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SUMMARY:MICDE / AIM Seminar: Blaise Bourdin\, PhD\, Professor of Mathematics & Statistics\, McMaster University
DESCRIPTION:Zoom Link \nBio: Blaise Bourdin is a professor in the department of mathematics and statistics at McMaster University (Hamilton\, ON\, Canada). Dr. Bourdin’s formal training is at the meeting point of solid mechanics\, scientific computing\, and applied mathematics. He borrows techniques for these areas to study problems in mechanical science with a specific focus on problems involving defect mechanics and optimal design. He has cultivated this multi-disciplinary training by revisiting “classical” problems with more advanced technical tools\, by skewing my theoretical work towards problems of particular relevance to engineering and science\, and by using investigative numerical simulations as a modeling tool in complex multi-scale problems. \nDr. Bourdin’s research focusses on modeling\, analysis\, and numerical implementations of problems arising in reservoir engineering\, defect mechanics\, optimal design\, and image processing. He is the recipient of multiple research grants from the National Science Foundation\, the Louisiana Board of Regents and industry\, totalling over $6M. He has written several high impact publications\, including three ESI highly cited papers in two disciplines (mathematics and engineering). He also maintains several open source software projects. \nVARIATIONAL AND PHASE-FIELD MODELS OF BRITTLE FRACTURE: PAST SUCCESSES AND CURRENT ISSUES\nIn this talk Dr. Bourdin will start with a modern interpretation of Griffith’s classical criterion as a variational principle for a free discontinuity energy and will recall some of the milestones in its analysis. Then he will introduce the phase-field approximation per se and describe its numerical implementation. He will illustrate how phase-field models have led to major breakthroughs in the predictive simulation of fracture in complex situations. He will show how this applies to current issues\, including crack nucleation in nominally brittle materials\, fracture of heterogeneous materials\, and inverse problems.\n\n\n\n  \nThe MICDE Winter 2022 Seminar Series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nThis seminar is cohosted by the Michigan Institute for Computational Discovery (MICDE) and the Applied & Interdisciplinary Mathematics program at the University of Michigan. Dr. Bourdin will be hosted by Dr. Selim Esedoglu\, Professor of Mathematics. \nThis is a hybrid event and will be held in-person and broadcasted online via Zoom. Join here.  \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-aim-seminar-blaise-bourdin-phd-professor-of-mathematics-statistics-mcmaster-university-2/
LOCATION:Zoom Event
CATEGORIES:Education,Featured Events,MICDE Seminar Series,Seminar
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20220314T140000
DTEND;TZID=America/Detroit:20220314T150000
DTSTAMP:20260626T174734
CREATED:20220121T172527Z
LAST-MODIFIED:20230713T171008Z
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SUMMARY:MICDE Seminar: Marta D`Elia\, Principal Member of the Technical Staff\, Sandia National Laboratories
DESCRIPTION:WATCH THE RECORDING HERE. \nBio: Marta D’Elia is a Principal Member of the Technical Staff at Sandia National Laboratories\, where she works since 2014. She’s currently part of the Data Science and Computing group at the California site. She obtained her master degree in Mathematical Engineering at Politecnico of Milano with Prof. Quarteroni and she obtained her Ph.D in Applied Mathematics at Emory University with Prof. Veneziani. There\, she worked on optimal control in CFD for cardiovascular applications. She was a postdoctoral fellow at Florida State University where she worked with Prof. Gunzburger on optimization and control for nonlocal and fractional models. She’s an associate editor of the SIAM Journal on Scientific Computing\, Advances in Continuous and Discrete Models\, Numerical Methods for PDEs\, and the Journal of Peridynamics and Nonlocal Models. Also\, she’s a co-founder of the One Nonlocal World project. Her interests include nonlocal modeling and simulation\, optimization and optimal control\, and scientific machine learning. \nScientific interests: \n\nModeling and Computational aspects of Nonlocal and Fractional equations\,\nScientific Machine Learning\,\nOptimization and Uncertainty Quantification.\n\nDATA-DRIVEN LEARNING OF NONLOCAL MODELS: BRIDGING SCALES WITH NONLOCALITY \nNonlocal models are characterized by integral operators that embed length scales in their definition. As such\, they are preferable to classical partial differential equation models in situations where the dynamics of a system is affected by the small scale behavior\, yet the small scales would require prohibitive computational cost to be treated explicitly. In this sense\, nonlocal models can be considered as coarse-grained\, homogenized models that\, without resolving the small scales\, are still able to accurately capture the system’s global behavior. However\, nonlocal models depend on “kernel functions” that are often hand tuned.\nWe propose to learn optimal kernel functions from high fidelity data by combining machine learning algorithms\, known physics\, and nonlocal theory. This combination guarantees that the resulting model is mathematically well-posed and physically consistent. Furthermore\, by learning the operator rather than a surrogate for the solution\, these models generalize well to settings that are different from the ones used during training. We apply this learning technique to find homogenized nonlocal models for subsurface solute transport solely on the basis of breakthrough curves.\nWe also apply the same kernel-learning technique to design new stable and resolution-independent deep neural networks\, referred to as Nonlocal Kernel Networks (NKN). Stability of NKNs is obtained by imposing constraints derived from the nonlocal vector calculus\, whereas deep training is performed by means of a shallow-to-deep initialization technique. We demonstrate the accuracy and stability of NKNs on PDE-learning and image-classification problems. \n\nThe MICDE Winter 2022 Seminar Series is open to all. University of Michigan faculty and students interested in computational modeling and machine learning are encouraged to attend. \nThis seminar is cohosted by the Michigan Institute for Computational Discovery (MICDE) and the Department of Mechanical Engineering. Dr. D`Elia will be hosted by Dr. Krishna Garikipati\, Professor of Mechanical Engineering\, and of Mathematics. \nThis is a virtual event and will be broadcasted online via Zoom. MICDE students and fellows\, please use this form to record your attendance. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-marta-delia-phd-principal-member-of-the-technical-staff-at-sandia-national-laboratories-california/
LOCATION:Zoom Event\, MI\, United States
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
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DTSTART;TZID=America/Detroit:20220321T160000
DTEND;TZID=America/Detroit:20220321T170000
DTSTAMP:20260626T174734
CREATED:20210805T184953Z
LAST-MODIFIED:20230713T170841Z
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SUMMARY:MICDE / MIDAS Seminar: Yun S. Song\, PhD\, Professor of Computer Science and Statistics\, University of California\, Berkeley
DESCRIPTION:ZOOM LINK\nBio: Professor Yun S. Song is a professor of EECS and Statistics working in mathematical and computational biology. He received his BS degrees in mathematics and physics from MIT\, and a PhD in physics from Stanford University.  Prof. Song’s research centers around computational and mathematical biology. He is generally interested in developing computational tools and statistical methods to facilitate the research of the broad biomedical community\, while also getting deeply involved in data analysis and interpretation.  Prof. Song is also interested in machine learning\, combinatorial optimization\, algorithms\, and Monte Carlo methods. \nRecent honors and awards include NIH Pathway to Independence Award K99/R00 (2006)\, Alfred P. Sloan Research Fellowship (2008)\, Packard Fellowship for Science and Engineering (2008)\, NSF CAREER Award (2009)\, Jim and Donna Gray Faculty Award for Excellence in Undergraduate Teaching (2013)\, Miller Research Professorship (2014)\, Math+X Simons Chair (2015)\, and Chan Zuckerberg Biohub Investigator Award (2017). \n\n  \nTalk Title: Mathematical and machine learning models for predicting protein synthesis and function\n  \nAbstract: Proteins are the workhorses of the cell and are involved in all aspects of cellular processes.  In spite of notable technological advances in protein biology and genomics over the past decade\, it remains an important challenge to unravel how protein synthesis and function are affected by genetic mutations.  In this talk\, I will describe our recent progress in tackling this challenge by leveraging new theoretical results on interacting particle systems and recent advances in natural language processing. \n\nThe MICDE Winter 2022 Seminar Series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nThis seminar is cohosted by the Michigan Institute for Computational Discovery (MICDE) and the Michigan Institute for Data Science (MIDAS). Dr. Song will be hosted by Dr. George Zhang\, Professor of Ecology and Evolutionary Biology. \nThis is a hybrid event and will be held in-person and broadcast online via Zoom. Note: You may register after the event has started. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-midas-seminar-yun-s-song-phd-professor-of-computer-science-and-statistics-university-of-california-berkeley/
LOCATION:West Hall 340
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2021/08/Yun-S.-Song.png
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20220401T150000
DTEND;TZID=America/Detroit:20220401T160000
DTSTAMP:20260626T174734
CREATED:20220302T210252Z
LAST-MODIFIED:20230713T170700Z
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SUMMARY:MICDE/AIM Seminar: Miguel Moyers-González\, Associate Professor of Mathematics and Statistics\, University of Canterbury
DESCRIPTION:WATCH THE RECORDING HERE.\nBio: Dr. Miguel Moyers-González completed his B.Sc. at the Instituto Tecnológico Autónomo de México and his M.Sc and Ph.D. in Mathematics at the University of British Columbia. He was a postdoctoral fellow at the Université de Montréal before joining the University of Durham as a Lecturer in Applied Mathematics. He is presently an Associate Professor in the School of Mathematics & Statistics at the University of Canterbury. Dr. Moyers-Gonzalez primary research interests are in the mathematical analysis and computation of complex fluid flows. In broad terms\, the problems he has studied involve the combination of physical understanding\, i.e. of a particular application\, coupled with both theoretical and computational techniques for partial differential equations. \nInferring physical properties and topographical features from free surface flow data\nThe accurate modelling of geophysical flows often requires information that is difficult to measure and therefore poorly quantified. Such information may relate to the fluid properties or an unknown boundary condition\, for example. The premise of this talk is that when the flow is bounded by a free surface\, the deformation of this free surface contains useful information which can be used to infer such unknown quantities. The increasing availability of free surface data through remote sensing using drones and satellites provides the impetus to use mathematical methods and numerical tools to interpret the signature embedded in the free surface deformation.\nIn this talk\, we will explore the problem of recovering simultaneously the ice thickness and basal slip of an ice flow governed by the shallow ice approximation. \n\nThe MICDE Winter 2022 Seminar Series is open to all. University of Michigan faculty and students interested in computational sciences are encouraged to attend. \nThis seminar is cohosted by the Michigan Institute for Computational Discovery (MICDE) and the Applied & Interdisciplinary Mathematics program at the University of Michigan. Dr. Moyers-González will be hosted by Dr. Mariana Carrasco-Teja\, Assistant Research Scientist and Associate Director of MICDE. \nGraduate Certificate in Computational Discovery and Engineering\, and MICDE fellows\, please use this form to record your attendance. \nThis is a virtual event. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-aim-seminar-miguel-moyers-gonzalez-phd-associate-professor-of-mathematics-and-statistics-university-of-canterbury/
LOCATION:Your Desktop
CATEGORIES:Education,Featured Events,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2022/03/Miguel-Moyers-Gonzalez.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20220405T150000
