Electrical engineering and computer science (EECS)

CSAIL researchers trained a robot to analyze and make scheduling suggestions in a hospital labor ward, writes Kelsey Atherton for Popular Science. Atherton writes that “by adding in a robot that can analyze scheduling needs, hospitals could make better informed decisions.”

The curved origami sculptures created by Prof. Erik Demaine and his father Martin Demaine are featured in the exhibit  “Above the Fold: New Expressions in Origami,” writes Solvej Schou for the Associated Press. The father-son duo use math algorithms to solve paper-folding problems. "Our work grows directly out of our decades collaborating together in mathematics and sculpture," explains Prof. Demaine.

Mary Beth Griggs writes for Popular Science that CSAIL researchers have created an algorithm that can predict human interaction. Griggs explains that the algorithm could “lead to artificial intelligence that is better able to react to humans or even security cameras that could alert authorities when people are in need of help.”

Dan Misener writes for CBC News that CSAIL researchers have developed an algorithm that can predict interactions between two people. PhD student Carl Vondrick explains that the algorithm is "learning, for example, that when someone's hand is outstretched, that means a handshake is going to come." 

CSAIL researchers have trained a deep-learning program to predict interactions between two people, writes Hope King for CNN. “Ultimately, MIT's research could help develop robots for emergency response, helping the robot assess a person's actions to determine if they are injured or in danger,” King explains. 

In an article for Wired, Tim Moynihan writes that a team of CSAIL researchers has created a machine-learning system that can produce sound effects for silent videos. The researchers hope that the system could be used to “help robots identify the materials and physical properties of an object by analyzing the sounds it makes.”

Writing for the Financial Times, Clive Cookson reports that MIT researchers have developed an artificial intelligence system capable of producing realistic sounds for silent movies. Cookson explains that another application for the system could be “to help robots understand objects’ physical properties and interact better with their surroundings." 

Washington Post reporter Matt McFarland writes that MIT researchers have created an algorithm that can produce realistic sounds. “The findings are an example of the power of deep learning,” explains McFarland. “With deep learning, a computer system learns to recognize patterns in huge piles of data and applies what it learns in useful ways.”

Popular Science reporter Mary Beth Griggs writes that MIT researchers have developed an algorithm that can learn how to predict sound. The algorithm “can watch a silent movie and create sounds that go along with the motions on screen. It's so good, it even fooled people into thinking they were actual, recorded sounds from the environment.”

TIME reporter Jeffrey Kluger writes that MIT researchers have designed an algorithm to produce an image of a black hole. Kluger explains that the algorithm will allow researchers “visualize the event horizon that surrounds the black hole at the center of our own galaxy.”

MIT graduate student Katie Bouman speaks with Ben Johnson of Marketplace about the algorithm she and her colleagues developed to allow people “to see the first image of a black hole.” Johnson notes the algorithm has uses beyond space exploration and could also potentially be used for MRI imaging. 

MIT researchers have developed a new algorithm to compile data gathered by the Event Horizon Telescope and create an image of a black hole, reports James Griffiths for CNN. The algorithm will “fill in the gaps and filter out the interference and noise caused by our own atmosphere,” Griffiths explains. 

Washington Post reporter Brian Fung writes that MIT researchers have developed an algorithm to create images of black holes by compiling data from radio telescopes around the world. Fung writes that the algorithm “could give us the first true images of a celestial phenomenon that, for decades, we've left to artists to imagine and describe with pictures.”

An algorithm developed by MIT researchers could help produce the first image of a black hole, reports Ryan Mandelbaum for Popular Science. Mandelbaum explains that the algorithm gathers data from radio telescopes around the globe and then uses “other images from space as references to craft a sort of mosaic that best matches the data from the telescopes.”

Boston Globe reporters J.D. Capelouto and Olivia Arnold write that MIT researchers have developed an algorithm aimed at producing images of black holes. MIT graduate student Katie Bouman notes that while there are predictions of what a black hole might look like, “it’s great to actually be able to probe it and…construct those images.”