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DTSTART;TZID=America/Detroit:20220225T150000
DTEND;TZID=America/Detroit:20220225T160000
DTSTAMP:20260603T200736
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SUMMARY:MICDE / AIM Seminar: Blaise Bourdin\, PhD\, Professor of Mathematics & Statistics\, McMaster University
DESCRIPTION:THE SEMINAR WILL ONLY BE OFFERED ONLINE!\nWATCH THE RECORDING HERE. \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/
LOCATION:Zoom Event\, MI\, United States
CATEGORIES:Featured Events,Seminar
ATTACH;FMTTYPE=image/jpeg:https://micde.umich.edu/wp-content/uploads/2023/02/Blaise-Bourdin.jpeg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20211208T150000
DTEND;TZID=America/Detroit:20211208T160000
DTSTAMP:20260603T200736
CREATED:20210923T032752Z
LAST-MODIFIED:20230713T171305Z
UID:10000526-1638975600-1638979200@micde.umich.edu
SUMMARY:MICDE Seminar: Sarah Hormozi\, Associate Professor\, Cornell University
DESCRIPTION:WATCH THE RECORDING HERE. \n\nBio: Sarah Hormozi is an associate professor of Chemical and Biomolecular Engineering at Cornell University. Her expertise lies in complex fluid mechanics\, rheology\, and soft matter physics. Her research has been recognized by a number of awards\, including the National Science Foundation CAREER award and the ACS Petroleum Research Fund Doctoral New Investigator Award. She also serves on the advisory boards of Journals of Physical Review Fluids\, Non-Newtonian Fluid Mechanics\, The American Institute of Chemical Engineers\, and Physics of Fluids. \nSlurries of complex fluids\nSuspensions of non-Brownian particles in viscous fluids\, for which thermal fluctuations are negligible\, are relevant in industrial processes (e.g. waste disposal\, concrete\, drilling muds\, metalworking chip transport\, and food processing) and in natural phenomena (e.g. flows of slurries\, debris\, and lava). It is also relevant to mention that some biological and smart materials can be designed from various suspensions\, drawing attention to applications in physiology\, bio\nlocomotion\, shock absorbers\, and beyond. This countless number of suspensions has a wide range of nonlinear rheological behaviors\, such as shear thinning\, shear thickening\, shear banding\, yield stress\, and finite normal stress differences even when inertia is negligible.\nFor applications enumerated above\, even small increases in efficiency when processing slurries of complex fluids could make significant positive economic and environmental impacts. Obviously\, a thorough understanding of the rheology and fluid mechanics of these materials in natural and industrial settings is essential to improving the efficiency of production. However\, this is extremely challenging due to the complex rheology of the suspending fluids\, the interaction of fluid and particle phases\, and multiple-body and short-range interactions of particles. My presentation will introduce an array of experimental and modeling techniques that my research team uses to investigate the rheological properties and fluid dynamical behavior of complex suspensions. The goal is to establish a continuum framework and refine it through a series of microstructure investigations. I will discuss how our recent results can be used to address and resolve some of the industrial issues. Finally\, open questions will be disclosed\, which must be answered to build a firm foundation for a long-term contribution to the area of complex suspensions. \n\nThe MICDE Fall 2021 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 hosted by the Michigan Institute for Computational Discovery and Engineering (MICDE) at the University of Michigan. Dr. Hormozi will be hosted by Dr. Mariana Carrasco-Teja\, MICDE Associate Director and Assistant Research Scientist. Questions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-sarah-hormozi-ph-d-associate-professor-smith-school-of-chemical-and-biomolecular-engineering-cornell-university/
LOCATION:Zoom Event\, MI\, United States
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2021/09/Sarah-Hormozi.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20211203T150000
DTEND;TZID=America/Detroit:20211203T160000
DTSTAMP:20260603T200736
CREATED:20210923T031753Z
LAST-MODIFIED:20230713T171452Z
UID:10000525-1638543600-1638547200@micde.umich.edu
SUMMARY:MICDE / AIM: Youngsoo Choi\, Research Scientist\, Center for Applied Scientific Computing\, Lawrence Livermore National Laboratory
