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

By breaking an intractable problem into smaller chunks, a deep-learning technique identifies the optimal areas for thinning out traffic in a warehouse.

An easy-to-use technique could assist everyone from economists to sports analysts.

The team used machine learning to analyze satellite and roadside images of areas where small farms predominate and agricultural data are sparse.

Scientists quantify a previously overlooked driver of human-related mercury emissions.

Exploiting the symmetry within datasets, MIT researchers show, can decrease the amount of data needed for training neural networks.

Developed by MIT engineers, the model could be a tool for designers looking to innovate in sneaker design.

MIT researchers develop a customized onboarding process that helps a human learn when a model’s advice is trustworthy.

A new, data-driven approach could lead to better solutions for tricky optimization problems like global package routing or power grid operation.

MIT researchers who share their data recognized at second annual awards celebration.