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

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

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 ...

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

High-precision GNSS applications, such as real-time displacement monitoring and vehicle navigation, rely heavily on resolving carrier-phase ambiguities. However, traditional methods like the R-ratio ...

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

High-entropy alloys are promising advanced materials for demanding applications, but discovering useful compositions is difficult and expensive due to the vast number of possible element combinations.

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

SANTA CLARA, CA - February 05, 2026 - - Interview Kickstart today announced the launch of its Advanced Machine Learning Program, a specialized interview preparation track designed for engineers and ...