Michigan Engineering | University of Michigan Highlights include CNN and Popular Science.
In the news: Michigan Engineering experts July 25-29
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Kamal Sarabandi named Fawwaz T. Ulaby Distinguished University Professor of EECS
Prof. Sarabandi has distinguished himself as an educator, researcher, and inventor with wide-ranging impact
The post Kamal Sarabandi named Fawwaz T. Ulaby Distinguished University Professor of EECS appeared first on Engineering Research News.
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H.V. Jagadish named Edgar F. Codd Distinguished University Professor of EECS
Professor Jagadish is being recognized for his work as one of the nation’s most visible and influential researchers in the interdisciplinary field of data science
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University of Michigan partners on multi-institution planning effort for state’s water future
Work for the Michigan Department of Environment, Great Lakes and Energy will develop a policy roadmap to safe, low cost water services.
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Sara Pozzi appointed University Diversity and Social Transformation Professor
Pozzi was one of six university faculty members to be recognized for outstanding contributions to excellence through their commitment to promoting diversity, equity, and inclusion.
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In the news: Michigan Engineering experts July 18-22
Highlights include The New York Times and National Geographic.
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Sharon Glotzer receives Vannevar Bush Faculty Fellowship
Sharon C. Glotzer, Anthony C. Lembke Department Chair of Chemical Engineering, has received the Vannevar Bush Faculty Fellowship from the U.S. Department of Defense.
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Great Lakes flood prevention: Report recommends mitigation steps
Broken pumps weren’t the main problem in Detroit’s 2021 floods—there was more rainfall than the water systems could handle.
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Studying Earth’s defenses against solar storms
NASA undertakes a comprehensive look at a critical atmospheric buffer between us and the sun, powered in part by University of Michigan researchers and alumni.
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Open source platform enables research on privacy-preserving machine learning
Virtual assortment of user devices provides a realistic training environment for distributed machine learning, protects privacy by learning where data lives.