Neel Somani has built a career that sits at the intersection of theory and practice. His work spans formal methods, mac ...

The process of testing new solar cell technologies has traditionally been slow and costly, requiring multiple steps. Led by a fifth-year PhD student, a Johns Hopkins team has developed a machine ...

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

Lithium-ion batteries have become the quiet workhorses of the energy transition, but the way they are designed and tested has ...

New forms of fentanyl are created every day. For law enforcement, that poses a challenge: How do you identify a chemical you've never seen before? Researchers at Lawrence Livermore National Laboratory ...

Electron density prediction for a four-million-atom aluminum system using machine learning, deemed to be infeasible using traditional DFT method. × Researchers from Michigan Tech and the University of ...

The question of whether prehospital emergency anaesthesia and intubation improves survival in patients with major trauma has ...

RIT researchers publish a paper in Nature Scientific Reports on a new tree-based machine learning algorithm used to predict chaos.

Phishing websites remain a persistent cybersecurity threat, exploiting users by imitating trusted online services. New ...