The data science and machine learning technology space is undergoing rapid changes, fueled primarily by the wave of generative AI and—just in the last year—agentic AI systems and the large language ...

Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, ...

Sriharsha Daram’s work in enterprise software architecture demonstrates how careful system design improves performance and reliability. While contributing to Toyota’s OneApp, a vehicle management ...

Northwestern Engineering students pursuing the machine learning and data science (MLDS) minor learn to develop comprehensive data science pipelines, glean insights from data, and think critically ...

In recent years, JupyterLab has rapidly become the tool of choice for data scientists, machine learning (ML) practitioners, and analysts worldwide. This powerful, web-based integrated development ...

Prediction of crystal structures of organic molecules is a critical task in many industries, especially in pharmaceuticals ...

The field of computational materials science has been profoundly transformed by integrating deep learning and other machine learning methodologies. These sophisticated data-driven approaches have ...

A recent study by researchers from CSIRO and the University of Melbourne has made progress in quantum machine learning, a field aimed at achieving quantum advantage to outperform classical machine ...