DTEND;TZID=America/Detroit:20220405T160000
DTSTAMP:20260626T174734
CREATED:20220111T193640Z
LAST-MODIFIED:20260522T182816Z
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SUMMARY:MICDE Seminar: Douglas Spearot\, Professor of Mechanical & Aerospace Engineering\, University of Florida
DESCRIPTION:WATCH THE RECORDING HERE.\nBio: Dr. Douglas Spearot is a Newton C. Ebaugh Professor in the Department of Mechanical & Aerospace Engineering in the Herbert Wertheim College of Engineering at the University of Florida. He also holds an affiliate appointment in the Department of Materials Science & Engineering. From 2005-2015\, he was an Assistant/Associate Professor in the Department of Mechanical Engineering and a member of the Institute for Nanoscience and Engineering at the University of Arkansas. His research focuses on the use of atomistic and mesoscale simulation techniques to study the mechanical and thermodynamic properties of materials\, with particular focus on the behavior of dislocations and interfaces\, and the development of computational tools to extract experimentally relevant metrics from simulation generated data. Dr. Spearot received his B.S. in Mechanical Engineering from the University of Michigan\, and his M.S. and Ph.D. in Mechanical Engineering from the Georgia Institute of Technology. \nAwards: \n\n2010 NSF CAREER Award to elucidate the nanoscale mechanisms associated with phase selection during vapor deposition.\n2007 Ralph E. Power Junior Faculty Enhancement Award to study plasticity in nanostructured materials.\n2020 Teacher of the Year in the Department of Mechanical & Aerospace Engineering\, University of Florida.\n2014 College of Engineering Imhoff Outstanding Teaching Award\, University of Arkansas.\n2014 Arkansas Alumni Association Rising Teaching Award\, University of Arkansas.\n\nMesoscale Modeling of Plasticity in Metallic Materials via Advancement of the Discrete Dislocation Dynamics Simulation Method\nPlastic deformation in metallic materials is governed by the individual and collective behaviors of defects\, such as dislocations and grain boundaries (GBs). Among computational methods for modeling this inherently multi scale problem\, discrete dislocation dynamics (DDD) is a powerful mesoscale technique that explicitly simulates the dynamics and interactions of dislocations and provides a continuum-level understanding of plasticity. Yet\, the utility of DDD simulations for certain problems is compromised by missing defect physics and limited linkages to experiments. The focus of this seminar will be on two advancements to the DDD method. First\, a disclination-dislocation framework for modeling the mechanical structure of equilibrium GBs (EGBs) and nonequilibrium GBs (NEGBs) is incorporated into the DDD method. This approach accounts for the mechanical and kinetic effects of multiple transmission events\, and the absorption of residual dislocations at the GB. DDD simulations reveal that accumulated dislocation content from prior slip transmission lowers the external driving stresses required for subsequent slip transmission\, indicating GB softening. Second\, to enhance the connection between DDD simulations and experiments\, a new “virtual” diffraction method is developed to generate strain-broadened diffraction profiles from DDD microstructures. This method is used to generate a database of diffraction profiles from simulated dislocation microstructures\, which enables a new data-driven approach for dislocation density prediction from diffraction line profile analysis. \n\nThe MICDE Winter 2022 Seminar Series is open to all. University of Michigan faculty and students interested in the mechanical and thermodynamic properties of materials are encouraged to attend. \nDr. Spearot will be hosted by Dr. Yue Fan\, Assistant Professor of Mechanical Engineering. \nThis is a hybrid event and will be held in-person and broadcast online via Zoom.  \nGraduate Certificate in Computational Discovery and Engineering\, and MICDE fellows\, please use this form to record your attendance. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-douglas-spearot-phd-professor-of-mechanical-aerospace-engineering-university-of-florida/
LOCATION:1311 EECS\, 1301 Beal Ave.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
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DTSTART;TZID=America/Detroit:20220414T103000
DTEND;TZID=America/Detroit:20220414T113000
DTSTAMP:20260626T174734
CREATED:20220322T145723Z
LAST-MODIFIED:20230713T165804Z
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SUMMARY:MICDE Seminar: Katya Scheinberg\,Professor of Operations Research and Information Engineering\, Cornell University
DESCRIPTION:WATCH THE RECORDING HERE. \nBio: Dr. Katya Scheinberg is a Professor and Director of Graduate Studies at the School of Operations Research and Information Engineering at Cornell University. Prior to joining Cornell she was the Harvey E. Wagner Endowed Chair Professor at the Industrial and Systems Engineering Department at Lehigh University. She attended Moscow University for her undergraduate studies and received her PhD degree from Columbia University. She worked at the IBM T.J. Watson Research Center as a research staff member for over a decade before joining Lehigh in 2010.\nProf. Scheinberg’s main research areas are related to developing practical algorithms (and their theoretical analysis) for various problems in continuous optimization\, such as convex optimization\, derivative free optimization\, machine learning\, quadratic programming\, etc. She is a recipient of the Lagrange Prize from SIAM and MOS\, the Farkas Prize from Informs Optimization Society and the Outstanding Simulation Publication award from Informs Simulation Society.\nProf. Scheinberg is currently the editor-in-chief of Mathematics of Operations Research\, and a co-editor of Mathematical Programming. \n\nOverview of Adaptive Optimization Methods for Stochastic Oracles\nContinuous optimization is a mature field\, which has recently undergone major expansion and change. One of the key new directions is the development of methods that do not require exact information about the objective function. Nevertheless\, the majority of these methods\, from stochastic gradient descent to “zero-th order” methods use some kind of approximate first order information. We will introduce a general definition of a stochastic and show how this definition applies in a variety of familiar settings\, including simple stochastic gradient via sampling\, traditional and randomized finite difference methods and more. We will overview several stochastic methods and how the general definition extends to the oracles used by these methods. \n  \n\nThe MICDE Winter 2022 Seminar Series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nThis seminar is cohosted by the Michigan Institute for Computational Discovery and Engineering (MICDE) and the Department of Industrial and Operations Engineering. Dr. Scheinberg will be hosted by Dr. Albert Berahas\, Assistant Professor of Industrial and Operations Engineering. \nThis is a hybrid event and will be held in-person and broadcasted online via Zoom.  \nGraduate Certificate in Computational Discovery and Engineering\, and MICDE fellows\, please use this form to record your attendance. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-katya-scheinberg/
LOCATION:1500 EECS
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2022/03/Katya-Scheinberg.png
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20220510T150000
DTEND;TZID=America/Detroit:20220510T160000
DTSTAMP:20260626T174734
CREATED:20220408T080005Z
LAST-MODIFIED:20260612T022419Z
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SUMMARY:SiTime Research Partnership and Career Event
DESCRIPTION:This event will also be broadcasted via Zoom. Please register.\nRefreshments will be served. Please REGISTER by May 6\, 2022\, specially if you are planning to attend in person. You’ll need to use your U-M credentials.\nSiTime\, a market leader in MEMS timing\, will present an overview of its business\, products and some of the tough computational science and FEA related problems it is working to solve in its MEMS resonator (timing reference) design. SiTime has a world leading computational science and FEA based design group and is looking for partnerships with research groups at the University of Michigan\, and great talents (graduate students and post docs hire) to help accelerate its innovation as it revolutionizes the timing industry with groundbreaking solutions. \nResumes of graduate students and post docs are welcome for internship and job opportunities!\n\nSiTime Corporation\, a market leader in MEMS timing\, offers MEMS-based silicon timing system solutions. SiTime’s configurable solutions offer a rich feature set that enables customers to differentiate their products with high performance\, small size\, low power\, and high reliability. With over 1.5 billion devices shipped to date\, SiTime is changing the timing industry. \n\nUniversity of Michigan faculty and students interested in finite element methods\, microelectromechanical systems\, shape optimization\, computational geometry\, continuum mechanics\, non-linear behavior\, multiparametric non-convex constrained optimization or materials science are encouraged to attend. \nThis is a hybrid event and will be held in-person and broadcast online via Zoom. Please register by May 6\, 2022
URL:https://micde.umich.edu/event/sitime-research-partnership-and-career-event/
LOCATION:Johnson Rooms\, Lurie Engineering Center\, 3rd Floor\, 1221 Beal Ave.\, Ann Arbor\, MI\, United States
CATEGORIES:Featured Events
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20220520T130000
DTEND;TZID=America/Detroit:20220521T173000
DTSTAMP:20260626T174734
CREATED:20220407T201959Z
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SUMMARY:Midwest Numerical Analysis Day 2022
DESCRIPTION:[vc_row type=”in_container” full_screen_row_position=”middle” scene_position=”center” text_color=”dark” text_align=”left” overlay_strength=”0.3″ shape_divider_position=”bottom” bg_image_animation=”none”][vc_column column_padding=”no-extra-padding” column_padding_position=”all” background_color_opacity=”1″ background_hover_color_opacity=”1″ column_link_target=”_self” column_shadow=”none” column_border_radius=”none” width=”1/1″ tablet_width_inherit=”default” tablet_text_alignment=”default” phone_text_alignment=”default” column_border_width=”none” column_border_style=”solid” bg_image_animation=”none”][vc_column_text]The Midwest Numerical Analysis Day (MWNADay) is a forum for researchers at all stages of their careers\, mainly from the Midwest\, to exchange ideas in numerical analysis\, scientific computing and related application areas. \nThis year it will take place in person and on line at the University of Michigan\, Ann Arbor on May 20 & May 21.\nParticipants are invited to give a contributed talk or present a poster. Participation of graduate students and postdocs is encouraged. Partial travel support is available. \nFor more information and to register\, please visit the event’s site. \n\nMWNAD 2022 is sponsored by the University of Michigan Department of Mathematics\, the Michigan Center for Applied and Interdisciplinary Mathematics (MCAIM) and the Michigan Institute for Computational Discovery and Engineering (MICDE). \nEmail questions about this year’s event to MWNADadmin@umich.edu.[/vc_column_text][/vc_column][/vc_row]
URL:https://micde.umich.edu/event/midwest-numerical-analysis-day-2022/
LOCATION:East Hall\, 530 Church St\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Conference,Featured Events
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/02/MidwestNumericalAnalysisDay2022_narrow.png
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20220527T100000
DTEND;TZID=America/Detroit:20220527T160000
DTSTAMP:20260626T174734
CREATED:20220426T182037Z
LAST-MODIFIED:20230217T195840Z
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SUMMARY:2022 SIAM Student Mini-Symposium in Applied Mathematics
DESCRIPTION:The SIAM student chapter at the University of Michigan is hosting its 3rd Annual Student Mini-symposium in Applied Mathematics. This event will allow students from different disciplines in the area to see what is being done in the field and promote interest in applied mathematics in general. \nThis event is open to all graduate students in the University of Michigan.  Students are invited to submit abstracts for short presentations. Deadline to submit an abstract is May 13\, 2022. To register please fill out this form by May 15\, 2022. \nFree food and drinks will be provided to all registered attendees!  \nEvent’s Website | Event Poster \n\nQuestions? Please email Christiana Mavroyiakoumou at chrismav@umich.edu or any of the organizer listed on the event’s website.
