mccormick.northwestern.edu

MECH_ENG 395: Machine Learning for Mechanical Sciences

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 ...
Nature

Training all-mechanical neural networks for task learning through in situ backpropagation

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

Representations of molecules and materials for interpolation of quantum-mechanical simulations via machine learning

Quantitative modeling of atomic-scale phenomena is central for scientific insights and technological innovations in many areas of physics, chemistry, and materials science. Solving the equations that ...
ACHR News

Machine Learning for Making Machines: Applying Visual Search to Mechanical Parts

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, ...
Symmetry Magazine

Tomorrow’s physics test: machine learning

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 ...
Science Daily

Machine learning technique sharpens prediction of material's mechanical properties

Scientists have developed new approaches that significantly improve the accuracy of an important material testing technique by harnessing the power of machine learning. The new analytical technique ...