In a new study published in Physical Review Letters, researchers used machine learning to discover multiple new classes of ...

Researchers at University of Jyväskylä (Finland) advance understanding of gold nanocluster behavior at elevated temperatures ...

Researchers developed a machine learning model that predicts high-yield antibody-producing cell lines early in manufacturing, ...

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

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

SANTA CLARA, CA - February 12, 2026 - - Interview Kickstart has launched a new Data Science course designed for working ...

Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known Heston option pricing model as a benchmark, researchers show that global ...

Researchers at University of Jyväskylä (Finland) advance understanding of gold nanocluster behavior at elevated temperatures ...

Cardiovascular diseases account for approximately 80% of all deaths caused by known medical conditions, making them the leading cause of mortality worldwide. The present study investigates the use of ...

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

This visualization shows moderately large pressure fluctuations within a 35-trillion-grid-point turbulence simulation, ...

Based on these challenges, a comprehensive reassessment of how AI should be deployed in electrocatalysis has become urgently needed. Addressing this need, a review published (DOI: 10.1016/j.esci.2025.