Electrical engineering and computer science (EECS)

CSAIL researchers have developed a system that detects objects and people hidden around blind corners, writes Anthony Cuthbertson for Newsweek. “We show that walls and other obstructions with edges can be exploited as naturally occurring ‘cameras’ that reveal the hidden scenes beyond them,” says lead author and MIT graduate Katherine Bouman.

MIT researchers have developed a new system that can spot moving objects hidden from view by corners, reports Douglas Heaven for New Scientist. “A lot of our work involves finding hidden signals you wouldn’t think would be there,” explains lead author and MIT graduate Katie Bouman. 

Wired reporter Matt Simon writes that MIT researchers have developed a new system that analyzes the light at the edges of walls to see around corners. Simon notes that the technology could be used to improve self-driving cars, autonomous wheelchairs, health care robots and more.  

Prof. Daniela Rus talks to Gareth Mitchell of BBC’s Click about how she and her colleagues have developed shape-shifting robots that can change their exoskeletons to perform different tasks. “These types of robots could become superheroes for the robot kingdom,” explains Rus. “A robot could amplify all of its capabilities by taking on these different types of clothes.” 

CSAIL researchers have developed a virtual reality system that allows operators to control robots remotely, reports Anthony Cuthbertson for Newsweek. The system, “uses off-the-shelf gaming and VR technology to place users in a virtual cockpit, making it more flexible and user-friendly compared to previous systems.”

CSAIL researchers have developed a new shape-shifting robot that can change outfits in order to perform different tasks, reports Timothy Revell for New Scientist. “In the future, we imagine robots like this could become mini surgeons, squished into a pill that you swallow,” explains Prof. Daniela Rus. 

In an article and accompanying puzzle they developed for The Boston Globe, Aloni Cohen, Sunoo Park, and Adam Sealfon of MIT’s Cryptography and Information Security group write about how bar and QR codes contain hidden messages. Cohen, Park and Sealfon note that the encoding scheme used in these codes, “allows not only error detection, but also error correction.”

In an article for HuffPost highlighting new developments in AI research, Jovan Kurbalija and Sorina Teleanu feature  how MIT researchers, “are one step closer to finding a way to determine why an AI system makes one decision over another.”

CSAIL researchers have developed an artificial intelligence system that can reduce video buffering, writes Kevin Murnane for Forbes. The system, “adapts on the fly to current network and buffers conditions,” enabling smoother streaming than other methods.   

Prof. Anantha Chandrakasan, dean of the School of Engineering, speaks with Meera Vankipuram of The Times of India about his research, his areas of focus as dean and what sets MIT apart. Chandrakasan explains that at MIT, there is an “emphasis on translating research into solutions that have a positive impact on the world.”

During this NECN segment, Boston Business Journal reporter Kelly O’Brien discusses the new wireless sleep detection device developed by CSAIL researchers. The algorithm developed by the research team can translate radio waves emitted by the device “into usable information about where a person is in their sleep cycle,” explains O’Brien. 

TechCrunch reporter Brian Heater spotlights a new device developed by MIT researchers that can wirelessly monitor sleep. “Thanks to new AI technology, the system is now able to translate subtle movement into meaningful information about the subject’s sleep patterns, including sleep stages (light/deep/R.E.M.), movement and breathing rate." 

MIT researchers have developed a new device that can track sleep patterns using radio waves, reports Alyssa Meyers for The Boston Globe. The researchers plan to “use the device to study how Parkinson’s disease affects sleep,” Meyers explains, adding that it could also be helpful with, “studying Alzheimer’s disease, insomnia, sleep apnea, and epilepsy.”

Wired reporter Liz Stinson writes that researchers from MIT and Google have developed a new algorithm that can automatically retouch images on a mobile phone. “The neural network identifies exactly how to make it look better—increase contrast a smidge, tone down brightness, whatever—and apply the changes in under 20 milliseconds,” Stinson explains. 

CSAIL researchers have developed an artificial neural network that generates recipes from pictures of food, reports Laurel Dalrymple for NPR. The researchers input recipes into an AI system, which learned patterns “connections between the ingredients in the recipes and the photos of food,” explains Dalrymple.