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

Machine learning redesigns microscopic web sensors to be five times more flexible than nature-inspired versions, enabling detection of masses as small as trillionths of a gram.

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

An agentic AI tool for battery researchers harnesses data from previous battery designs to predict the cycle life of new ...

Investments in automation and additional tools for data analytics keep coming to packaging lines as plants become more connected. Machine learning and digital twin technology are increasing throughput ...

Artificial intelligence, if carefully designed, could significantly reduce emergency vehicle delays in congested cities ...

Enterprises in France increasingly consider AI-driven innovation and cost optimization essential in cloud service engagements ...

When it comes to powering aircraft, jet engines need dense, energy-packed fuels. Right now, nearly all of that fuel comes ...

NTN applies AI and machine learning to accelerate bearing design, cut analysis time and reduce engineering workload.

Advancements strengthen hybrid search adoption and deliver deeper visibility into shopper behavior and search performance.

This paper presents a novel framework for optimizing Carbon Release (CR) through an AI-driven approach to Fossil Fuel Intake (FFI) management. We propose a new training methodology for AI models to ...

As ad platforms turn into black boxes, signal optimization offers a way to predict downstream value early and improve CAC and ROAS.