Recent advances in AI, quantum computing, and physics-based modeling are dramatically accelerating and expanding the scope of ...

The landscape of physics education has shifted dramatically by 2026, with specialized AI solvers and updated PhET simulations offering unprecedented support for mastering core mechanics concepts like ...

Researchers use statistical physics and "toy models" to explain how neural networks avoid overfitting and stabilize learning in high-dimensional spaces.

Adrian Macneil has a solid understanding of this space. As an executive at the self-driving startup Cruise, he built the ...

Researchers present a comprehensive review of frontier AI applications in computational structural analysis from 2020 to 2025, focusing on graph neural networks (GNNs), sequence-to-sequence (Seq2Seq) ...

AI excels at correlations but lacks physical intuition, creating gaps in real-world reasoning and reliability.

Design engineering is running headfirst into a materials bottleneck. Industries such as automotive, aerospace, electronics, and semiconductors now depend on increasingly complex materials. Yet ...

During surgery to correct an abnormal heartbeat, doctors rely on a mix of imaging and inference. Still, many critical details remain hidden. At RIT, artificial intelligence (AI) researchers want to ...

Generative AI is becoming ubiquitous in everyday life. Large language models like ChatGPT can help answer questions, write email, and solve problems at seemingly lightning speed, pulling from enormous ...

Since the first FEA solver, Nastran, was developed for NASA in the 1960s, the simulation software industry has contended with a number of hurdles. For one, while the software (FEA, CFD, CEM) is ...