In the Media

Mapping the human genome, accomplished a decade ago, was heralded for laying the foundation for understanding genetic variation and links to a wide range of diseases. But genes can be switched on and off by many chemical modifications, aka "epigenetic marks." Now Manolis Kellis, EECS professor and member of the Computer Science and Artificial Intelligence Lab and the Broad Institute has led an NIH group that has created a similar map of the human epigenome. This work will lead to a global map towards understanding fundamental developmental and disease processes in humans. Read more.

In a paper appearing in a forthcoming issue of the International Journal of Robotics Research, Professors and member of the Learning and Intelligent Systems Group Leslie Kaelbling and Tomas Lozano Perez and EECS graduate student Lawson Wong show that a system using an off-the-shelf algorithm to aggregate different perspectives can recognize four times as many objects as one that uses a single perspective, while reducing the number of misidentifications. Read more.

Vivienne Sze, core member of the Microsystems Technology Laboratories (MTL), principal investigator in the Research Laboratory of Electronics (RLE) and the Emanuel E. Landsman (1958) Career Development Professor in the Electrical Engineering and Computer Science Department (EECS), has received a 2014 Defense Advanced Research Projects Agency (DARPA) Young Faculty Award (YFA). Read more.

Using Bayesian regression, Devavrat Shah, member of the Laboratory for Information and Decision Systems and the Computer Science and Artificial Intelligence Lab (LIDS) and recent graduate student Kang Zhang have identified patterns from five months of price data from all major Bitcoin exhanges — enabling them to predict the price of Bitcoin — thereby allowing them to double their investment over a 50 day period. Read more.

Researchers at MIT -- including EECS graduate student Abe Davis and EECS faculty members Fredo Durand and Bill Freeman, and members of the Computer Graphics Group in MIT's Computer Science and Artificial Intelligence Lab (CSAIL) have collaborated with colleagues at Microsoft and Adobe to develop an algorithm to reconstruct an audio signal produced by practically invisible vibrations of objects filmed in video and normally inaudible to human hearing. Read more.

At the IEEE Conference on Computer Vision and Pattern Recognition this month, EECS faculty member and associate department head William Freeman and colleagues from the Computer Science and Artificial Intelligence Lab (CSAIL) will present a new algorithm that can, with roughly 80 percent accuracy, determine whether a given snippet of video is playing backward or forward. Read more.

MIT's Computer Science and Artificial Intelligence Lab (CSAIL) held a two day conference celebrating 50 years of computer science looking forward to the future with solutions for today's obstacles and tomorrow's solutions. Read more.

Prof. Daniela Rus, Director of MIT's Computer Science and Artificial Intelligence Lab (CSAIL) and head of the Distributed Robotics Lab (DRL) envisions new ways for design and manufacture of robots — including the potential for one robot per child in schools. She and members from the DRL group received multiple prizes at the Ultra-Affordable Robot competition particularly for the group's printable, origami-inspired Segway robot, called SEG, which won first place.

Computer Science and Artificial Intelligence Lab's Leslie Kaelbling, the Panasonic Professor of Electrical Engineering and Computer Science in collaboration with members of her research group the Learning and Intelligent Systems Group have developed a new way to use "multiagent systems" to allow for teams of robots to accomplish tasks requiring flexibility and communication in uncertain environments. Read more.

Computer Science and Artificial Intelligence Laboratory's (CSAIL) Aude Oliva, associate professor of cognitive science at MIT's Brain and Cognitive Sciences working with her CSAIL colleagues including Antonio Torralba, associate professor in MIT's Electrical Engineering and Computer Science Department and also a member of in the MIT Computer Vision Group has developed an algorithm to slightly modify a person's face — making it more memorable without altering that person's overall appearance.

Using artificial intelligence tools including probabilistic graphical models, Ying Liu, EECS graduate student working with Alan Willsky, EECS professor and director of the Laboratory for Information and Decisions Systems (LIDS) has developed a technique that can efficiently infer vital information about the propagation of flight delays at U.S. airports. Liu and Willsky will present their work, which has potential application to a wide range of areas, at the Neural Information Processing Systems Foundation in early December. Read more.