Four MIT faculty elected 2015 AAAS Fellows
Berggren, Bertschinger, Fink, and Zue are among those recognized for efforts toward advancing science.
Topic
Computer Science and Artificial Intelligence Laboratory (CSAIL)
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Designing virtual identities for empowerment and social change
D. Fox Harrell receives $1.35 million in grant funding to advance research at the intersection of social science and digital technology.
NASA gives MIT a humanoid robot to develop software for future space missions
Team led by Professor Russ Tedrake of CSAIL to develop algorithms for 6-foot-tall “Valkyrie” robot to travel to Mars and beyond.
Streamlining mobile image processing
Technique for mobile image processing in the cloud cuts bandwidth use by more than 98 percent.
MIT Libraries explore 17th-century postal archive in "Signed, Sealed, and Undelivered"
2,600 recently rediscovered early modern letters to be analyzed in groundbreaking international digital humanities project.
Amplifying — or removing — visual variation
Algorithms could offer new tools for graphics software or reveal structural defects.
How to make better visualizations
Eye-tracking research reveals which types of visuals actually get the message across.
System automatically converts 2-D video to 3-D
Exploiting video game software yields broadcast-quality 3-D video of soccer games in real time.
Real-time epidemiology from urban wastewater
MIT and Kuwait researchers have been awarded $4 million to fund Underworlds, a study of real-time epidemiology using biomarkers in urban sewage.
How wireless “X-ray vision” could power virtual reality, smart homes, and Hollywood
By seeing silhouettes through a wall, CSAIL device could help with motion capture, fall prevention and even your heating bill.
A basis for all cryptography
A tool that would provide a secure foundation for any cryptographic system may be close at hand.
Faster optimization
New general-purpose optimization algorithm promises order-of-magnitude speedups on some problems.
Automating big-data analysis
System that replaces human intuition with algorithms outperforms 615 of 906 human teams.
Predicting change in the Alzheimer’s brain
Combining MRI and other data helps machine-learning systems predict effects of neurodegenerative disease.
More-flexible machine learning
Giving machine-learning systems “partial credit” during training improves image classification.