Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of ...
Reservoir computing is a promising machine learning-based approach for the analysis of data that changes over time, such as ...
Understanding and predicting complex physical systems remain significant challenges in scientific research and engineering. Machine learning models, while powerful, often fail to follow the ...
Lithium-ion batteries have become the quiet workhorses of the energy transition, but the way they are designed and tested has ...
The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle ...
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 ...
Design engineers can use AI-driven simulation to overcome bottlenecks and accelerate materials discovery with hybrid workflow approaches.
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 ...