Electrical engineering and computer science (EECS)

CSAIL researchers have found that ride-sharing services could reduce the number of cars on the road by 75 percent, reports Marisa Kendall for The Mercury News. The researchers developed an algorithm that can increase service speeds by 20 percent by rerouting cars to “their most efficient routes, including automatically sending idle cars to areas of high demand.”

A new study conducted by MIT researchers shows that ride-sharing services could reduce the number of cars on the road in New York City by 75 percent, according to the BBC News. The researchers found that “a fleet of 3,000 four-passenger taxis could do the same job as the current fleet of 13,000 yellow cabs in New York City.”

A new study by MIT researchers provides evidence that if more people in New York City were willing to carpool, the city would only need 3,000 taxis, reports Hiawatha Bray for The Boston Globe. With carpooling, “we have fewer vehicles, we have less pollution and we have a better travel situation for everyone,” explains Prof. Daniela Rus. 

CSAIL researchers have found that ride-sharing taxis controlled by a citywide computer system could decrease the number of cars on the road in New York City, reports Clive Cookson for the Financial Times. The researchers found that “3,000 four-passenger cars could satisfy 98 per cent of the city’s demand.”

Washington Post reporter Faiz Siddiqui writes that MIT researchers have found that 3,000 four-person cars could serve 98 percent of New York City’s taxi demand. “Fewer cars on roads means improved quality of life for everyone, it means better traffic, it means lower pollution, it’s a better transportation experience,” explains Prof. Daniela Rus. 

CNN reporter Matt McFarland writes about a new MIT study that finds ridesharing would allow the number of taxi cabs in Manhattan to be reduced by 78 percent, cutting congestion and pollution in the city. The study showed that “only 3,000 four-person sedans are needed to serve 98% of ride demands in Manhattan.”

Graduate students Mohammad Ghassemi and Tuka Al Hanai write for Salon about an app they developed aimed at connecting people from different backgrounds. Ghassemi and Al Hanai note that about a third of the app’s users “report having made a lasting friend, someone they keep in touch with regularly.” 

Research by Prof. Erik Demaine looks to find the best method for wrapping spherical objects, writes Sophie Bushwick for Popular Science. By examining how an Austrian candy maker wraps round candies, Demaine found that foil is the best material as “it makes lots of little tiny crinkles, or folds.”

Kevin Murnane of Forbes spotlights five innovations developed by CSAIL researchers in 2016. Murnane highlights an ingestible origami robot, a 3-D printed robot with solid and liquid components, a robot that can assist with scheduling decisions, an artificial neural network that can explain its decisions, and an algorithm that can predict human interactions. 

MIT researchers have developed a technique to make big data more manageable, writes Kevin Murnane for Forbes. The technique creates "coresets" that can be used by data analysis tools “often applied in computer vision, natural language processing, neuroscience, weather prediction, recommendation systems and more.”

Washington Post reporter Nick Anderson writes that four MIT students - Matthew Cavuto, Zachary Hulcher, Kevin Zhou and Daniel Zuo - have been named recipients of the prestigious Marshall scholarships. The MIT group is “the largest delegation of Marshall Scholars named this year from a single school.”

A new system developed by MIT researchers can predict how a scene will unfold, similar to how humans can visually imagine the future, reports Ed Gent for Scientific American. Graduate student Carl Vondrick explains that the system is “an encouraging development in suggesting that computer scientists can imbue machines with much more advanced situational understanding."

Steven Melendez of NBC News writes that a new system developed by CSAIL researchers can predict the future by examining a photograph. Grad student Carl Vondrick explains that the system’s ability to forecast normal behavior could allow it to be used for applications like self-driving cars.

MIT researchers have created a self-driving scooter that can be used both indoors and outdoors, reports Siyi Chen for Quartz. The scooter will “slow down or stop in order to calibrate a new route” when faced with an obstacle, explains Chen.

Stephanie Mlot reports for FOX News that MIT researchers have developed a new portable system that can monitor energy usage, and could be useful for both residential and military applications. The system could “not only generate major savings in fuel or power,” Mlot writes, “but it may also safeguard soldiers responsible for base resupply.”