A mathematics professor at The University of Manchester has developed a novel machine-learning method to detect sudden changes in fluid behaviour, improving speed and cost of identifying these ...

Recent developments in machine learning techniques have been supported by the continuous increase in availability of high-performance computational resources and data. While large volumes of data are ...

Researchers at The University of Manchester have created a physics‑informed machine‑learning model that can run molecular ...

When engineers at Sumitomo Riko needed to speed up the design cycle for automotive rubber and polymer components, they turned ...

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 ...

Crystals, bacterial colonies, flame fronts: the growth of surfaces was first described in the 1980s by the ...

A machine-learning model trained on fewer than 300 molecules has flagged diatomic pairs with record-high electric dipole moments, several of them in combinations that chemists had not seriously ...

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 ...

“A scientific career is a journey of transfer learning and federated learning.” ...

Letters: Prof Ruben Saakyan and Prof Sheila Rowan respond to Prof Charlotte Deane of UK Research and Innovation ...

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...