009 04:00:00 GMT</pubDate>
                        	<guid>http://video.mit.edu/watch/deep-brain-stimulation-therapy-for-movement-disorders-9488/</guid>
                      	</item>
                      				</channel>
			</rss>
	