DESCRIPTION:Zoom link | Meeting ID: 964 5038 3843 | Psswd: 010182 \n\nBio: Youngsoo is a computational math scientist in CASC under Computing directorate at LLNL. He is currently leading data-driven reduced order model development team for various physical simulations\, with whom he developed the open source codes\, libROM (https://www.librom.net) and LaghosROM (https://github.com/CEED/Laghos/tree/rom/rom). libROM is a library for reduced order models and LaghosROM implements reduced order models for Lagrangian hydrodynamics (https://authors.elsevier.com/c/1e3CuAQEIviQh). He has earned his undergraduate degree for Civil and Environmental Engineering from Cornell University with applied mathematics as minor and his PhD degree for Computational and Mathematical Engineering from Stanford University. He was a postdoc in Sandia National Laboratory and Stanford University prior to joining LLNL in 2017. \nPhysics-constrained data-driven methods for accurately accelerating simulations\nA data-driven model can be built to accurately accelerate computationally expensive physical simulations\, which is essential in multi-query problems\, such as inverse problem\, uncertainty quantification\, design optimization\, and optimal control. In this talk\, two types of data-driven model order reduction techniques will be discussed\, i.e.\, the black-box approach that incorporates only data and the physics-constrained approach that incorporates the first principle as well as data. The advantages and disadvantages of each method will be discussed. Several recent developments of generalizable and robust data-driven physics-constrained reduced order models will be demonstrated for various physical simulations as well. For example\, a hyper-reduced time-windowing reduced order model overcomes the difficulty of advection-dominated shock propagation phenomenon\, achieving a speed-up of O(20~100) with a relative error much less than 1% for Lagrangian hydrodynamics problems\, such as 3D Sedov blast problem\, 3D triple point problem\, 3D Taylor–Green vortex problem\, 2D Gresho vortex problem\, and 2D Rayleigh–Taylor instability problem. The nonlinear manifold reduced order model also overcomes the challenges posed by the problems with Kolmogorov’s width decaying slowly by representing the solution field with a compact neural network decoder\, i.e.\, nonlinear manifold. The space–time reduced order model accelerates a large-scale particle Boltzmann transport simulation by a factor of 2\,700 with a relative error less than 1%. Furthermore\, successful application of these reduced order models for mate-material lattice–structure design optimization problems will be presented. Finally\, the library for reduced order models\, i.e.\, libROM (https://www.librom.net)\, and its webpage and several YouTube tutorial videos will be introduced\, which is useful for education as well as research purpose. \n\n  \nThe MICDE Fall 2021 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 and Interdisciplinary Mathematics program at the University of Michigan. Dr. Choi will be hosted by Dr. Jesse Capecelatro\, Assistant Professor of Mechanical Engineering and Aerospace Engineering. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-aim-youngsoo-choi-llnl/
LOCATION:Zoom Event\, MI\, United States
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2021/09/Youngsoo-Choi.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20211104T120000
DTEND;TZID=America/Detroit:20211104T130000
DTSTAMP:20260603T200736
CREATED:20210923T030754Z
LAST-MODIFIED:20230713T171653Z
UID:10000524-1636027200-1636030800@micde.umich.edu
SUMMARY:MICDE / SPH: Laura Matrajt\, Staff Scientist\, Vaccine and Infectious Disease Division\, Fred Hutch
DESCRIPTION:Bio: Dr. Matrajt is a Staff Scientist in the Vaccine and Infectious Disease Division at the Fred Hutch research center in Seattle. She is an applied mathematician passionate about utilizing quantitative tools (mathematical and computer models\, statistics\, optimization theory) to understand complex biological processes. Her research lies at the interface of applied mathematics\, biology and public health policy. Dr. Matrajt uses a wide range of tools from applied mathematics including dynamical systems\, differential equations\, stochastic processes\, operations research and optimization theory to forward our understanding of infectious disease dynamics. \nDr. Matrajt was born and raised in Mexico City\, Mexico. She attended UNAM\, where she studied Mathematics as an undergraduate. Dr. Matrajt moved to Seattle\, WA\, where she completed a PhD in the Applied Mathematics Department at the University of Washington\, where