A major challenge to developing better neural prostheses is sensory encoding: transforming information captured from the environment by sensors into neural signals that can be interpreted by the ...

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

A team of researchers has built one of the most detailed open maps of emerging technologies yet assembled, allowing ...

Researchers at University of Toronto Engineering, led by Professor Yu Zou, are leveraging machine learning to improve additive manufacturing, also commonly known as 3D printing. In a new paper ...

Robotic systems that mirror humans both in their appearance and movements, also known as humanoid robots, could be best ...

COMET, a novel machine learning framework, integrates EHR data and omics analyses using transfer learning, significantly enhancing predictive modeling and uncovering biological insights from small ...

A research team led by professor Olivia Merkel, Chair of Drug Delivery at LMU and co-spokesperson of the Cluster for Nucleic ...

For decades, scientists have relied on structure to understand protein function. Tools like AlphaFold have revolutionized how researchers predict and design folded proteins, allowing for new ...

Are you contemplating a PhD and interested in economic or social science applications of machine learning? You might be a good fit for our pre-doc position. The Center for Applied Artificial ...