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DTSTART:20070311T020000
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DTSTAMP:20250805T113918
DTSTART;TZID=America/Detroit:20250828T150000
DTEND;TZID=America/Detroit:20250828T170000
SUMMARY:Social / Informal Gathering:Hopwood Tea
DESCRIPTION:Enjoy coffee\, tea\, and refreshments in a beautiful\, book-filled space. Check out a book from the Hopwood library or engage with other readers and writers. All are welcome.
UID:136054-21877764@events.umich.edu
URL:https://events.umich.edu/event/136054
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Food,Literary Arts,Literature,The Helen Zell Writers' Program,Undergraduate Students,Well-being,Writing,Ann Arbor,Books,Creative Writing,English Language And Literature,Free,Graduate Students,Hopwood Program
LOCATION:Angell Hall - 1176 (Hopwood Room)
CONTACT:
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DTSTAMP:20250821T162650
DTSTART;TZID=America/Detroit:20250828T150000
DTEND;TZID=America/Detroit:20250828T160000
SUMMARY:Lecture / Discussion:IOE 899 - Jingwen Hu\, University of Michigan
DESCRIPTION:Dr. Hu is a Professor at IOE and a Research Professor at UMTRI.  His research interests primarily focus on injury biomechanics and traffic injury prevention by a multidisciplinary approach using a combination of experimental\, numerical\, and epidemiological methods. Dr. Hu is an author of 150+ peer-reviewed journal and conference papers with four Best Paper Awards. His research has been funded by the National Highway Traffic Safety Administration\, the National Science Foundation\, the National Institute of Justice\, the Department of Defense\, and the Auto Industry.\n\nAbstract:\nRecent literature has shown that there is a growing concern of safety disparity in motor-vehicle crashes (MVCs)\, but technological tools for addressing this issue are limited. In particular\, females\, the elderly\, and obese occupants are among the vulnerable populations who are often at increased risk of death and serious injury compared with mid-size young men in MVCs. This presentation will introduce the parametric finite element (FE) human and vehicle modeling work conducted in the past decade\, along with recent machine-learning models and design optimizations.  The results demonstrated the effectiveness of a population-based virtual testing framework on improving safety disparity among the diverse population.
UID:137881-21880995@events.umich.edu
URL:https://events.umich.edu/event/137881
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:899 Seminar Series,Graduate,Graduate Students,Industrial And Operations Engineering,Michigan Engineering,Undergraduate,Undergraduate Students
LOCATION:Industrial and Operations Engineering Building - 1680
CONTACT:
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