she graduated in 2011. \nOptimizing COVID-19 vaccine allocation\nVaccines have proven to be our best tool to control the current COVID-19 pandemic. However\, due to limited vaccine supply\, vaccine prioritization has been\, and continues to be\, unavoidable. In this talk\, I will discuss two projects that used mathematical modeling combined with a fast optimization algorithm to determine the optimal use of these precious resources. In the first one\, we determined who should be vaccinated first\, and showed that the optimal use of COVID-19 vaccine depends on vaccine efficacy and vaccination coverage. In the second project we considered who should be vaccinated and how many doses they should get\, and found that optimal allocation strategies with one or two doses of vaccine depend on the efficacy after the first dose\, the background viral transmission and the amount of vaccine available. \n\nWATCH THE RECORDING HERE. \n\nThe MICDE Fall 2021 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 department of Epidemiology within the School of Public Health at the University of Michigan. Dr. Matrajt will be hosted by Dr. Rafael Meza\, Professor of Epidemiology and Global Public Health. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-sph-laura-matrajt-ph-d-scientist-vaccine-and-infectious-disease-division-fred-hutchinson-cancer-research-center/
LOCATION:Zoom Event\, MI\, United States
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2021/09/Laura-Matrajt.png
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20211028T160000
DTEND;TZID=America/Detroit:20211028T170000
DTSTAMP:20260603T200736
CREATED:20211021T140003Z
LAST-MODIFIED:20230217T195900Z
UID:10000547-1635436800-1635440400@micde.umich.edu
SUMMARY:PhD Seminar: Christiana Mavroyiakoumou and Vishwas Goel
DESCRIPTION:Register via Zoom to immediately receive login information. Note: You may register and join after the event has started. \n\nThe 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:\n\nCHRISTIANA MAVROYIAKOUMOU\, PhD Candidate\, Applied and Interdisciplinary Mathematics\, and Scientific Computing\nBio: Christiana Mavroyiakoumou is a 5th year PhD candidate in Applied and Interdisciplinary Mathematics\, working on extensible membrane flutter in inviscid flow using theoretical and computational tools. Her advisor is Professor Silas Alben at the Department of Mathematics. \nDYNAMICS OF TETHERED MEMBRANES IN INVISCID FLOW: We study the dynamics of membranes (with stretching stiffness but zero bending stiffness) that shed vortex wakes in inviscid flows. Previous studies have focused on membranes with fixed ends\, where only static deflection occurs. Here we consider instead membranes held by tethers with hinged ends\, and find that a variety of unsteady large-amplitude motions\, both periodic and chaotic\, may occur. We characterize the dynamics over ranges of the key parameters: membrane mass density\, stretching stiffness\, pretension\, and tether length. We find the region of instability and the small-amplitude behavior in a linearized model by solving a nonlinear eigenvalue problem. We also derive asymptotic scaling laws by considering a simplified model: an infinite periodic membrane. We find qualitative similarities among all three models in terms of the oscillation frequencies and membrane shapes at small and large values of the parameters. \nVISHWAS GOEL\, PhD Candidate\, MATERIALS SCIENCE AND ENGINEERING\, and Scientific Computing\nBio: I am a 4th Ph.D. student in the Department of Materials Science and Engineering. My research is focused on multi-scale modeling of electrochemical processes such as energy storage\, energy conversion\, and corrosion. \nMODELING BASED OPTIMIZATION OF HOLE ARCHITECTURE FOR ENABLING FAST CHARGING IN LI-ION BATTERIES: For the widespread adoption of electric vehicles\, we need Li-ion batteries (LIBs) that are energy and power dense. However\, we cannot realize both these properties even in state-of-the-art commercial Li-ion batteries. This inability is caused by the electrode design used in LIBs. In such a design\, to increase the energy density\, one needs to increase the active material loading (either in terms of active material mass fraction or the electrode thickness). However\, such a design proves to be highly tortuous for the transport of Li-ions in the electrolyte\, which causes the electrode to exhibit poor fast charging performance. \nIn our previous work [1]\, we demonstrated that the rate performance of the energy-dense electrodes can be improved by employing 3D architectures