Less instrumentation. More insight. Physics-informed virtual sensors are shifting condition monitoring from isolated pilots ...

By leveraging AI/ML-driven modeling, Keysight enables semiconductor companies to accelerate innovation, reduce development ...

Parisa Khodabakhshi is an assistant professor of mechanical engineering and mechanics in Lehigh University’s P.C. Rossin College of Engineering and Applied Science. Prior to joining the Lehigh faculty ...

This study presents a transfer learning–based method for predicting train-induced environmental vibration. The method applies data fusion to combine physics-based numerical simulations and limited ...

Buildings produce a large share of New York's greenhouse gas emissions, but predicting future energy demand—essential for ...

In the world of particle physics, where scientists unravel the mysteries of the universe, artificial intelligence (AI) and machine learning (ML) are making waves with how they're increasing ...

Understanding and predicting complex physical systems remain significant challenges in scientific research and engineering. Machine learning models, while powerful, often fail to follow the ...

A case study in aerospace manufacturing provides an overview of how physics-informed digital twin systems transform robotics processes—from adaptive process planning and real-time process monitoring ...