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Curtis Reichenfeld, CTO of Curtiss-Wright Electronic Systems, showcases some of their newest integrated electronics for military and aerospace applications, including a compact flight control computer, the next generation single board computer for the Global Hawk UAV, a conduction-cooled 3U VPX chassis and more.

Hosted by: Bill Wong Videography by: Curtis Ellzey Edited by: Curtis Ellzey

Designed to meet the needs of military research and training programs for UAVs such as Predator and Reaper drones, the Reaper Ground Control Simulator from CH Products features industrial grade components, driverless USB connectivity, and is capable of supporting a wide variety of simulation software.

Hosted by: Bill Wong Videography by: Curtis Ellzey Edited by: Curtis Ellzey

Curtiss-Wright's Skyquest ALPHA series of rugged standalone video displays feature a wealth of surveillance features such as FLIR, long range daylight video cameras, moving maps, computers and radar. Skyquest CTO Anthony McQuiggan showcases their AVDU-5008 20", ideal for integrating into today's airborne military and search & rescue platforms.

Hosted by: Bill Wong Videography by: Curtis Ellzey Edited by: Curtis Ellzey

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 “are scared off by the noise, the randomness of people.” Pentland, on the other hand, has long explored human decision-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 “determine predictive signals of driving.” The sensors permitted the analysis of “clusters of behaviors,” so Pentland could figure out with 95% accuracy “what people would do before they did it.” 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

Four women who have made ground-breaking contributions in different disciplines describe their research, which has not only involved ‘thinking outside the box,’ but in some cases persevering in the face of skepticism.

Two presenters work on the frontier of biological systems and materials science, and find both inspiration and practical subject matter in aquatic life forms. For Angela Belcher, the abalone offers a model for development of organic/inorganic hybrid structures. The shell of this creature, which is 3000 times tougher than its purely geological counterpart, consists of stacks of calcium carbonate in precise geometries, made from just 20 different amino acids, says Belcher. Some years ago, she had the insight that it might be possible to fabricate hybrid materials, kind of like an abalone, “at a living/nonliving interface.” She set about creating an organism that could build structures like battery electrodes, using bacterial hosts injected with viruses that had an affinity for a particular material. “When I said I was trying to develop a genetic link between semiconductor materials and biology, I was told I was insane,” says Belcher. “But it came out OK.” Undaunted, Belcher is now developing

Although these three speakers travel in quite disparate worlds -- natural language processing, mechanics of tiny organisms, and violent cosmic events -- they convey a comparably infectious enthusiasm for their research.

In the early days of artificial intelligence, “people had the naïve idea that if you took a computer, and fed it with enough human knowledge, it could eventually understand human language,” relates Regina Barzilay. In the 1990s, after this “spectacular failure” in methodology, a new approach evolved: training a machine to infer knowledge from piles of data. Some successes are already in evidence (IBM’s chess- and Jeopardy-playing programs). Barzilay wants to move this learning further, toward “grounding interpretation of language in the real world.” She describes algorithms that could take over the often exasperating grunt work of installing new Windows software on computers, by reading common instructions and executing the actions. Her system learns to map words with increasing accuracy by using feedback. She is also investigating how to get a machine to understand and act in a much more complex environment, such as the Civilization computer game. Using simulations, her algorithms make predictions about the best possible

With many years of academic and corporate workplace experience among them, these panelists share expertise and best practices for recruiting and retaining women to science and engineering careers.

Mildred Dresselhaus came to MIT to teach physics to engineering students. Although she received a scholarship funding women in science, she always believed “it was important for men to take you seriously, and not to worry about your sex.” Dresselhaus feels she “works for her students, and they work for her,” and says she learned a lot about teaching and providing for students’ careers from her years as a mother to four children. She believes mentoring serves an important function on campus, for men and women, and that it can prove particularly helpful to women, who may lack self-confidence. Her mentoring, which includes weekly meetings with some young women faculty, emphasizes some basic ideas, such as curiosity, creativity, being skeptical and thinking innovatively. She also wants her protégées to learn how to “handle disappointment,” since work “at the cutting edge doesn’t work most of the time.” She is particularly sympathetic to the challenges of combining work and family life, which still

It’s Day 95 in MIT’s 150 days of sesquicentennial celebration, and all thoughts turn to the evolution of computer science and MIT’s pivotal role in that history. As Victor Zue puts it so succinctly, “Computers sure have changed.” They are even invading biology, and President Hockfield (who is also a Professor of Neuroscience) sees this history as another branch in the tradition, initiated by William Barton Rogers, of education bringing the “useful arts” (or as we now say, technology) to bear on the economic development of the United States.

Tom Leighton asserts that “To say computers are transforming everything is an understatement.” Leighton offers a brief lesson in theoretical computer science, defining an algorithm through the example of searching for the prime factors of a given number N, and identifying the key follow-up questions: Can you prove it works? How long does it take? How good is it? Then the big question: Does theoretical computer science matter? Leighton cites some powerful examples of the field’s impact on our lives, from encryption to Google’s page-rank algorithm to the content delivery system of

Personal reminiscence and professional observations share the stage in the second panel of this symposium on computation.

As a boy, former MIT President Charles (Chuck) Vest daydreamed about going on a rocket ship to the moon, having a tiny TV, and obtaining a Dick Tracy wristwatch. While he never made it to the moon (though he knows those who have), he has fulfilled other wishes, thanks to “amazing developments in computing:” mobile devices he can carry in his pocket that combine watch, TV and many more functions.

Vest was on hand for the dawn of the digital revolution, and recalls learning to program in Fortran in college in 1961, and describes a computer with 8 bits of memory held in a mercury vapor tube. He developed a recurring nightmare after many nights carrying boxes full of punched cards to the University of Michigan computer center, and worrying about “one little bug ruining the whole program.” He held onto the cards until he moved to Cambridge in 1990.

While working as a young faculty member in the field of optical holography, Vest said his team became the “nth group to develop the idea

Moore’s law and energy efficiency emerge as themes in these two lectures on past and future progress in microprocessors and robotics.

Back in the old days, recalls Rodney Brooks, people were not allowed near computers, because the smoke from human cigarettes might damage delicate machinery. Then humans had to steer clear of robots, lest they come out on the losing end of an encounter with a hulking machine limb. But following the explosion of PC and portable computing technology, the last 10 years have brought robots into close proximity with people. Brooks says more than nine thousand robots now serve in the U.S. military, and six million work in human homes -- including his own line at iRobot.

Brooks attributes this proliferation of AI aides to “IT exponentials that beget other exponentials.” Leaps in processing speed enormously aided in the development of essential robotics systems, such as vision, machine learning, wireless networking, and speech understanding. He shows a robot, “The Cart,” from Stanford’s AI lab circa 1979. The device relied on a giant mainframe (shared with the music department), and moved 20 meters in six hours. By 2005, Stanford’s AI