Electrical engineering and computer science (EECS)

New Scientist reporter Abigail Beale writes that MIT researchers have been able to trick an AI system into thinking an image of a turtle is a rifle. Beale writes that the results, “raise concerns about the accuracy of face recognition systems and the safety of driverless cars, for example.”

In an article published by The Wall Street Journal about the future of programmable materials, Kelly and Zach Weinersmith highlight Prof. Daniela Rus’ work developing “origami bots that can shape themselves into tools to perform medical procedures or deliver drugs inside the body.”

Guardian reporter Alex Hern writes that in a new paper MIT researchers demonstrated the concept of adversarial images, describing how they tricked an AI system into thinking an image of a turtle was an image of a gun. The researchers explained that their work “demonstrates that adversarial examples are a significantly larger problem in real world systems than previously thought.”

Using video to processes shadows, MIT researchers have developed an algorithm that can see around corners, writes Alyssa Meyers for The Boston Globe. “When you first think about this, you might think it’s crazy or impossible, but we’ve shown that it’s not if you can understand the physics of how light propagates,” says lead author and MIT graduate Katie Bouman.

During an appearance on WGBH’s Greater Boston, Prof. Regina Barzilay speaks with Jim Braude about her research and the experience of winning a MacArthur grant. Barzilay explains that the techniques she and her colleagues are developing to apply machine learning to medicine, “can be applied to many other areas. In fact, we have started collaborating and expanding.” 

Prof. Regina Barzilay, recipient of a 2017 MacArthur grant, speaks to Radio Boston’s Meghna Chakrabarti about her research. Barzilay explains that data is not currently used in the medical field “to select treatments, to personalize it, or to help the patients reduce their uncertainty about the outcomes. I really strongly felt it has to be changed.” 

Prof. Regina Barzilay has been named a MacArthur grant recipient for her work in computational linguistics and with applying machine learning to the field of oncology, reports Ellen Gamerman for The Wall Street Journal. “I firmly believe there is a lot of really important information and patterns that are hidden in the data of cancer patients,” said Barzilay. 

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.”