Research
Labs
Areas
II - Computer Science (Artificial Intelligence)
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We study how to make computers see, hear, understand, plan, and act in the world.
Area II web site -
Machine-learning system spontaneously reproduces aspects of human neurology. -
Green, Ketterle, Nedivi, and Shrobe are among those recognized for their efforts toward advancing science. -
Industry leaders, computer scientists, and venture capitalists gather to discuss how smarter computers are remaking our world. -
“Information extraction” system helps turn plain text into data for statistical analysis. -
Self-driving scooter demonstrated at MIT complements autonomous golf carts and city cars. -
New training technique would reveal the basis for machine-learning systems’ decisions. -
Computer system could help identify subtle speech, language disorders in time for early intervention. -
Depth sensor built from off-the-shelf parts filters out ambient infrared light. -
Collaboration has created a pioneering new graduate university in Russia, says project director. -
Senior YQ Lu finds new ways to combine math and paper art, shares his passion for both. -
System lets Web users share aspects of their browsing history with friends, researchers. -
System could help prevent robots from overwhelming human teammates with information. -
Algorithm lets planning systems generate backup plans efficiently. -
Advance could enable mobile devices to implement “neural networks” modeled on the human brain. -
Professor emeritus was a co-founder of CSAIL and a founding member of the Media Lab, and an EECS faculty member for 43 years. -
App that rates drivers’ behavior yields promising safety results on the road. -
New untraceable text-messaging system comes with statistical guarantees. -
Censio’s data analytics on driving behavior helps users improve safety and lower insurance rates. -
By seeing silhouettes through a wall, CSAIL device could help with motion capture, fall prevention and even your heating bill. -
Stefanie Jegelka wins “Deutscher Mustererkennungspreis” prize. -
System that replaces human intuition with algorithms outperforms 615 of 906 human teams. -
Combining MRI and other data helps machine-learning systems predict effects of neurodegenerative disease. -
Giving machine-learning systems “partial credit” during training improves image classification. -
System learns to play text-based computer game using only linguistic information. -
William T. Freeman has been appointed the Thomas and Gerd Perkins Professor of Electrical Engineering and Computer Science
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