URL:https://micde.umich.edu/event/2022-siam-student-mini-symposium-in-applied-mathematics/
LOCATION:1372 East Hall\, 530 Church St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Education,Featured Events
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20220915T150000
DTEND;TZID=America/Detroit:20220915T160000
DTSTAMP:20260626T174734
CREATED:20220818T193725Z
LAST-MODIFIED:20230713T164622Z
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SUMMARY:MICDE / IOE Seminar: Andreas Wächter\, Professor of Industrial Engineering and Management Sciences\, Northwestern University
DESCRIPTION:WATCH THE RECORDING HERE. \nAndreas Wächter is a Professor in the Department of Industrial Engineering and Management Sciences at Northwestern University. His research interests include the design\, analysis\, implementation and application of numerical algorithms for nonlinear continuous and mixed-integer optimization. He obtained his master’s degree in Mathematics at the University of Cologne\, Germany\, in 1997\, and this Ph.D. in Chemical Engineering at Carnegie Mellon University in 2002. Before joining Northwestern University in 2011\, he was a Research Staff Member in the Department of Mathematical Sciences at IBM Research in Yorktown Heights\, NY. He is a recipient of the 2011 Wilkinson Prize for Numerical Software and the 2009 Informs Computing Society Prize for his work on the open-source optimization package Ipopt. \n\n\n\nTHE ARPA-E GRID OPTIMIZATION COMPETITION\nIn recent years\, the US Advanced Research Projects Agency-Energy (ARPA-E) has been organizing the “Grid Optimization Competition.” To participate\, teams from academia and industry submitted computer program implementations of specialized algorithms for solving large realistic Security-Constrained Optimal Power Flow (SCOPF) problems. The performance of the solvers was tested and ranked independently by the organizers\, using large-scale real-life instances. The goal of SCOPF is the determination of the most cost-efficient operation of an electrical power grid in a such way that it can withstand contingencies in the form of outages of any its components. Mathematically\, this is an extremely large-scale two-stage nonlinear and nonconvex optimization problem. In this presentation\, the approach of several teams will be described\, including that of our own GO-SNIP team that placed second in the first challenge. \nFollowing the seminar IOE is holding a small reception in IOE Commons – 1709\, snacks and refreshments will be served. \n\nThe MICDE Fall 2022 Seminar Series is open to all. University of Michigan faculty and students interested in power grid optimization are encouraged to attend. \nThis seminar is cohosted by the Michigan Institute for Computational Discovery & Engineering (MICDE) and the Department of Industrial and Operations Engineering. Prof. Wächter will be hosted by Dr. Salar Fattahi\, Assistant Professor of Industrial and Operations Engineering and Dr. Siqian Shen\, Associate Professor of Industrial and Operations Engineering and Associate Professor of Civil and Environmental Engineering. \nThis event is in-person only! \nGraduate Certificate in Computational Discovery and Engineering\, and MICDE fellows\, please use this form to record your attendance. \nQuestions? Email MICDE-events@umich.edu \n 
URL:https://micde.umich.edu/event/micde-ioe-seminar-andreas-wachter-professor-of-industrial-engineering-and-management-sciences-northwestern-university/
LOCATION:Johnson Rooms\, Lurie Engineering Center\, 3rd Floor LEC 3213ABC\, 1221 Beal Ave.\, Ann Arbor\, MI\, United States
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20220923T160000
DTEND;TZID=America/Detroit:20220923T170000
DTSTAMP:20260626T174734
CREATED:20220825T193358Z
LAST-MODIFIED:20230810T200736Z
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SUMMARY:MICDE Seminar: Pania Newell\, Assistant Professor of Mechanical Engineering\, University of Utah
DESCRIPTION:Pania Newell is currently an Assistant Professor in the Department of Mechanical Engineering and holds adjunct faculty positions at the School of Computing and Civil Engineering Department at the University of Utah. Before joining The University of Utah\, she was a member of the technical staff at Sandia National Laboratories. She obtained her M.S. and Ph.D. from the University of New Mexico and the University of Colorado-Boulder\, respectively. Her research interest lies at the interface of mechanics and material sciences. In particular\, she is interested in multi-scale\, multi-physics phenomena in heterogeneous porous materials through developing theoretical\, computational\, and experimental frameworks combined with data sciences. She is the co-founder/co-host of an academic podcast called “This Academic Life”. \nMECHANICS OF HIERARCHICAL POROUS MATERIALS: DESIGN\, CONTROL AND PREDICTION \nHierarchical porous materials with pores at multiple length scales are widespread in nature. Although different compositions\, textures\, and physical properties of natural porous materials have inspired researchers and engineers to design materials with controllable pore structures\, the hierarchical structure of natural porous materials poses challenges in understanding damage and fracture in these complex systems. To be able to create nature-inspired materials\, we must have a mechanistic understanding of materials ranging from the macro- to the nanoscale. In this talk\, I will begin by providing an overview of porous materials and their substantial role in our energy sector. I will then discuss some of our recent efforts in designing nano/micro porous structures with different pore morphology and novel in-situ testing to highlight the effect of different structural and geometrical parameters in porous materials across scales. I will also show how computational tools enable us to enhance our fundamental understanding of fracture propagation mechanisms in such materials over a wide range of scales. At the nanoscale\, molecular dynamics simulation provides information about mechanical properties\, such as fracture energy release rate for various pore morphologies. At the micro-scale\, the impact of the pore shape and size on fracture pattern is investigated through a two-scale homogenization method coupled with the state-of-the-art phase-field fracture technique. The results of this hierarchical coupling approach highlight the importance of higher-order parameters associated with the pore shape and size on fracture properties and patterns at the continuum scale. \n  \n\n  \nThe MICDE Fall 2022 Seminar Series is open to all. University of Michigan faculty and students interested in multi-scale\, multi-physics phenomena in heterogeneous porous materials are encouraged to attend. \nThis seminar is hosted by the Michigan Institute for Computational Discovery & Engineering (MICDE). Prof. Newell will be hosted by Prof. Krishna Garikipati\, Professor of Mechanical Engineering and Mathematics and Director of MICDE. \nThis is an in-person event\, Zoom link will only be provided upon request. \nGraduate Certificate in Computational Discovery and Engineering\, and MICDE fellows\, please use this form to record your attendance. \nQuestions? Email MICDE-events@umich.edu \nWATCH THE RECORDING HERE.
