Researchers are developing algorithms to predict failures when automation meets the real world in areas like air traffic scheduling or autonomous vehicles.

Researchers share the design and implementation of an incentive-based Space Sustainability Rating.

Using diagrams to represent interactions in multipart systems can provide a faster way to design software improvements.

Engineers developed a planning tool that can help independent entities decide when they should invest in joint projects.

With their recently-developed neural network architecture, MIT researchers can wring more information out of electronic structure calculations.

Neural network controllers provide complex robots with stability guarantees, paving the way for the safer deployment of autonomous vehicles and industrial machines.

Known for building connections between the social sciences, data science, and computation, the political science professor will lead IDSS into its next chapter.

A new method to measure homophily in large group interactions offers insights into how groups might interact in the future.

The team’s new algorithm finds failures and fixes in all sorts of autonomous systems, from drone teams to power grids.

Designed to ensure safer skies, “Air-Guardian” blends human intuition with machine precision, creating a more symbiotic relationship between pilot and aircraft.