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

A new MIT study identifies steps that can lower not only emissions, but also costs, across the combined electric power and natural gas industries that now supply heating fuels.

MIT researchers developed a new approach for assessing predictions with a spatial dimension, like forecasting weather or mapping air pollution.

New research could improve the safety of drone shows, warehouse robots, and self-driving cars.

Using the island as a model, researchers demonstrate the “DyMonDS” framework can improve resiliency to extreme weather and ease the integration of new resources.

A new technique identifies and removes the training examples that contribute most to a machine-learning model’s failures.

Using LLMs to convert machine-learning explanations into readable narratives could help users make better decisions about when to trust a model.

MIT engineers show how detailed mapping of weather conditions and energy demand can guide optimization for siting renewable energy installations.

The technique could make AI systems better at complex tasks that involve variability.

By sidestepping the need for costly interventions, a new method could potentially reveal gene regulatory programs, paving the way for targeted treatments.