Mohit Shrivastava pioneers physics-informed AI to build intelligent, energy-efficient data centers that redefine sustainable engineering.

system combines deep learning and artificial potential fields to enable real-time, collision-free navigation in complex ...

Extreme weather events such as heavy rain and flooding pose growing challenges for early warning systems worldwide.

Scientists at CERN have observed a rare phenomenon where a single top quark formed alongside W and Z bosons for the first ...

In the study, researchers identified top-performing covalent organic frameworks (COFs) for both adsorption and membrane ...

As a physics major, I didn’t have much experience with electronics,” said Spinola Castro. “However, over the course of the summer I realized how much I really liked building these things and ...

The machine-learning programs that underpin their ability to “see” still have blind spots—but not for much longer ...

Philip Ball dives into the challenges in developing quantum computing, and building up investments and users for the tech ...

Machine learning models are designed to take in data, to find patterns or relationships within those data, and to use what ...

Physics-based machine learning unlocks 3D printing potential, thanks to work from Lehigh University's Parisa Khodabakhshi.

The field of computational materials science has been profoundly transformed by integrating deep learning and other machine learning methodologies. These sophisticated data-driven approaches have ...