A clear view to better batteries
Engineering researchers at WashU are providing guidance and maps to improve the performance and safety of lithium-ion batteries.
Ralph S. Quatrano, former dean of engineering, 84
Ralph S. Quatrano, an internationally renowned plant scientist, former dean of the Washington University in St. Louis School of Engineering & Applied Science and former chair of the Department of Biology in Arts & Sciences, died Feb. 24, 2026, in St. Louis. He was 84.
Four named senior members of National Academy of Inventors
Four WashU researchers have been named senior members of the National Academy of Inventors: Rajan Chakrabarty, Vijay Ramani, Christina Stallings and Zhude Tu.
Ottley appointed to UN panel on artificial intelligence
Alvitta Ottley, a computer science researcher at WashU, was appointed to a United Nations panel on artificial intelligence.
Clinically informed AI outperforms foundation models in spinal cord disease prediction
Machine learning researchers at Washington University in St. Louis used artificial intelligence to help with early detection of spinal cord disease.
Fiber implant sheds new light on Alzheimer’s disease progression
Researchers at Washington University in St. Louis have a federal grant to further develop a fiber-based, deep-brain interface to study the relationship between neurovascular dysfunction and memory loss in Alzheimer’s disease.
Putting some ‘muscle’ into material design
Researchers at Washington University in St. Louis have developed muscle-inspired fiber materials for use in textiles, foods and biomedical applications.
Light gives boost to image processing, optical systems
Researchers at Washington University in St. Louis have found a way to use light to boost the efficiency of image processing and optical neural networks.
Making hydrogen fuel cells ‘less precious’
WashU engineers are working to bring stability to iron components instead of using more expensive precious metals in fuel-cell technologies.
Reinforcement learning for arbitrarily large systems is possible
Researchers at Washington University in St. Louis are developing mathematically rigorous and computationally efficient techniques to transform extremely complex reinforcement learning problems into a manageable domain.
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