Predictions from the OncoNPC model could enable doctors to choose targeted treatments for difficult-to-treat tumors.

With a new, user-friendly interface, researchers can quickly design many cellular metamaterial structures that have unique mechanical properties.

“PhotoGuard,” developed by MIT CSAIL researchers, prevents unauthorized image manipulation, safeguarding authenticity in the era of advanced generative models.

A new technique helps a nontechnical user understand why a robot failed, and then fine-tune it with minimal effort to perform a task effectively.

PIGINet leverages machine learning to streamline and enhance household robots' task and motion planning, by assessing and filtering feasible solutions in complex environments.

Researchers create a privacy technique that protects sensitive data while maintaining a machine-learning model’s performance.

MIT researchers develop "FrameDiff," a computational tool that uses generative AI to craft new protein structures, with the aim of accelerating drug development and improving gene therapy.

This AI system only needs a small amount of data to predict molecular properties, which could speed up drug discovery and material development.

A new computational method facilitates the dense placement of objects inside a rigid container.

A new dataset can help scientists develop automatic systems that generate richer, more descriptive captions for online charts.