Recent advances unveiled physical neural networks as promising machine learning platforms, offering faster and more energy-efficient information processing. Compared with extensively-studied optical ...

Mechanical engineering has traditionally relied on physics, mathematics, and empirical knowledge to design and optimize systems. Machine learning (ML) introduces powerful tools that can complement ...

Computer vision researchers use machine learning to train computers in visually recognizing objects but very few apply machine learning to mechanical parts, such as gearboxes, bearings, brakes, ...

Developing polymer composites that simultaneously achieve high strength, toughness, and impact resistance remains a fundamental challenge due to inherent trade-offs and brittle interfacial failure.

Machine learning is becoming an essential part of a physicist’s toolkit. How should new students learn to use it? When Radha Mastandrea started her undergraduate physics program at MIT in 2015, she ...