McKelvey School of Engineering

With a new grant from the National Science Foundation, Christopher Gill at the McKelvey School of Engineering plans to advance cyberphysical systems’ performance for applications in earthquake safety.

Students from the Department of Energy, Environmental & Chemical Engineering at the McKelvey School of Engineering competed in the WERC Environmental Design Contest as a part of their environmental engineering capstone course, winning second place in the bench-scale competition.

Washington University is leading a new effort to address the grand challenge of developing the next generation of high-performance, sustainably sourced and biodegradable plastics that advance engineering while also protecting the environment.

Researchers at the McKelvey School of Engineering are developing better ways to predict preterm birth by analyzing electrical activity during pregnancy. Arye Nehorai’s lab uses electrical activity and deep learning to make predictions.

Ian Bogost has been named the Barbara and David Thomas Distinguished Professor at Washington University in St. Louis.

Wearable brain-imaging tech aims to reveal how the brain works in natural, realistic situations. Washington University researchers received a National Institutes of Health (NIH) grant to develop and commercialize a brain-imaging cap that uses LED light to gauge brain activity.

Some mammals and birds have a clever way to preserve energy and heat by going into torpor, during which their body temperature and metabolic rate drop. Researchers at Washington University in St. Louis safely and noninvasively induced a torpor-like state in mice and rats by using ultrasound to stimulate the hypothalamus preoptic area in the brain.

Yiannis Kantaros, an assistant professor at the McKelvey School of Engineering, received a $413,694 grant to advance the safety, efficiency and transferability of artificial intelligence-enabled autonomous robots.

Researchers in Amit Pathak’s lab at the McKelvey School of Engineering found that cells learn from past environments to promote future invasions.

A team of researchers from the McKelvey School of Engineering and the School of Medicine are using Fitbit data and deep learning to detect depression and anxiety.