URL:https://micde.umich.edu/event/micde-seminar-pania-newell-assistant-professor-of-mechanical-engineering-university-of-utah/
LOCATION:1200 EECS\, 1301 Beal Ave.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20221026T133000
DTEND;TZID=America/Detroit:20221026T143000
DTSTAMP:20260626T174734
CREATED:20210907T174508Z
LAST-MODIFIED:20230217T195905Z
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SUMMARY:MICDE & MIDAS Graduate Programs Info Session North Campus
DESCRIPTION:Join the MICDE and MIDAS teams for a 1-hour information session to learn more about our computational and data science graduate program offerings\, including: the Ph.D. in Scientific Computing\, the Graduate Certificate in Computational Discovery & Engineering\, the Graduate Certificate in Computational Neuroscience\, and the Graduate Certificate in Data Science. \nAfter a short presentation\, each program’s faculty director and/or staff manager will be present to answer questions. \n 
URL:https://micde.umich.edu/event/micde-midas-graduate-programs-info-session-virtual-2-2/
LOCATION:Johnson Rooms\, Lurie Engineering Center\, 3rd Floor\, 1221 Beal Ave.\, Ann Arbor\, MI\, United States
CATEGORIES:Education,Featured Events,Info Session
GEO:42.2914823;-83.7138452
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20221027T153000
DTEND;TZID=America/Detroit:20221027T163000
DTSTAMP:20260626T174734
CREATED:20220825T193358Z
LAST-MODIFIED:20230713T163634Z
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SUMMARY:MICDE Seminar: John Tramm\, Assistant Computational Scientist\, Argonne National Laboratory
DESCRIPTION:Dr. John Tramm is an assistant scientist in the computational science division at Argonne National Laboratory. He received his PhD in computational nuclear engineering from MIT in 2018. John’s research efforts are focused on improving neutron transport methods that drive massively parallel simulations of nuclear reactors using some of the world’s largest supercomputers. John also has deep experience developing and optimizing simulation applications for GPU-based systems. \n  \nTHE RISE OF PORTABLE GPU PROGRAMMING: EXPERIENCES DEVELOPING GPU-BASED SCIENTIFIC SIMULATION APPLICATIONS FOR INTEL\, NVIDIA\, AND AMD GPUs \nHistorically\, portability has not been important for GPU programming as NVIDIA has dominated the high performance computing (HPC) GPU market. With only one major GPU vendor available to choose from\, it has always made sense to develop scientific HPC apps using NVIDIA’s proprietary CUDA programming model. However\, in 2022 both AMD and Intel are releasing HPC GPU products with the intention of competing directly with NVIDIA. In fact\, the world’s first exascale supercomputer (Oak Ridge National Laboratory’s Frontier) is powered by AMD GPUs\, with another even larger exascale supercomputer (Aurora) powered by Intel GPUs set to arrive at Argonne National Laboratory shortly. These new computers highlight a trend not just from CPU to GPU in HPC\, but also a trend from proprietary CUDA into a number of different portable performance models for GPU. Thus\, scientific application developers are now confronted with not only the difficultly of porting or developing apps for GPU architectures\, but also with selecting from a wide variety of portable GPU programming models (for instance\, OpenMP offloading\, HIP\, SYCL/DPC++\, OpenCL\, Kokkos\, RAJA\, and OCCA). \nIn this talk\, I will briefly introduce the newest supercomputing systems and will give an overview of the many different portable performance models now available for GPUs. I will show a few snippets of an example kernel implemented in a variety of different models\, and will even compare performance of a scientific mini-app\, XSBench\, across all major programming models and GPU architectures. Subjective “pros and cons” of each programming model will be discussed along with quantitative performance comparisons. Next\, I will use a full scientific GPU application (the OpenMC Monte Carlo particle transport code) as a case study to discuss real-world issues affecting portable scientific GPU applications and how bleeding-edge GPU compiler technology stacks are faring. I will also briefly discuss a few of the algorithmic performance optimizations that we developed for OpenMC to give a feel for what types of changes are required to achieve high performance on GPU. \n  \n\n  \nThe MICDE Fall 2022 Seminar Series is open to all. \nThis seminar is hosted by the Michigan Institute for Computational Discovery & Engineering (MICDE). Dr. Tramm will be hosted by Prof. Brendan Kochunas\, Assistant Professor of Nuclear Engineering and Radiological Sciences. \nThis is an in-person event\, Zoom link will only be provided upon request. This seminar will not be recorded! \nGraduate Certificate in Computational Discovery and Engineering\, and MICDE fellows\, please use this form to record your attendance. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-john-tramm-assistant-computational-scientist-argonne-national-laboratory/
LOCATION:1010 H. H. Dow\, 2300 Hayward St\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20221031T153000
DTEND;TZID=America/Detroit:20221031T163000
DTSTAMP:20260626T174734
CREATED:20230714T153416Z
LAST-MODIFIED:20230714T153416Z
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SUMMARY:MICDE Seminar: Reese Jones\, Distinguished Member of the Technical Staff\, Sandia National Laboratories
DESCRIPTION:Reese Jones is currently a staff scientist at Sandia National Laboratories in Livermore\, CA. He is engaged in materials science and computational physics research with scales ranging from atomic/molecular to the continuum. He has made contributions to multi-scale methods\, electrochemical and thermal transport\, atomic-level fracture\, and contact. Recently he has been developing and applying machine learning methods to provide constitutive models for\ncomplex materials\, quantify material uncertainty\, and interpret materials imaging for reliability analysis. \nPREDICTING FAILURE IN POROUS METALS USING CONVOLUTIONAL NEURAL NETWORKS \nPredicting whether defects are critical or not is a high-value task in medicine\, materials engineering\, and other fields. Tools that augment expert opinion are needed in the current era of high resolution imaging that can reveal an overwhelming number of defects. In particular\, porosity is a persistent feature of additively manufactured materials and determines failure locations through complex mechanics that exhibit sensitivity to the initial pore locations. In the case of materials engineering expensive direct numerical simulations are available and can be used to train efficient surrogates. Neural networks\, such as the one we have developed\, enable more complete analysis of potential outcomes. \nIn this work\, we develop convolutional neural networks as surrogate models for predicting failure\nlocations. The binary classification problem of categorizing intact/failed voxels is first regularized by recasting it as a regression problem for the continuous damage field subjected to pre-processing transformations. An apparent challenge is the damage fields display a relatively small number of voxels close to failure leading to a form of class imbalance for regression that can cause the optimizer to converge to a poor local minimum. We address this through a re-weighting of the loss function which accounts for the relative frequencies of damage values. Another challenging aspect is the high sensitivity of the outcomes to the porosity field which typically creates multiple regions of high damage competing for failure. This motivates the use of Bayesian neural networks to capture sensitivities in the prediction through uncertainty quantification. We use these uncertainties to rank the likelihood of failure of any particular cluster of porosity in a reliability analysis. Lastly\, to aid transferability of the network and reduce the training burden when it is applied to new materials and processes\, we are exploring transfer learning techniques. \n  \n\n  \nThe MICDE Fall 2022 Seminar Series is open to all. \nThis seminar is hosted by the Michigan Institute for Computational Discovery & Engineering (MICDE). Dr. Jones will be hosted by Prof. Krishna Garikipati\, Professor of Mechanical Engineering and Mathematics and Director of MICDE. \nThis is an in-person event\, Zoom link will only be provided upon request. This seminar will not be recorded. \nGraduate Certificate in Computational Discovery and Engineering\, and MICDE fellows\, please use this form to record your attendance. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-reese-jones-distinguished-member-of-the-technical-staff-sandia-national-laboratories/
LOCATION:1303 EECS\, 1301 Beal Ave\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Education,Featured Events,MICDE Seminar Series,Seminar
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20221031T153000
DTEND;TZID=America/Detroit:20221031T163000
DTSTAMP:20260626T174734
CREATED:20230905T171445Z
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SUMMARY:MICDE Seminar: Reese Jones\, Distinguished Member of the Technical Staff\, Sandia National Laboratories
DESCRIPTION:Reese Jones is currently a staff scientist at Sandia National Laboratories in Livermore\, CA. He is engaged in materials science and computational physics research with scales ranging from atomic/molecular to the continuum. He has made contributions to multiscale methods\, electrochemical and thermal transport\, atomic-level fracture\, and contact. Recently he has been developing and applying machine learning methods to provide constitutive models for\ncomplex materials\, quantify material uncertainty\, and interpret materials imaging for reliability analysis. \nPREDICTING FAILURE IN POROUS METALS USING CONVOLUTIONAL NEURAL NETWORKS \nPredicting whether defects are critical or not is a high-value task in medicine\, materials engineering\, and other fields. Tools that augment expert opinion are needed in the current era of high resolution imaging that can reveal an overwhelming number of defects. In particular\, porosity is a persistent feature of additively manufactured materials and determines failure locations through complex mechanics that exhibit sensitivity to the initial pore locations. In the case of materials engineering expensive direct numerical simulations are available and can be used to train efficient surrogates. Neural networks\, such as the one we have developed\, enable more complete analysis of potential outcomes. \nIn this work\, we develop convolutional neural networks as surrogate models for predicting failure\nlocations. The binary classification problem of categorizing intact/failed voxels is first regularized by recasting it as a regression problem for the continuous damage field subjected to pre-processing transformations. An apparent challenge is the damage fields display a relatively small number of voxels close to failure leading to a form of class imbalance for regression that can cause the optimizer to converge to a poor local minimum. We address this through a re-weighting of the loss function which accounts for the relative frequencies of damage values. Another challenging aspect is the high sensitivity of the outcomes to the porosity field which typically creates multiple regions of high damage competing for failure. This motivates the use of Bayesian neural networks to capture sensitivities in the prediction through uncertainty quantification. We use these uncertainties to rank the likelihood of failure of any particular cluster of porosity in a reliability analysis. Lastly\, to aid transferability of the network and reduce the training burden when it is applied to new materials and processes\, we are exploring transfer learning techniques. \n  \n\n  \nThe MICDE Fall 2022 Seminar Series is open to all. \nThis seminar is hosted by the Michigan Institute for Computational Discovery & Engineering (MICDE). Dr. Jones will be hosted by Prof. Krishna Garikipati\, Professor of Mechanical Engineering and Mathematics and Director of MICDE. \nThis is an in-person event\, Zoom link will only be provided upon request. This seminar will not be recorded. \nGraduate Certificate in Computational Discovery and Engineering\, and MICDE fellows\, please use this form to record your attendance. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-reese-jones-scientist-sandia-national-laboratories/
