EurekAlert!

Frontier AI in computational civil engineering: a review of graph, sequence, physics-informed deep learning, and beyond (2020–2025)

Researchers present a comprehensive review of frontier AI applications in computational structural analysis from 2020 to 2025 ...
EurekAlert!

Transfer learning-enhanced physics-informed neural network (TLE-PINN): A breakthrough in melt pool prediction for laser melting

The TLE-PINN method integrates EPINN and deep learning models through a transfer learning framework, combining strong physical constraints and efficient computational capabilities to accurately ...

As wildfires intensify, researchers test if AI can improve fire spread prediction

With wildfires growing more destructive both in the United States and around the world, University at Buffalo researchers have conducted one of the most extensive evaluations to date of artificial ...
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 ...