Machine learning algorithms that output human-readable equations and design rules are transforming how electrocatalysts for ...

By reviewing three decades of AI applications in electrocatalysis, researchers reveal how the field has shifted from isolated data analysis toward end-to-end, data-driven discovery. The work ...

Traditional computational electromagnetics (CEM) methods—such as MoM, FEM, or FDTD—offer high fidelity, but struggle to scale ...

Read more about AI-driven learning analytics struggle to deliver measurable gains in higher education on Devdiscourse ...

India is entering a decisive phase in its artificial intelligence journey. Over the last two years,  conversations around AI have largely revolved around model sizes, GPU access, and sovereign ...

Nuclear medicine is a rapidly evolving domain at the intersection of advanced radiopharmaceuticals, hybrid imaging modalities such as PET/CT and PET/MR, and ...

Peter Grindrod CBE, Professor in Oxford University's Mathematical Institute and Co-Investigator of the Erlangen AI Hub, outlines why mathematics is ...

This is where AI-augmented data quality engineering emerges. It shifts data quality from deterministic, Boolean checks to ...

Even in the best-case scenario, it’s incredibly disruptive. And this is where you’ve been quoted saying that A.I. will disrupt 50 percent of entry-level white-collar jobs. On a five-year time horizon, ...

A new software tool, ovrlpy, improves quality control in spatial transcriptomics, a key technology in biomedical research. Developed by the Berlin Institute of Health at Charité (BIH) in international ...