LOCATION:1303 EECS\, 1301 Beal Ave\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Education,Featured Events,Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20221102T133000
DTEND;TZID=America/Detroit:20221102T143000
DTSTAMP:20260626T174734
CREATED:20210907T174508Z
LAST-MODIFIED:20230217T195904Z
UID:10000529-1667395800-1667399400@micde.umich.edu
SUMMARY:MICDE & MIDAS Graduate Programs Info Session Central Campus
DESCRIPTION:Join the MICDE and MIDAS teams for a 1-hour information session to learn more about our computational and data science graduate program offerings\, including: the Ph.D. in Scientific Computing\, the Graduate Certificate in Computational Discovery & Engineering\, the Graduate Certificate in Computational Neuroscience\, and the Graduate Certificate in Data Science. \nAfter a short presentation\, each program’s faculty director and/or staff manager will be present to answer questions. \n 
URL:https://micde.umich.edu/event/micde-midas-graduate-programs-info-session-virtual-2/
LOCATION:340 West Hall\, 1085 South University Ave.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Education,Featured Events,Info Session
GEO:42.2757556;-83.7362041
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=340 West Hall 1085 South University Ave. Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=1085 South University Ave.:geo:-83.7362041,42.2757556
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20221103T160000
DTEND;TZID=America/Detroit:20221103T170000
DTSTAMP:20260626T174734
CREATED:20211021T140003Z
LAST-MODIFIED:20230809T192106Z
UID:10000537-1667491200-1667494800@micde.umich.edu
SUMMARY:PhD Seminar: Srihari Sundar and Vishwas Goel
DESCRIPTION:The Ph.D. in Scientific Computing program is intended for students who will make extensive use of large-scale computation\, computational methods\, or algorithms for advanced computer architectures in their doctoral studies. This seminar series showcases the breadth of research covered by the program.  \nFeatured Speakers:\nSrihari Sundar\, PhD Candidate\, Aerospace Engineering and Scientific Computing\nHari’s research interests include decarbonization of the power sector\, climate impacts\, computational modeling\, and sustainable transformation. His current research in the center for sustainable systems is focused on predicting changes in the energy system — meteorology interaction with a transition to widespread renewable energy generation. He aspires to use this to inform long term planning of reliable power systems under a changing climate while ensuring a just transition. \nLinkedIn   Twitter \nMeteorological Drivers of Resource Adequacy Failures During the Transition to a Decarbonized Power System\nIncreasing meteorological extremes and renewable penetrations could challenge resource adequacy (RA) in the electric power system\, as demonstrated by recent blackouts in California and Texas. We quantify meteorological drivers of RA in the Western U.S. power system\, and examine how these drivers change with increasing renewable penetrations. Our analysis integrates an optimization-based capacity expansion model\, stochastic RA model\, and neural-network-based self-organizing maps. We find that RA failures are driven by high pressure circulation patterns which produce positive surface temperature anomalies and negative solar radiation and wind speed anomalies. Further\, with increasing renewable penetration we find that the probability of failure attributed to patterns associated with heat waves over the region increases. \n\nVishwas Goel\, PhD Candidate\, Materials Science and Engineering and Scientific Computing\nVishwas is a Ph.D. candidate in the Department of Materials Science and Engineering. His research is primarily focused on simulating electrochemical phenomena on multiple scales. \nLinkedIn \nSimulating microgalvanic corrosion in Mg alloys using PRISMS-PF\nMagnesium and its alloys are the lightest structural metallic materials known\, and therefore\, hold vast potential for reducing the weight for various transportation modes such as airplanes\, cars\, buses\, etc. Although the alloying of Mg with elements such as Al\, Mn\, and rare earth (RE) elements is known to improve the mechanical properties of Mg\, the process is often detrimental to the corrosion performance of Mg. This increase in the corrosion rate occurs because of the micro-galvanic couple that forms between the Mg-rich phase\, which acts as an anode\, and the alloying-element-rich phase\, which acts as a cathode. \nUsing both experiments and modeling\, it has been reported that the rate of micro-galvanic corrosion in the Mg-alloys depends on the alloying element and microstructure. However\, a deeper understanding is required for quantifying the effect of microstructure characteristics such as the fraction of the two phases\, spacing between the two phases\, the geometry of the two phases\, etc.\, on the corrosion rate. This understanding is crucial for designing Mg-alloys with optimal mechanical properties and high corrosion resistance. \nTo bridge this gap in our understanding\, we perform the continuum-scale phase-field modeling of different microstructures observed in Mg-alloys. Furthermore\, we complement the modeling work with theoretical analysis\, where we develop analytical relations for studying the effect of various material and microstructural parameters on the characteristic corrosion length scale. The results from both these efforts will be summarized in our presentation. \n\n  \nThis event is part of MICDE’s Fall 2022 seminar series featuring Ph.D. students in the Scientific Computing program. This series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nQuestions? Email MICDE-events@umich.edu \n 
URL:https://micde.umich.edu/event/phd-seminar-srihari-sundar-and-vishwas-goel/
LOCATION:Weiser Hall\, 6th Floor\, 619\, 500 Church Street\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE PhD Seminar Series,Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20221111T150000
DTEND;TZID=America/Detroit:20221111T160000
DTSTAMP:20260626T174734
CREATED:20220901T211133Z
LAST-MODIFIED:20230713T163450Z
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SUMMARY:MICDE / AIM Seminar: Jennifer Franck\, Assistant Professor of Engineering Physics\, University of Wisconsin-Madison
DESCRIPTION:WATCH THE RECORDING HERE. \nJennifer Franck is an Assistant Professor in the Department of Engineering Physics at the University of Wisconsin-Madison. She leads the Computational Flow Physics and Modeling Lab\, using computational fluid dynamics (CFD) techniques to explore the flow physics of unsteady and turbulent flows. Ongoing research projects are in the areas of bio-inspired flows and the fluid dynamics of renewable energy systems with current projects funded by NSF and ARPA-E. Prior to joining the UW-Madison faculty in 2018\, she was faculty at Brown University. She received her undergraduate degree in Aerospace Engineering from University of Virginia\, followed by a M.S. and Ph.D. from California Institute of Technology. Following her PhD\, she was awarded an NSF Postdoctoral Fellowship hosted at Brown University to computationally explore fluid dynamics mechanics of flapping flight. \nPREDICTIVE MODELING OF OSCILLATING FOIL WAKE DYNAMICS \nSwimming and flying animals rely on the fluid around them to provide lift or thrust forces\, leaving behind a distinct vortex wake in the fluid. The structure and size of the vortex wake is a blueprint of the animal’s kinematic trajectory\, holding information about the forces and also the size\, speed and direction of motion. This talk will introduce a bio-inspired oscillating turbine\, which can be operated to generate energy from moving water through lift generation\, in the same manner as flapping birds or bats. This style of turbines offers distinct benefits compared with traditional rotation-based turbines such as the ability to dynamically shift its kinematics for changing flow conditions\, thus altering its wake pattern. Current efforts lie in predicting the vortex formation and dynamics of the highly structured wake such that it can be utilized towards cooperative motion within arrays of oscillating foils. Using numerical simulations\, this talk will discuss efforts towards linking the fluid dynamic wake signature to the underlying foil kinematics\, and investigating how that effects the energy harvesting performance of downstream foils. Two machine learning methodologies are introduced to classify\, cluster and identify complex vorticity patterns and modes of energy harvesting\, and inform more detailed modeling of arrays of oscillating foils. \n  \n\nThe MICDE Fall 2022 Seminar Series is open to all. University of Michigan faculty and students interested in computational fluid dynamics are encouraged to attend. \nThis seminar is cohosted by the Michigan Institute for Computational Discovery and Engineering (MICDE) and the Applied & Interdisciplinary Mathematics program (AIM) at the University of Michigan. Prof. Franck will be hosted by Prof. Silas Alben\, Professor of Mathematics. \nThis is a virtual event broadcasted online via Zoom. \nGraduate Certificate in Computational Discovery and Engineering\, and MICDE fellows\, please use this form to record your attendance. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-jennifer-franck-assistant-professor-of-engineering-physics-university-of-wisconsin-madison/
LOCATION:Zoom Event\, MI\, United States
CATEGORIES:Education,Featured Events,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2022/09/Jennifer-Franck.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20221116T153000
DTEND;TZID=America/Detroit:20221116T163000
DTSTAMP:20260626T174734
CREATED:20220825T193358Z
LAST-MODIFIED:20230713T163322Z
UID:10000579-1668612600-1668616200@micde.umich.edu
SUMMARY:MICDE Seminar: Miguel Bessa Associate Professor of Engineering\, Brown University
DESCRIPTION:Miguel Bessa is an Associate Professor in the School of Engineering at Brown University. His research interests include computational mechanics and materials science\, development of numerical methods\, machine learning and optimization\, multi-scale modeling of materials and structures. Miguel Bessa and his research group envision a new era for the design of materials and structures using artificial intelligence. Miguel received a PhD in Mechanical Engineering from Northwestern University in 2016 as a Fulbright scholar. After a short postdoctoral position at Caltech (2017) and a quick leap from Assistant to Associate Professor (2021) at Delft University of Technology\, he joined the Solid Mechanics Group at Brown University in the Summer of 2022. \nCOOPERATIVE DATA-DRIVEN MODELING \nThe human brain is capable of learning tasks mostly without forgetting. However\, deep neural networks suffer from catastrophic forgetting when learning tasks one after the other. We address this challenge considering a class-incremental learning scenario where the network sees test data without knowing its origin. We show the best results to date for the ImageNet dataset\, outperforming by more than 20% the state of the art. The proposed method is also applied to learn material laws\, illustrating its versatility. This strategy is believed to open new avenues for cooperation among different researchers and practitioners. \n  \n\nThe MICDE Fall 2022 Seminar Series is open to all. \nThis seminar is hosted by the Michigan Institute for Computational Discovery & Engineering (MICDE). Prof. Bessa will be hosted by Prof. Krishna Garikipati\, Professor of Mechanical Engineering and Mathematics and Director of MICDE. \nThis is an in-person event\, Zoom link will only be provided upon request. \nGraduate Certificate in Computational Discovery and Engineering\, and MICDE fellows\, please use this form to record your attendance. \nQuestions? Email MICDE-events@umich.edu \nWATCH THE RECORDING HERE.
