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DTSTART;TZID=America/Detroit:20201020T113000
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UID:10000405-1603193400-1603198800@micde.umich.edu
SUMMARY:LSA Complex Systems / MICDE / MIDAS Seminar: Marissa Renardy\, Research Fellow\, Microbiology & Immunology\, University of Michigan
DESCRIPTION:Predicting the second wave of COVID-19 in Washtenaw County\, MI\nAbstract: In this work\, we study and predict the spread of COVID-19 in Washtenaw County\, MI through applying a discrete and stochastic network-based modeling framework. In this framework\, we construct contact networks based on synthetic population datasets specific for Washtenaw County that are derived from US Census datasets. We assign individuals to households\, workplaces\, schools\, and group quarters (such as prisons or long term care facilities). In addition\, we assign casual contacts to each individual at random. Using this framework\, we explicitly simulate Michigan-specific government-mandated workplace and school closures as well as social distancing measures. We perform sensitivity analyses to identify key model parameters and mechanisms contributing to the observed disease burden in the three months following the first observed cases of COVID-19 in Michigan. We then consider several scenarios for relaxing restrictions and reopening workplaces to predict what actions would be most prudent. In particular\, we consider the effects of 1) different timings for reopening\, and 2) different levels of workplace vs. casual contact re-engagement. Through simulations and sensitivity analyses\, we explore mechanisms driving the magnitude and timing of a second wave of infections upon re-opening. \nThis work is based on Dr. Renardy’s paper in press in the Journal of Theoretical Biology with coauthors:\nMarisa Eisenberg\, UM Complex Systems & Math (LSA) and Epidemiology (Public Health)\nDenise Kirschner\, UM Department of Microbiology & Immunology (Medical School) \nRegistration is not required for this event\, you may join the seminar via this link. \nThe recording of this webinar will be available for viewing soon! \nThis seminar is hosted by the LSA Center for the Study of Complex Systems\, and co-sponsored by the Michigan Institute for Computational Discovery & Engineering (MICDE) and the Michigan Institute for Data Science (MIDAS).
URL:https://micde.umich.edu/event/lsa-complex-systems-micde-midas-seminar-marissa-renardy-research-fellow-microbiology-immunology-university-of-michigan/
LOCATION:Zoom Event
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2020/09/Marissa-Renardy.png
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DTSTART;TZID=America/Detroit:20201020T150000
DTEND;TZID=America/Detroit:20201020T160000
DTSTAMP:20260607T061321
CREATED:20230905T171253Z
LAST-MODIFIED:20230905T171253Z
UID:10000402-1603206000-1603209600@micde.umich.edu
SUMMARY:MICDE Seminar: Grace Gu\, Assistant Professor\, Mechanical Engineering\, University of California- Berkeley
DESCRIPTION:About Grace Gu: Grace X. Gu is an Assistant Professor of Mechanical Engineering at the University of California\, Berkeley. She received her Ph.D. and MS in Mechanical Engineering from the Massachusetts Institute of Technology and her BS in Mechanical Engineering from the University of Michigan\, Ann Arbor. Her current research focuses on creating new materials with superior properties for mechanical\, biological\, and energy applications using multiphysics modeling\, artificial intelligence\, and high-throughput computing\, as well as developing intelligent additive manufacturing technologies to realize complex material designs previously impossible. Gu is the recipient of several awards\, including the 3M Non-Tenured Faculty Award\, MIT Tech Review Innovators Under 35\, Johnson & Johnson Women in STEM2D Scholars Award\, Royal Society of Chemistry Materials Horizons Outstanding Paper Prize\, and SME Outstanding Young Manufacturing Engineer Award. \n  \n\nMETAMATERIALS DESIGN AND MANUFACTURING: LEARNING FROM BIOLOGY AND ARTIFICIAL INTELLIGENCE\nAfter billions of years of evolution\, it is no surprise that biological materials are treated as an invaluable source of inspiration in the search for new materials. Additionally\, developments in computation spurred the fourth paradigm of materials discovery and design using artificial intelligence. Our research aims to advance design and manufacturing processes to create the next generation of high-performance engineering and biological materials by harnessing techniques integrating artificial intelligence\, multiphysics modeling\, and multiscale experimental characterization. This work combines computational methods and algorithms to investigate design principles and mechanisms embedded in materials with superior properties\, including bioinspired materials. Additionally\, we develop and implement deep learning algorithms to detect and resolve problems in current additive manufacturing technologies\, allowing for automated quality assessment and the creation of functional and reliable structural materials. These advances will find applications in robotic devices\, energy storage technologies\, orthopedic implants\, among many others. In the future\, this algorithmically driven approach will enable materials-by-design of complex architectures\, opening up new avenues of research on advanced materials with specific functions and desired properties. \n\nThe MICDE Fall 2020 and Winter 2021 Seminar Series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nTo view the recording for this event\, please complete this form and a link will be sent to you. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-grace-gu-assistant-professor-mechanical-engineering-university-of-california-berkeley/
LOCATION:Zoom Event
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2020/09/Grace-Gu.png
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