such as highly ordered laser-patterned electrodes (HOLE). The architecture alleviates the electrolyte mass transport limitations by providing rapid mass transport via laser-ablated channels through the electrode thickness. In this study\, we investigate how the geometric parameters of the HOLE design\, such as inter-channel spacing and channel radius\, affect the fast-charging performance of the HOLE graphite anodes with > 3 mAh/cm2 loading. We conduct this analysis using a fully parameterized continuum scale model based on the porous electrode theory. Our results show that for a constant volume retained (after the laser ablation)\, the smaller and closer channels exhibit better 4C charging performance than the larger and farther channels. \n1. K.-H. Chen et al.\, J. Power Sources\, 471\, 228475 (2020) doi.org/10.1016/j.jpowsour.2020.228475 \n\n  \nThis event is part of MICDE’s Fall 2021 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-christiana-mavroyiakoumou-and-vishwas-goel-2/
LOCATION:Zoom Event\, MI\, United States
CATEGORIES:Featured Events,Seminar
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210604T100000
DTEND;TZID=America/Detroit:20210604T110000
DTSTAMP:20260603T200736
CREATED:20230905T171444Z
LAST-MODIFIED:20230905T171444Z
UID:10000483-1622800800-1622804400@micde.umich.edu
SUMMARY:Marc Henry de Frahan Webinar
DESCRIPTION:Title: Leveraging modeling hierarchies in the Exascale era: applications to combustion technologies \nAbstract: As we approach the confluence of widespread use of machine learning techniques and simulations running at exascale\, several important challenges will need to be addressed. In this talk\, we explore some of these challenges\, with a specific focus on combustion applications. We discuss a combustion simulation code\, PeleC\, and its performance characteristics on the fastest supercomputers available today. We look at leveraging the resulting high-fidelity simulations to construct data-driven models for lower-fidelity simulations. We then examine how to adapt reinforcement learning methods to explore a modeling hierarchy and determine adequate control strategies for combustion technologies. \nBio: Marc Henry de Frahan is a computational scientist at the National Renewable Energy Laboratory\, where he works on improving next-generation wind and combustion processes. As part of the Exascale Computing Project\, Marc develops high-fidelity turbulence models to enhance simulation accuracy and efficient numerical algorithms for future high-performance computing hardware architectures. In addition to traditional physics-based modeling\, he is integrating deep neural networks into modeling and reinforcement learning into advanced control strategies. Marc obtained his PhD in Mechanical Engineering in 2016 from the University of Michigan. \n\nZoom information to connect: \nLink: https://umich.zoom.us/j/98133041706 \nPasscode: 762808
URL:https://micde.umich.edu/event/marc-henry-de-frahan-webinar/
LOCATION:Zoom Event\, MI\, United States
CATEGORIES:Featured Events,Seminar,Webinar
ATTACH;FMTTYPE=image/jpeg:https://micde.umich.edu/wp-content/uploads/2023/02/marc-henry-de-frahan.jpeg
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200602T150000
DTEND;TZID=America/Detroit:20200602T160000
DTSTAMP:20260603T200736
CREATED:20230905T171345Z
LAST-MODIFIED:20230905T171345Z
UID:10000605-1591110000-1591113600@micde.umich.edu
SUMMARY:MICDE Webinar Series: Gabriel Ehrlich\, Director\, Research Seminar in Quantitative Economics\, University of Michigan
DESCRIPTION:Bio: Dr. Gabriel Ehrlich is the Director of the Research Seminar in Quantitative Economics (RSQE)\, and an Assistant Research Scientist in the department of Economics at the University of Michigan. Prior to joining RSQE\, he worked in the Financial Analysis Division at the Congressional Budget Office (CBO)\, where he forecast interest rates and conducted analysis on monetary policy and the mortgage finance system. His academic research focuses on several areas of housing and land economics as well as the effects of wage rigidity on labor market outcomes. \nMODELING THE ECONOMIC OUTLOOK IN THE TIME OF COVID-19\nWe will present the Research Seminar in Quantitative Economics’ (RSQE’s) forecast for the national and Michigan economies from 2020 to 2022. We will discuss the incoming data during the COVID-19 pandemic\, the near-term economic damage\, and the prospects for economic recovery. RSQE is the world’s oldest continuously operating economic forecasting unit and is home to the “Michigan Model” of the U.S. economy.
