In an interview with Technology Networks, Dr. Daniel Reker discusses how machine learning is improving data-scarce areas of drug discovery.

Lithium-ion batteries have become the quiet workhorses of the energy transition, but the way they are designed and tested has long been slow, expensive, and heavily empirical. Machine learning is now ...

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

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 ...

The new toolkit integrates with Keysight’s device modeling software to automate parameter extraction and shorten compact-model and PDK development cycles.

Digital twins revolutionize drug discovery by integrating AI and biological data, enhancing prediction, trial design, and decision-making in precision medicine.

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...

What if vaccine development didn’t have to take a decade? This piece looks at how AI is helping scientists ask better ...

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 ...

A new peer-reviewed study published in the journal Algorithms signals a major shift in how humanitarian logistics can be ...