Georgia Tech’s Qi Tang is building machine learning (ML) models to accelerate nuclear fusion research, making it more affordable and more accurate. Backed by a grant from the U.S. Department of Energy ...

Modeling-Driven Design of Materials and Electrodes for Beyond Lithium-Ion Batteries with Damla Eroglu, Department of Chem ...

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered considerable interest among researchers. The debate around the use of machine ...

This integration addresses the fundamental barriers that have historically limited formal verification adoption: complexity ...

Office of Water Prediction (OWP) makes critical flood forecasts with the National Water Model. Despite improvements over time ...

Researchers at the University of Bayreuth have developed a method using artificial intelligence that can significantly speed up the calculation of liquid properties. The AI approach predicts the ...

A new study reveals how advanced carbon based nanofluids could significantly improve heat transfer in technologies ranging from microelectronics to ...

Raja Shankar, VP of machine learning at IQVIA, discusses which AI capabilities sponsors are most likely to adopt first to ...

NTN announced that it has integrated machine learning technology into its automated calculation system used for designing 3rd‑generation hub bearings, marking the first use of this approach in the ...

Real-world data (RWD) is transforming clinical research, augmenting existing randomized controlled trial (RCT) data to de-risk studies and improve generalizability. With regulators setting clearer ...

Keysight SOS is a powerful data management platform that facilitates AI-powered chip design workflows and AI accelerator ...

The PALLAS simulation framework is a Geant4-based toolkit for modeling plasma-accelerated particle beams. It integrates traditional Monte Carlo methods with machine learning-based ONNX beam generation ...