URL:https://micde.umich.edu/event/micde-seminar-miguel-bessa-associate-professor-of-engineering-brown-university/
LOCATION:1303 EECS\, 1301 Beal Ave\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2022/08/Miguel-bessa.png
GEO:42.292322;-83.713272
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=1303 EECS 1301 Beal Ave Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=1301 Beal Ave:geo:-83.713272,42.292322
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20221117T160000
DTEND;TZID=America/Detroit:20221117T163000
DTSTAMP:20260626T174734
CREATED:20211021T140003Z
LAST-MODIFIED:20230809T191957Z
UID:10000548-1668700800-1668702600@micde.umich.edu
SUMMARY:PhD Seminar: Khoi Dang
DESCRIPTION:The Ph.D. in Scientific Computing program is intended for students who will make extensive use of large-scale computation\, computational methods\, or algorithms for advanced computer architectures in their doctoral studies. This seminar series showcases the breadth of research covered by the program.  \nFeatured Speaker:\nKhoi Dang\, PhD Candidate\, Chemistry and Scientific Computing\nKhoi is a 5th year graduate student in the Chemistry Department currently developing electronic structure theory methods in the Zimmerman Group. \nParallel Heat-bath Configuration Interaction\nThe heat-bath configuration interaction (HBCI) method is a deterministic wave function method that approaches the full CI limit at greatly reduced cost. HBCI consists of two parts: the generation of a variational wave function\, followed by a perturbative correction. This work introduces a parallel implementation that is highly scalable and overcomes the memory bottleneck of perturbation theory. The implementation demonstrates 83% parallel efficiency for the perturbative step on 32 nodes. \n\n  \nThis event is part of MICDE’s seminar series featuring Ph.D. students in the Scientific Computing program. This series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nQuestions? Email MICDE-events@umich.edu \n 
URL:https://micde.umich.edu/event/phd-seminar-khoi-dang/
LOCATION:Weiser Hall\, 6th Floor\, 619\, 500 Church Street\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE PhD Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/02/2022-Fall-Dang.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20221201T160000
DTEND;TZID=America/Detroit:20221201T170000
DTSTAMP:20260626T174734
CREATED:20211021T140003Z
LAST-MODIFIED:20260522T141801Z
UID:10000549-1669910400-1669914000@micde.umich.edu
SUMMARY:PhD Seminar: Meichen Liu
DESCRIPTION:The Ph.D. in Scientific Computing program is intended for students who will make extensive use of large-scale computation\, computational methods\, or algorithms for advanced computer architectures in their doctoral studies. This seminar series showcases the breadth of research covered by the program.  \nFeatured Speakers:\nMeichen Liu\, PhD Candidate\, Earth and Environmental Science and Scientific Computing\nShe works with Professor Jeroen Ritsema in the department of Earth and Environmental Sciences. Her research involves characterizing earthquake sources as well as imaging structures in deep Earth. \nInfluence of shear wave velocity heterogeneity on SH-wave reverberation imaging of the mantle transition zone\nWe use the top-side shear wave reflection Ssds as a probe for mapping the depths of the mantle transition zone (MTZ) beneath the contiguous US. Using a common-reflection point (CRP) mapping approach\, we observe that the MTZ are about 40–50 km deeper beneath the western United States than the central-eastern United States if based on the 1-D Earth wave velocity model (Preliminary Reference Earth Model). However\, the east-to-west deepening of the MTZ disappears in the CRP image if we account for 3-D shear wave velocity variations in the mantle according to global tomography. In addition\, from spectral-element method synthetics\, we find that ray theory overpredicts the traveltime delays of the reverberations. Undulations of the MTZ are underestimated when their wavelengths are smaller than the Fresnel zones of the wave reverberations in the MTZ. Therefore\, modelling of layering in the upper mantle must be based on 3-D reference structures and accurate calculations of reverberation traveltimes. \n\n  \nThis event is part of MICDE’s seminar series featuring Ph.D. students in the Scientific Computing program. This series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nQuestions? Email MICDE-events@umich.edu \n 
URL:https://micde.umich.edu/event/phd-seminar-meichen-liu/
LOCATION:Weiser Hall\, 6th Floor\, 619\, 500 Church Street\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE PhD Seminar Series,Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20230112T160000
DTEND;TZID=America/Detroit:20230112T163000
DTSTAMP:20260626T174734
CREATED:20211021T140003Z
LAST-MODIFIED:20230809T191524Z
UID:10000550-1673539200-1673541000@micde.umich.edu
SUMMARY:PhD Seminar: Ismael Mendoza
DESCRIPTION:The Ph.D. in Scientific Computing program is intended for students who will make extensive use of large-scale computation\, computational methods\, or algorithms for advanced computer architectures in their doctoral studies. This seminar series showcases the breadth of research covered by the program.  \nFeatured Speaker:\nIsmael Mendoza\, PhD Candidate\, Physics and Scientific Computing\nIsmael is a 4th year Physics PhD student working in the area of cosmology. His research focuses on developing novel statistical and machine learning methods to analyze astronomical images from state-of-the-art telescopes. \nGitHub \nMachine Learning in Cosmology\nIn the upcoming decades\, we will have the opportunity to solve some of the biggest questions about our universe by taking advantage of the huge amounts of data produced by upcoming state-of-the-art cosmological experiments. In order to harness the full statistical power of this data\, we will need to develop scalable and accurate algorithms that can extract its maximal information. Recent advances in Machine Learning have demonstrated its ability to overcome the computational bottlenecks of traditional statistical techniques and even achieve better performance when analyzing cosmology data. In this talk\, I will give a brief overview of the open problems in cosmology\, motivate how Machine Learning (ML) could help us answer these by enabling novel analyses of upcoming cosmological surveys\, and give a specific application of ML enabling probabilistic detection and measurement of galaxy images. \n\n  \nThis event is part of MICDE’s seminar series featuring Ph.D. students in the Scientific Computing program. This series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nQuestions? Email MICDE-events@umich.edu \n 
URL:https://micde.umich.edu/event/phd-seminar-ismael-mendoza-2/
LOCATION:Weiser Hall\, 6th Floor\, 619\, 500 Church Street\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE PhD Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/02/Mendoza.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20230117T140000
DTEND;TZID=America/Detroit:20230117T150000
DTSTAMP:20260626T174734
CREATED:20221222T184418Z
LAST-MODIFIED:20230714T152222Z
UID:10000590-1673964000-1673967600@micde.umich.edu
SUMMARY:MICDE Seminar: Mark Vogelsberger Associate Professor of Physics\, Massachusetts Institute of Technology
DESCRIPTION:WATCH THE RECORDING HERE \nProfessor Vogelsberger grew up in Germany\, and received his undergraduate degree in physics from the University of Mainz and his Ph.D from the University of Munich and the Max Planck Institute for Astrophysics in 2010\, advised by Prof. Simon D.M. White. In 2009 he won the Rudolf Kippenhahn Prize for his thesis work. He was an ITC postdoctoral fellow at the Harvard-Smithsonian Center for Astrophysics from 2009-2012\, and a Hubble fellow from 2012-2013. In 2014\, Dr. Vogelsberger joined the MIT physics faculty as Assistant Professor. In 2016 he won an Alfred P. Sloan Fellowship in Physics. Professor Vogelsberger was promoted to Associate Professor in 2018. Professor Vogelsberger is a theoretical astrophysicist whose research interests broadly cover structure and galaxy formation\, dark matter physics and large-scale hydrodynamical simulations. He makes extensive use of numerical simulations using state-of-the-art high-performance supercomputers around the world. \n  \nSIMULATING EARLY STRUCTURE AND GALAXY FORMATION – THE THESAN PROJECT \nCosmological simulations of galaxy formation have evolved significantly over the last decade. In my talk I will describe recent efforts to model the\nlarge-scale distribution of galaxies with cosmological hydrodynamical simulations. The focus of the talk will be a discussion of our new simulation\ncampaign\, the THESAN project\, to study the epoch of re-ionization and the early Universe. \n  \n\nThe MICDE Winter 2023 Seminar Series is open to all. University of Michigan faculty and students interested in cosmology are encouraged to attend. \nThis seminar is hosted by the Michigan Institute for Computational Discovery & Engineering (MICDE). Prof. Vogelsberger will be hosted by Prof. Monica Valluri\, Research Professor of Astronomy. \nGraduate Certificate in Computational Discovery and Engineering\, and MICDE fellows\, please use this form to record your attendance. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/mark-vogelsberger-associate-professor-of-physics-massachusetts-institute-of-technology-2/
LOCATION:MI
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2022/12/Mark-Vogelsberger.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20230123T150000
DTEND;TZID=America/Detroit:20230123T160000
DTSTAMP:20260626T174734
CREATED:20221222T184418Z
LAST-MODIFIED:20230810T200557Z
UID:10000589-1674486000-1674489600@micde.umich.edu
SUMMARY:MICDE Seminar: Albert Berahas Assistant Professor of Industrial and Operations Engineering at the University of Michigan
