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DTSTART;TZID=America/Detroit:20201020T150000
DTEND;TZID=America/Detroit:20201020T160000
DTSTAMP:20260604T214433
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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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20201020T113000
DTEND;TZID=America/Detroit:20201020T130000
DTSTAMP:20260604T214433
CREATED:20230905T171253Z
LAST-MODIFIED:20230905T171253Z
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
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20201016T090000
DTEND;TZID=America/Detroit:20201016T170000
DTSTAMP:20260604T214433
CREATED:20230905T171253Z
LAST-MODIFIED:20230905T171253Z
UID:10000014-1602838800-1602867600@micde.umich.edu
SUMMARY:Fundamentals of Accelerated Computing with CUDA C/C++
DESCRIPTION:The CUDA computing platform enables the acceleration of CPU-only applications to run on the world’s fastest massively parallel GPUs. Experience C/C++ application acceleration by: \n\nAccelerating CPU-only applications to run their latent parallelism on GPUs\nUtilizing essential CUDA memory management techniques to optimize accelerated applications\nExposing accelerated application potential for concurrency and exploiting it with CUDA streams\nLeveraging command line and visual profiling to guide and check your work\n\nUpon completion\, you’ll be able to accelerate and optimize existing C/C++ CPU-only applications using the most essential CUDA tools and techniques. You’ll understand an iterative style of CUDA development that will allow you to ship accelerated applications fast. \nThe workshop will use online tools\, so there is no need to install any software ahead of time.
URL:https://micde.umich.edu/event/fundamentals-of-accelerated-computing-with-cuda-c-c-2/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200929T140000
DTEND;TZID=America/Detroit:20200929T150000
DTSTAMP:20260604T214433
CREATED:20230905T171252Z
LAST-MODIFIED:20230905T171252Z
UID:10000409-1601388000-1601391600@micde.umich.edu
SUMMARY:MICDE / Mechanical Engineering Seminar: Sophia Haussener\, Associate Professor\, Laboratory of Renewable Energy Science and Engineering\, EPFL\, Lausanne\, Switzerland
DESCRIPTION:View webinar recording. \nBio: Sophia Haussener is an Associate Professor heading the Laboratory of Renewable Energy Science and Engineering at the Ecole Polytechnique Fédérale de Lausanne (EPFL). Her current research is focused on providing design guidelines for thermal\, thermochemical\, and photoelectrochemical energy conversion reactors through multi-physics modelling. Her research interests include: thermal sciences\, fluid dynamics\, charge transfer\, electro-magnetism\, and thermo/electro/photochemistry in complex multi-phase media on multiple scales. She received her MSc (2007) and PhD (2010) in Mechanical Engineering from ETH Zurich. Between 2011 and 2012\, she was a postdoctoral researcher at the Joint Center of Artificial Photosynthesis (JCAP) and the Energy Environmental Technology Division of the Lawrence Berkeley National Laboratory (LBNL). She has published over 70 articles in peer-reviewed journals and conference proceedings\, and 2 books. She has been awarded the ETH medal (2011)\, the Dimitris N. Chorafas Foundation award (2011)\, the ABB Forschungspreis (2012)\, the Prix Zonta (2015)\, the Global Change Award (2017)\, and the Viskanta Award (2019)\, and is a recipient of a Starting Grant of the Swiss National Science Foundation (2014). She is a deputy leader in the Swiss Competence Center for Energy Research (SCCER) on energy storage and acts as a Member of the Scientific Advisory Council of the Helmholtz Zentrum. \nModelling\, experimentation and scaling of photo-electrochemical fuel processing devices\nThe development of a sustainable energy economy based on renewable\, carbon-neutral energy is a necessary and urgent task. Photo-electrochemical approaches for solar fuels and materials are interesting\, provided they can be efficiently\, stably\, scalably\, and sustainably implemented. The functionality of such devices relies on complicated and coupled multi-physics processes\, occurring at multiple temporal and spatial scales. Device modelling can actively and efficiently support the choice of the most promising – in terms of efficiency\, cost\, robustness\, scalability\, and