Living better with algorithms
Graduate student Sarah Cen explores the interplay between humans and artificial intelligence systems, to help build accountability and trust.
Laboratory for Information and Decisions Systems (LIDS)
On the road to cleaner, greener, and faster driving
Researchers use artificial intelligence to help autonomous vehicles avoid idling at red lights.
System helps severely motor-impaired individuals type more quickly and accurately
For individuals who communicate using a single switch, a new interface learns how they make selections, and then self-adjusts accordingly.
A tool for predicting the future
Researchers design a user-friendly interface that helps nonexperts make forecasts using data collected over time.
Learning to fly
Veteran and PhD student Andrea Henshall has used MIT Open Learning to soar from the Air Force to multiple aeronautics degrees.
New maps show airplane contrails over the U.S. dropped steeply in 2020
The computer-vision technique behind these maps could help avoid contrail production, reducing aviation’s climate impact.
Preparing global online learners for the clean energy transition
MIT Energy Initiative edX course asks students to rethink how we operate power systems.
Systems scientists find clues to why false news snowballs on social media
A new model shows that the more polarized and hyperconnected a social network is, the more likely misinformation will spread.
Machine learning speeds up vehicle routing
Strategy accelerates the best algorithmic solvers for large sets of cities.
Avoiding shortcut solutions in artificial intelligence
A new method forces a machine learning model to focus on more data when learning a task, which leads to more reliable predictions.
Making machine learning more useful to high-stakes decision makers
A visual analytics tool helps child welfare specialists understand machine learning predictions that can assist them in screening cases.
One giant leap for the mini cheetah
A new control system, demonstrated using MIT’s robotic mini cheetah, enables four-legged robots to jump across uneven terrain in real-time.
3 Questions: Kalyan Veeramachaneni on hurdles preventing fully automated machine learning
Researchers hope more user-friendly machine-learning systems will enable nonexperts to analyze big data — but can such systems ever be completely autonomous?
Making self-driving cars safer through keener robot perception
PhD student Heng Yang is developing algorithms to help driverless vehicles quickly and accurately assess their surroundings.
System trains drones to fly around obstacles at high speeds
New algorithm could enable fast, nimble drones for time-critical operations such as search and rescue.