DESCRIPTION:Albert S. Berahas is an Assistant Professor in the Industrial and Operations Engineering department at the University of Michigan. Before joining the University of Michigan\, he was a Postdoctoral Research Fellow in the Industrial and Systems Engineering department at Lehigh University working with Professors Katya Scheinberg\, Frank Curtis and Martin Takáč. Prior to that appointment\, he was a Postdoctoral Research Fellow in the Industrial Engineering and Management Sciences department at Northwestern University working with Professor Jorge Nocedal. Berahas completed his PhD studies in the Engineering Sciences and Applied Mathematics (ESAM) department at Northwestern University in 2018\, advised by Professor Jorge Nocedal. He received his undergraduate degree in Operations Research and Industrial Engineering (ORIE) from Cornell University in 2009\, and in 2012 obtained an MS degree in Applied Mathematics from Northwestern University. Berahas’ research broadly focuses on designing\, developing and analyzing algorithms for solving large scale nonlinear optimization problems. Specifically\, he is interested in and has explored several sub-fields of nonlinear optimization such as: (i) general nonlinear optimization algorithms\, (ii) optimization algorithms for machine learning\, (iii) constrained optimization\, (iv) stochastic optimization\, (v) derivative-free optimization\, and (vi) distributed optimization. \n  \nALGORITHMS FOR DETERMINISTICALLY CONSTRAINED STOCHASTIC OPTIMIZATION \nStochastic gradient and related methods for solving stochastic optimization problems have been studied extensively in recent years. It has been shown that such algorithms and much of their convergence and complexity guarantees extend in straightforward ways when one considers problems involving simple constraints\, such as when one can perform projections onto the feasible region of the problem. However\, settings with general nonlinear constraints have received less attention\, and many of the approaches that have been proposed for solving such problems resort to using penalty or (augmented) Lagrangian methods\, which are often not the most effective strategies. In this work\, we propose and analyze stochastic optimization algorithms for deterministically constrained problems based on the sequential quadratic optimization (commonly known as SQP) methodology. We discuss the rationale behind our proposed techniques\, convergence in expectation and complexity guarantees for our algorithms\, and the results of preliminary numerical experiments that we have performed. This is joint work with Raghu Bollapragada\, Frank E. Curtis\, Michael O’Neill\, Daniel P. Robinson\, Jiahao Shi and Baoyu Zhou. \n  \n\nThe MICDE Winter 2023 Seminar Series is open to all. \nThis seminar is hosted by the Michigan Institute for Computational Discovery & Engineering (MICDE). Prof. Berahas will be hosted by Prof. Siqian Shen\, Associate Professor of Industrial and Operations Engineering and Associate Professor of Civil and Environmental Engineering. \nGraduate Certificate in Computational Discovery and Engineering\, and MICDE fellows\, please use this form to record your attendance. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/albert-berahas-assistant-professor-of-industrial-and-operations-engineering-university-of-michigan/
LOCATION:Johnson Rooms\, Lurie Engineering Center\, 3rd Floor LEC 3213ABC\, 1221 Beal Ave.\, Ann Arbor\, MI\, United States
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2022/12/Albert-Berahas.png
GEO:42.2914823;-83.7138452
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20230126T160000
DTEND;TZID=America/Detroit:20230126T163000
DTSTAMP:20260626T174734
CREATED:20230104T090003Z
LAST-MODIFIED:20230809T191357Z
UID:10000588-1674748800-1674750600@micde.umich.edu
SUMMARY:PhD Seminar: Alex Hrabski
DESCRIPTION:The Ph.D. in Scientific Computing program is intended for students who will make extensive use of large-scale computation\, computational methods\, or algorithms for advanced computer architectures in their doctoral studies. This seminar series showcases the breadth of research covered by the program.  \nFeatured Speaker:\nAlex Hrabski\, PhD Candidate\, Naval Architecture & Marine Engineering and Scientific Computing\nAlex is a PhD candidate in the department of Naval Architecture and Marine Engineering\, working in Yulin Pan’s Flow Physics and Engineering Lab to study nonlinear waves. His research seeks to leverage modern computational capabilities to explore wave turbulence theory and the physics that it seeks to describe. \nInvestigations of Wave Turbulence in Bounded Domains\nNonlinear wave systems are ubiquitous in nature\, and when many incoherent dispersive waves interact\, there is the potential for wave turbulence. Just as in hydrodynamic turbulence (HDT)\, systems in wave turbulence exhibit inter-scale energy cascades\, power-law inertial-range spectra\, and even intermittency. Unlike in HDT\, however\, a natural analytical closure for field statistics has been developed: spectral evolution in wave turbulence can be expressed as a Boltzmann-like kinetic equation. In this talk\, we will numerically probe the interplay of nonlinear strength and domain size (critical quantities to the analytical closure) in determining the behaviors of wave turbulence in a model system. Our numerical experiments demonstrate that (a) domain aspect ratio plays a key role in spectral evolution when nonlinearity is weak\, (b) that near-resonant interactions are important for the observation of kinetic behavior\, and (c) evaluations of the energy cascade can be used to investigate the wave turbulence closure. \n\n  \nThis event is part of MICDE’s seminar series featuring Ph.D. students in the Scientific Computing program. This series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nQuestions? Email MICDE-events@umich.edu \n 
URL:https://micde.umich.edu/event/phd-seminar-alex-hrabski/
LOCATION:Weiser Hall\, 6th Floor\, 619\, 500 Church Street\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE PhD Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/02/2023-Winter-Hrabski.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20230126T163000
DTEND;TZID=America/Detroit:20230126T170000
DTSTAMP:20260626T174734
CREATED:20230104T090003Z
LAST-MODIFIED:20230809T191218Z
UID:10000595-1674750600-1674752400@micde.umich.edu
SUMMARY:PhD Seminar: Gurmeet Singh
DESCRIPTION:The Ph.D. in Scientific Computing program is intended for students who will make extensive use of large-scale computation\, computational methods\, or algorithms for advanced computer architectures in their doctoral studies. This seminar series showcases the breadth of research covered by the program.  \nFeatured Speaker:\nGurmeet Singh\, PhD Candidate\, Aerospace Engineering and Scientific Computing\nGurmeet is a Ph.D. candidate in the Department of Aerospace Engineering. His research interests lie in the field of computational solid mechanics focusing on constitutive behavior of materials. He works in Prof. Veera Sundararaghavan’s research group\, and his PhD dissertation focuses on the multiscale modeling of vitrimers and semi-crystalline polymers. \nUnderstanding thermomechanical behavior of vitrimers using molecular dynamics simulations\nVitrimers are a special class of polymers that undergo dynamic cross-linking under thermal stimuli. Their ability to exchange covalent bonds can be harnessed to mitigate damage in a composite or to achieve recyclable composites. This work addresses the primary challenge of modeling dynamic cross-linking reactions in vitrimers during thermomechanical loading. Dynamic bond exchange reaction probability change during heating and its effect on dilatometric and mechanical response are simulated in large scale molecular dynamics (MD) simulations. Healing of damage under thermal cycling is computed with mechanical properties predicted before and after self–healing. \nSubsequently\, the model is used to simulate the creep response of the vitrimer. The results show that the vitrimers demonstrate a secondary creep response on contrary to pure epoxy. The MD simulations are able to probe the interplay between chemical reactions and the loading that results in the healing of the vitrimer under creep. The important feature that explains the difference between epoxies and vitrimers is the orientation of the crosslink bonds with respect to the loading direction. Furthermore\, it is found that the free volume that arises from tensile loads is reduced in vitrimers through dynamic bond rearrangement. The bond orientation\, however\, is preferentially chosen to be normal to the loading axis which ends up decreasing the stiffness along the loading axis\, leading to higher strain as compared to epoxies. Over longer timescales\, the increased strain leads to faster damage localization in tertiary creep where the largest void grows to a critical volume beyond which healing is no longer possible. Thus\, chemistry changes or additives that can prevent the initial realignment of dynamic bonds can be an effective strategy to mitigate creep in vitrimers. \n\n  \nThis event is part of MICDE’s seminar series featuring Ph.D. students in the Scientific Computing program. This series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nQuestions? Email MICDE-events@umich.edu \n 
URL:https://micde.umich.edu/event/phd-seminar-gurmeet-singh-2/
LOCATION:Weiser Hall\, 6th Floor\, 619\, 500 Church Street\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE PhD Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/02/2023-Winter-Singh.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20230216T120000
DTEND;TZID=America/Detroit:20230216T130000
DTSTAMP:20260626T174734
CREATED:20230127T161137Z
LAST-MODIFIED:20230714T152013Z
UID:10000598-1676548800-1676552400@micde.umich.edu
SUMMARY:MICDE Seminar: Mark Pauly Professor of Computer Science\, École Polytechnique Fédérale de Lausanne
DESCRIPTION:WATCH THE RECORDING HERE. \nMark Pauly is a full professor at EPFL\, where he directs the Geometric Computing Laboratory (GCM). Prior to joining EPFL\, he was assistant professor at ETH Zurich\, postdoctoral scholar at Stanford University\, and doctoral student at ETH Zurich. He received the ETH medal for outstanding dissertation in 2003\, was awarded the Eurographics Young Researcher Award in 2006\, an ERC Starting Grant in 2010\, and the Eurographics Outstanding Technical Contributions Award in 2016. He is the co-founder of two EPFL spin-offs\, Faceshift AG and Rayform SA. \n  \nCOMPUTATIONAL INVERSE DESIGN OF DEPLOYABLE STRUCTURES \nResearch at the EPFL Geometric Computing Laboratory (GCM) aims at empowering creators. We develop efficient simulation and optimization algorithms to build computational design methodologies for advanced material systems and digital fabrication technology. Mathematical reasoning\, geometric abstractions\, and powerful numerical methods are key ingredients in our work.\nIn this talk I will show how these tools can be used to solve challenging inverse problems for deployable structures that can transition between multiple geometric states. Several design studies will highlight how the interplay of geometry\, computation\, and digital fabrication technologies facilitates the discovery of new material systems with superior functional performance. Such systems offer a wide variety of potential applications\, for example in industrial and consumer products\, soft robotics\, medical devices\, or architecture. \n\n  \nThe MICDE Winter 2023 Seminar Series is open to all. University of Michigan faculty and students interested in computationally designed advanced material systems and digital fabrication technology are encouraged to attend. \nThis seminar is hosted by the Michigan Institute for Computational Discovery & Engineering (MICDE). Prof. Pauly will be hosted by Prof. Evgueni Filipov\, Assistant Professor of Civil and Environmental Engineering. \nGraduate Certificate in Computational Discovery and Engineering\, and MICDE fellows\, please use this form to record your attendance. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/mark-pauly-professor-at-the-school-of-computer-and-communication-sciences-ecole-polytechnique-federale-de-lausanne/