practicability – conceptual design pathways\, material choices\, and operating approaches. \nFirst\, I focus on cost competitive photo-electrochemical (PEC) devices identified through quasi-transient techno-economic modelling [1]. I will describe the conceptual idea of thermal integration in the context of PEC [2]\, provide results of maximum theoretical efficiency calculations to quantify the benefits\, and review the modelling framework that enabled the design of a feasible device [3]. I will illustrate how we have used our models to design and implement a PEC device with a solar-to-fuel efficiency of 17%\, and discuss ongoing approaches to scale up by our lab in order to bridge the gap between research and practical applications. \nSecond\, I will discuss detailed multi-dimensional mesoscale models that allow to assess the transport in complex (photo)electrodes. Specifically\, we use direct pore-level simulations for the coupled transport characterization of mesostructured (photo)electrodes utilizing nano-tomography techniques to obtain the exact mesostructure that is utilized in direct numerical simulations [4]. I will extend these investigations to ordered structures for the assessment of the transport in mesostructured electrodes for the electorchemical reduction of CO2 and discuss the effect of the mass transport on selectivity and activity [5]. I will then present possibilities to simplify these involved multi-dimensional numerical models into rapid screening models based on semi-analytical correlations. I will discuss analysis results for a large range of semiconductor materials [6\,7]. I will end with an outlook on research challenges and gaps in the field of (photo)electrochemical water and CO2 splitting. \n\nThis seminar is co-hosted by the Michigan Institute for Computational Discovery & Engineering\, and the Mechanical Engineering department within the University of Michigan College of Engineering. Dr. Haussener will be hosted by Rohini Bala Chandran\, Assistant Professor of Mechanical Engineering. \nThe MICDE Fall 2020 and Winter 2021 Seminar Series is open to the general public. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend.  \nQuestions? Email MICDE-events@umich.edu \n\nReferences: \n[1] M. Dumortier\, S. Tembhurne\, S. Haussener\, Energy Environ. Sci. \, 8:3614–3628\, 2015\n[2] S. Tembhurne\, F. Nandjou\, S. Haussener\, Nature Energy\, 10.1038/s41560-019-0373-7\, 2019\n[3] S. Tembhurne\, S. Haussener\, Journal of The Electrochemical Society \, 163:H1008-H1018\, 2016\n[4] S. Suter\, M. Catoni\, Y. Gaudy\, S. Pokrant\, S. Haussener\, Linking Morphology and Multi-Physical Transport in\nStructured Photoelectrodes\, Sustainable Energy & Fuels \, doi: 10.1039/C8SE00215K\, 2018.\n[5] S. Suter\, S. Haussener\, Energy Environmental Science \, doi: 10.1039/C9EE00656G\, 2019.\n[6] Y. Gaudy\, S. Haussener\, Rapid Performance Optimization Method for Photoelectrodes\, Journal of Physical Chemistry\nC\, doi: 10.1021/acs.jpcc.9b04102\, 2019.\n[7] Y. Gaudy\, Z. Gacevic\, Haussener\, Theoretical maximum photogeneration efficiency and performance characterization\nof InxGa1-xN/Si tandem water-splitting photoelectrodes\, APL Materials\, accepted\, 2020.
URL:https://micde.umich.edu/event/micde-mechanical-engineering-seminar-sophia-haussener-associate-professor-laboratory-of-renewable-energy-science-and-engineering-swiss-federal-institute-of-technology-lausanne/
LOCATION:Zoom Event
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2020/09/Sophia-Haussener.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200923T140000
DTEND;TZID=America/Detroit:20200923T170000
DTSTAMP:20260604T214433
CREATED:20230905T171252Z
LAST-MODIFIED:20230905T171252Z
UID:10000013-1600869600-1600880400@micde.umich.edu
SUMMARY:Using GPUs with Python
DESCRIPTION:Python is the Lingua Franca of Data today and is being increasingly used in scientific computations. This workshop introduces Python GPU tools for porting and writing code that runs on GPUs. The primary tools\, Numba and CuPy\, are presented with examples. A Jupyter notebook is used along with a set of lecture slides. \nThe workshop will use online tools\, so there is no need to install any software ahead of time.
URL:https://micde.umich.edu/event/using-gpus-with-python/
LOCATION:Your Desktop
CATEGORIES:Workshops
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