URL:https://micde.umich.edu/event/micde-webinar-series-gabriel-ehrlich-director-research-seminar-in-quantitative-economics-university-of-michigan/
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/2023/07/Gabriel-Ehrlich.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200326T160000
DTEND;TZID=America/Detroit:20200326T170000
DTSTAMP:20260603T200736
CREATED:20230905T171342Z
LAST-MODIFIED:20230905T171342Z
UID:10000352-1585238400-1585242000@micde.umich.edu
SUMMARY:POSTPONED - MICDE/EEB Seminar: Yun Song\, Professor\, Computer Science and Statistics\, University of California\, Berkeley
DESCRIPTION:Bio: Yun S. Song is a professor of EECS and Statistics. He received the BS degrees in mathematics and physics from MIT\, and a PhD in physics from Stanford University. After his PhD\, he spent a year at the Mathematical Institute at the University of Oxford\, where he decided to change fields. He became a postdoctoral researcher in the Department of Statistics at Oxford\, and started doing research in computational biology and mathematical population genetics. From 2004 to 2007\, he was a postdoctoral researcher at UC Davis in the Department of Computer Science\, and the Section of Evolution and Ecology. \nThe key parameters that govern translation efficiency\nTranslation of mRNA into protein is a fundamental biological process mediated by the flow of ribosomes on mRNA transcripts.  With multiple factors that can potentially affect its efficiency\, this transport process is highly complex and heterogeneous: different mRNAs can have different initiation rates\, local elongation rates can vary substantially along the mRNA\, and multiple ribosomes can simultaneously translate the same mRNA\, potentially leading to interference.  In this talk\, I will present new theoretical results on a probabilistic model of mRNA translation which allowed us to identify the key parameters that govern the overall rate of protein synthesis\, sensitivity to initiation rate changes\, and efficiency of ribosome usage.  I will then describe our ongoing study\, which combines in vitro translation experiments with mathematical modeling\, to elucidate the role of the 5′ UTR (particularly uAUGs and uORFs) in regulating translation initiation in eukaryotes.
URL:https://micde.umich.edu/event/micde-seminar-yun-song/
LOCATION:MI
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:20200320T150000
DTEND;TZID=America/Detroit:20200320T160000
DTSTAMP:20260603T200736
CREATED:20230905T171343Z
LAST-MODIFIED:20230905T171343Z
UID:10000351-1584716400-1584720000@micde.umich.edu
SUMMARY:POSTPONED - MICDE/AIM Seminar: John Harlim\, Professor\, Mathematics and Meteorology\, Penn State University
DESCRIPTION:Bio: John Harlim is a Professor in the Department of Mathematics and the Department of Meteorology and Atmospheric Sciences. Harlim received his undergraduate degree in Mathematics from the Universitas Padjadaran (Indonesia)\, a master’s from the University of Guelph in Applied Mathematics\, and a PhD in Applied Mathematics and Scientific Computation from the University of Maryland at College Park. His research interests in applied mathematics include parameter estimation\, machine learning\, manifold learning\, operator estimation\, data assimilation. \n Learning Missing Dynamics through Data\nThe recent success of machine learning has drawn tremendous interest in applied mathematics and scientific computations. In this talk\, I would address the classical closure problem that is also known as model error\, missing dynamics\, or reduced-order-modeling in various community. Particularly\, I will discuss a general framework to compensate for the model error. The proposed framework reformulates the model error problem into a supervised learning task to approximate a very high-dimensional target function involving the Mori-Zwanzig representation of projected dynamical systems. Connection to traditional parametric approaches will be clarified as specifying the appropriate hypothesis space for the target function. Theoretical convergence and numerical demonstration on modeling problems arising from PDE’s will be discussed.