LOCATION:MI
CATEGORIES:Education,Featured Events,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/01/Mark-Pauly.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20230223T160000
DTEND;TZID=America/Detroit:20230223T163000
DTSTAMP:20260626T174734
CREATED:20230123T090003Z
LAST-MODIFIED:20230809T191036Z
UID:10000599-1677168000-1677169800@micde.umich.edu
SUMMARY:PhD Seminar: Pei-Hsun Huang
DESCRIPTION:The Ph.D. in Scientific Computing program is intended for students who will make extensive use of large-scale computation\, computational methods\, or algorithms for advanced computer architectures in their doctoral studies. This seminar series showcases the breadth of research covered by the program.  \nFeatured Speaker:\nPei-Hsun Huang\, PhD Candidate\, Nuclear Engineering & Radiological Sciences and Scientific Computing\nPei-Hsun is a PhD student in Nuclear Engineering & Radiological Sciences working with Professor Annalisa Manera in the Experimental and Computational Multiphase Flow Laboratory. His project involves high-temperature two-phase heat pipe technologies. \nSimulation for the Design of Sodium Heat Pipes Bundle Test Facility for the Application of Microreactors\nThe 20 MW Special Purpose Reactor (SPR) is a heat pipe cooled microreactor that designed for electricity production in remote locations where reliable power grids are not always available. The key to SPR is the alkali metal heat pipes\, which offer entirely passive operation capacity with high mobility. Prior to deployment\, safety analysis with postulated accident scenarios is required for the licensing of SPR. To this regard\, a sufficiently accurate model is crucial to predict the behavior of heat pipes\, and high-resolution data is needed for the safety analysis of SPR. However\, the current existing heat pipe models are either oversimplified or unpractical expensive in view of the difficulty of the simulation with the wick structure and two-phase flow in the heat pipe. Therefore\, high fidelity experimental data is required for model verification in the high temperature heat pipe bundle system. The Michigan Sodium Heat Pipe bundle test facility which serves as a scale-down test facility using ten sodium heat pipes with a triangular array\, was utilized to verify the model for the licensing of SPR. In the talk\, the feasibility analysis using Computer Aided Engineering and Computational Fluid Dynamics for the design of the test facility was addressed. \n\n  \nThis event is part of MICDE’s seminar series featuring Ph.D. students in the Scientific Computing program. This series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nQuestions? Email MICDE-events@umich.edu \n 
URL:https://micde.umich.edu/event/phd-seminar-pei-hsun-huang-2/
LOCATION:Rackham Building\, Earl Lewis Room\, 3rd Floor East\, 915 E. Washington St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE PhD Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/02/2023-Winter-Huang.png
GEO:42.2807892;-83.7381556
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20230223T163000
DTEND;TZID=America/Detroit:20230223T170000
DTSTAMP:20260626T174734
CREATED:20230123T090003Z
LAST-MODIFIED:20230809T190922Z
UID:10000591-1677169800-1677171600@micde.umich.edu
SUMMARY:PhD Seminar: Shirlyn Wang
DESCRIPTION:The Ph.D. in Scientific Computing program is intended for students who will make extensive use of large-scale computation\, computational methods\, or algorithms for advanced computer architectures in their doctoral studies. This seminar series showcases the breadth of research covered by the program.  \nFeatured Speaker:\nShirlyn Wang\, PhD Candidate\, Applied & Interdisciplinary Mathematics and Scientific Computing\nShirlyn Wang is a Ph.D candidate in Applied and Interdisciplinary Mathematics. Her research interest is in mathematical oncology\, the study of cancer initiation\, progression\, and therapy through data-driven mathematical models and simulations.  \nModeling CTL-mediated Tumor Cell Death Mechanisms and the Activity of Immune Checkpoints in Immunotherapy\nImmunotherapy has dramatically transformed the cancer treatment landscape. Of the variety of types of immunotherapies available\, immune checkpoint inhibitors (ICIs)\, which block inhibitory signals from tumor cells and reinvigorate killing activities of immune cells\, have gained the spotlight. Although ICIs have shown promising results for some patients\, the low response rates in many cancers highlight the challenges of using immune checkpoint blockade as an effective treatment. Cytotoxic T lymphocytes (CTLs) execute their cell-killing function via two distinct mechanisms. The first process is fast-acting and perforin/granzyme-mediated\, and the second is a slower\, Fas ligand (FasL)-driven killing mechanism. There is also evidence suggesting that the preferred killing mechanism by CTLs depends on the antigenicity of tumor cells. To determine the key factors affecting responses to checkpoint blockade therapy\, we constructed an ordinary differential equation model describing in vivo tumor-immune dynamics in the presence of active or blocked PD-1/PDL1 immune checkpoint. Specifically\, we analyzed which aspects of the tumor-immune landscape affect the response to ICIs with endpoints of tumor size and composition in the short and long term. By generating a virtual cohort with heterogeneous tumor and immune attributes\, we also simulated the therapeutic outcomes of immune checkpoint blockade in a largely diverse population. In this way\, we identified key tumor and immune characteristics that are associated with tumor elimination\, dormancy and escape. This talk will also shed light on which fraction of a population potentially responds well to ICIs and ways to enhance therapeutic outcomes with combination therapy. \n\n  \nThis event is part of MICDE’s seminar series featuring Ph.D. students in the Scientific Computing program. This series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nQuestions? Email MICDE-events@umich.edu \n 
URL:https://micde.umich.edu/event/phd-seminar-shirlyn-wang/
LOCATION:Rackham Building\, Earl Lewis Room\, 3rd Floor East\, 915 E. Washington St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE PhD Seminar Series,Seminar
GEO:42.2807892;-83.7381556
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Rackham Building Earl Lewis Room 3rd Floor East 915 E. Washington St. Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=915 E. Washington St.:geo:-83.7381556,42.2807892
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20230302T153000
DTEND;TZID=America/Detroit:20230302T163000
DTSTAMP:20260626T174734
CREATED:20230905T171445Z
LAST-MODIFIED:20230905T171445Z
UID:10000017-1677771000-1677774600@micde.umich.edu
SUMMARY:MICDE Seminar: Daniele Schiavazzi\, Associate Professor of Applied and Computational Mathematics and Statistics\, University of Notre Dame
DESCRIPTION:Daniele Schiavazzi is an Associate Professor in the Department of Applied and Computational Mathematics and Statistics at the University of Notre Dame. He graduated with honors and received a Ph.D. in Applied Mathematics from Universita’ degli Studi di Padova in Italy. He held postdoctoral appointments at the University of California\, San Diego and Stanford University. He is the recipient of a CAREER Award from the National Science Foundation\, a Young Faculty Award from DARPA and a Postdoctoral Fellowship from the American Heart Association. His research interests include uncertainty quantification\, cardiovascular simulation\, multi-resolution and multi-fidelity approximation\, model-based inference and inverse problems in medical imaging. \nTalk Title: NEW PARADIGMS FOR ENSEMBLE MODELING\, UNCERTAINTY QUANTIFICATION AND INFERENCE IN CARDIOVASCULAR SIMULATION \nAbstract: \nComputer simulations are increasingly used to complement clinical decision making in the diagnosis and treatment of cardiovascular disease. High-fidelity cardiovascular models are traditionally deterministic and solved using implicit time integration\, without directly accounting for uncertainty and variability in the underlying input processes\, for example boundary conditions\, material properties or segmented model anatomy. I will discuss an alternative simulation paradigm based on the explicit integration in time of an ensemble of model realizations\, running on multiple GPUs. Additionally\, I will present some results on the acceleration of traditional numerical solvers through data-driven methods based on deep neural networks\, focusing on synchronization-avoiding algorithms for distributed finite element solvers. I will finally discuss recently proposed approaches for multi-fidelity uncertainty propagation and variational inference\, combining high-fidelity cardiovascular models with their low-fidelity approximation or neural network surrogate. \n  \n\n  \nThe MICDE Fall 2022 Seminar Series is open to all. \nThis seminar is hosted by the Michigan Institute for Computational Discovery & Engineering (MICDE). Prof. Schiavazzi will be hosted by Prof. Alex Gorodetsky\, Assistant Professor of Aerospace Engineering. \nThis is an in-person event\, Zoom link will only be provided upon request. This seminar will not be recorded! \nGraduate Certificate in Computational Discovery and Engineering\, and MICDE fellows\, please use this form to record your attendance. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-daniele-schiavazzi-associate-professor-of-applied-and-computational-mathematics-and-statistics-university-of-notre-dame/
LOCATION:1014 H. H. Dow\, 2300 Hayward St\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
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