Electrical engineering and computer science (EECS)

Ian Sample of The Guardian reports on how a team of researchers from MIT and Harvard have developed a “Transformer” robot that can self-assemble. "This will rapidly extend the manufacturing capabilities that we have today where configuring an assembly line is done manually and requires a lot of time," Prof. Daniela Rus explains.

Heather Kelly of CNN reports on how MIT researchers have developed a new technique to recreate audio from silent video. "We showed that we can determine pretty reliably the gender of a speaker from low-quality sound we managed to recover from a tissue box," says Dr. Michael Rubinstein. 

Colleen Shalby reports for the PBS NewHour on the “visual microphone” developed by MIT researchers that can detect and reconstruct audio by analyzing the sound waves traveling through objects. 

Bloomberg Businessweek reporter Drake Bennett writes about how MIT researchers have developed a technique for extracting audio by analyzing the sound vibrations traveling through objects. Bennett reports that the researchers found that sound waves could be detected even when using cell phone camera sensors. 

Alyssa Newcomb of ABC News reports on how MIT researchers have developed a new method that can uncover intelligible audio by videotaping everyday objects and translating the sound vibrations back into intelligible sound. 

NPR’s Melissa Block examines the new MIT algorithm that can translate visual information into sound. Abe Davis explains that by analyzing sound waves traveling through an object, “you can start to filter out some of that noise and you can actually recover the sound that produced that motion.” 

Time reporter Nolan Feeney writes about how researchers from MIT have developed a new technique to extract intelligible audio of speech by “videotaping and analyzing the tiny vibrations of objects.”

“Researchers have developed an algorithm that can use visual signals from videos to reconstruct sound and have used it to recover intelligible speech from a video,” writes Katie Collins for Wired about an algorithm developed by a team of MIT researchers that can derive speech from material vibrations.

Rachel Feltman of The Washington Post examines the new MIT algorithm that can reconstruct sound by examining the visual vibrations of sound waves. “This is a new dimension to how you can image objects,” explains graduate student Abe Davis. 

In a piece for Popular Science, Douglas Main writes on the new technique developed by MIT researchers that can reconstruct speech from visual information. The researchers showed that, “an impressive amount of information about the audio (although not its content) could also be recorded with a regular DSLR that films at 60 frames per second.”

Hal Hodson of New Scientist reports on the new algorithm developed by MIT researchers that can turn visual images into sound. "We were able to recover intelligible speech from maybe 15 feet away, from a bag of chips behind soundproof glass," explains Abe Davis, a graduate student at MIT. 

Michael Morisy writes for BetaBoston about an algorithm developed by MIT researchers that can recreate speech by analyzing material vibrations. “The sound re-creation technique typically required cameras shooting at thousands of frames per second,” writes Morisy.

Jane Porter writes for Fortune about WiTricity, an MIT spinout focused on the development of wireless power-transfer technology. By using vibrational frequencies, electricity can be transferred over distances of up to four feet.

Boston Magazine reporter Steve Annear writes about a new robot, designed by MIT undergraduate Patrick McCabe, that can play the game Connect Four. “It’s kind of a magical thing with computer science and technology, being able to leverage that to actually make something smarter than you are,” said McCabe of the device, which can beat its creator.

Wired reporter Margaret Rhodes writes about a new system developed by MIT researchers that uses drones as lighting assistants for photographs. The system operates by examining, “how much light is hitting the subject, and where the drone needs to move to adjust that light.”