URL:https://micde.umich.edu/event/micde-seminar-john-harlim-psu/
LOCATION:MI
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2020/03/John-Harlim.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200228T150000
DTEND;TZID=America/Detroit:20200228T160000
DTSTAMP:20260603T200736
CREATED:20230905T171341Z
LAST-MODIFIED:20230905T171341Z
UID:10000333-1582902000-1582905600@micde.umich.edu
SUMMARY:MICDE Seminar: Sarah D. Olson\, Associate Professor\, Mathematical Sciences\, Worcester Polytechnic Institute
DESCRIPTION:Bio:Sarah Olson is an Associate Professor in the Department of Mathematical Sciences at Worcester Polytechnic Institute. Olson received her undergraduate degrees in Mathematics and Biology from Providence College\, a master’s from the University of Rhode Island in Mathematics\, and a PhD in Biomathematics from North Carolina State University. She has worked in the general areas of fluid dynamics\, scientific computing\, and mathematical biology. \nSperm Navigation in Complex Environments\nMicroorganisms can swim in a variety of environments\, interacting with chemicals and other proteins in the fluid. In this talk\, we will highlight recent computational methods and results for swimming efficiency and hydrodynamic interactions of swimmers in different fluid environments. Sperm are modeled via a centerline representation where forces are solved for using elastic rod theory. The method of regularized Stokeslets is used to solve the fluid-structure interaction where emergent swimming speeds can be compared to asymptotic analysis. In the case of fluids with extra proteins or cells that may act as friction\, swimming speeds may be enhanced and attraction may not occur. \nThis seminar is co-sponsored by the Applied & Interdisciplinary Mathematics program. Prof. Olson is being hosted by Prof. Alben (MATH). If you would like to meet with her during her visit\, please send an email to micde-events@umich.edu. If you are an MICDE student or a MATH student and you would like to join Professor Olson for lunch during her visit\, please RVSP by Feb. 27. 
URL:https://micde.umich.edu/event/micde-seminar-sarah-d-olson-wpi/
LOCATION:1084 East Hall\, 530 Church St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2020/01/Sarah-Olson.png
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200225T113000
DTEND;TZID=America/Detroit:20200225T130000
DTSTAMP:20260603T200736
CREATED:20230905T171342Z
LAST-MODIFIED:20230905T171342Z
UID:10000354-1582630200-1582635600@micde.umich.edu
SUMMARY:Complex Systems Seminar: David Goluskin\, Assistant Professor\, Mathematics and Statistics\, University of Victoria
DESCRIPTION:Bio: David Goluskin is an Assistant Professor in the Department of Mathematics and Statistics at the University of Victoria. Goluskin received his undergraduate degrees from the University of Colorado\, Boulder\, a master’s from Columbia University\, and a PhD in Applied Mathematics from Columbia University. His research is in the broad area of applied nonlinear dynamics and incorporates both computation and analysis. Much of Professor Goluskin’s work concerns fluid dynamics\, but he also studies simpler ordinary and partial differential equations. \nStudying dynamics using computational polynomial optimization\nMany complex systems are governed by nonlinear ODEs or PDEs that cannot be solved exactly. Various properties of such solutions can be inferred by constructing auxiliary functions that satisfying suitable inequalities. The most familiar example is the construction of Lyapunov functions to infer stability of particular states\, but similar approaches can produce many other types of mathematical statements\, including for systems with chaotic or otherwise complicated behavior. Such statements include estimates of time-averaged quantities and extreme transient behavior\, approximation of nonlinear stability properties\, and design of controls. In many cases\, the search for the auxiliary function that implies the strongest mathematical statement can be posed as a convex optimization problem. Such problems can be studied analytically or computationally\, but in most cases computation is needed to find solutions that are close to optimal. Of particular use are computational methods of polynomial optimization\, where the optimization constraints include polynomial inequalities. This talk will provide an overview of different ways in which auxiliary functions can be used to study nonlinear ODEs and PDEs\, as well as how polynomial optimization can be used to implement these methods computationally. Methods will be illustrated using applications to various complex systems.
URL:https://micde.umich.edu/event/complex-systems-seminar-david-goluskin-assistant-professor-mathematics-and-statistics-university-of-victoria/
LOCATION:Weiser Hall\, Room 747\, 500 Church St\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,Seminar
ATTACH;FMTTYPE=image/jpeg:https://micde.umich.edu/wp-content/uploads/2023/02/event_72568_original-1-e1582558578476.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200221T150000
DTEND;TZID=America/Detroit:20200221T160000
DTSTAMP:20260603T200736
CREATED:20230905T171342Z
LAST-MODIFIED:20230905T171342Z
UID:10000332-1582297200-1582300800@micde.umich.edu
SUMMARY:MICDE Seminar: Osman Basaran\, Professor\, Chemical Engineering\, Purdue University
DESCRIPTION:Bio: Professor Osman Basaran is a Burton and Kathryn Gedge Professor of Chemical Engineering at Purdue University. He received his undergraduate degree at Massachusetts Institute of Technology and a PhD from the University of Minnesota. Prof. Basaran’s research involves the use of a balanced approach based on computation\, theory\, and experiment to attack a number of fundamental issues that lie at the heart of such practical problems. \nHigh-accuracy simulation of free surface flows near finite-time pinch-off and coalescence singularities\nMotivated by applications such as ink jet printing\, drop-by-drop manufacturing\, sprays\, emulsions\, and chemical separations\, we study the dynamics of breakup and coalescence through high-accuracy simulation\, theory\, and experiment.  In this talk\, I will highlight our group’s work on accurately capturing the fluid dynamics that takes place in the vicinity of finite-time singularities. The free surface flow algorithms and solvers that we develop and use rely on a sharp interface representation of phase boundaries.  In the simulations\, we are able to analyze situations that involve disparate length scales that differ by up to seven orders of magnitude (commercial codes can handle about 2-3 orders and custom codes can capture at most 3-4 orders of magnitude disparity in length scales). The primary focus of the talk will be on simulations of the breakup of surfactant-covered filaments where I will pay special attention to the pinch-off singularity.  I will also summarize some of our recent work on the pre- and post-coalescence singularities that arise when two drops or bubbles are driven together and made to merge into one.  \nThis seminar is co-sponsored by the Applied & Interdisciplinary Mathematics program. Prof. Basaran is being hosted by Prof. Deegan (Physics). If you would like to meet with Prof. Basaran during his visit\, please send an email to micde-events@umich.edu. If you are an MICDE student or an AIM student and you’re interested in having lunch with Prof. Basaran during his visit\, please RSVP by Thursday\, February 20\, 2020.
URL:https://micde.umich.edu/event/micde-seminar-osman-basaran-purdue/
LOCATION:1084 East Hall\, 530 Church 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:20200131T153000
DTEND;TZID=America/Detroit:20200131T163000
DTSTAMP:20260603T200736
CREATED:20230905T171340Z
LAST-MODIFIED:20230905T171340Z
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SUMMARY:MICDE Seminar: Amir Salaree\, Postdoctoral Fellow\, Earth and Environmental Sciences\, University of Michigan
DESCRIPTION:Due to unforeseen circumstances the originally scheduled talk by Professor Brandon Johnson has been cancelled and replaced with the following seminar. \nTheoretical and Computational Contributions to the Modeling of Global Tsunamis\nThe distribution of tsunami amplitudes in the open ocean is controlled by source mechanism as well as bathymetry geometry and resolution\, with the latter controlling far-field tsunami features. However\, large detailed bathymetry grids result in long computer simulation times for tsunamis. It is therefore of interest to investigate the amount of physical detail in bathymetric grids that control the most important features in tsunami amplitudes\, to assess what constitutes sufficient level for grids in numerical simulations. By decomposing the Pacific bathymetry using a spherical harmonics approach one can create “smoothed” versions of the original field. Using these simplified bathymetries to simulate tsunamis from potential ruptures around the Pacific\, we can see that for large megathrust events (M0=1029 dyn-cm)\, only a resolution of ~1000 km (equivalent to l=40)\, or ~1% surface smoothness of the Pacific is needed in order to reproduce the main components of the true distribution of tsunami amplitudes. This would result in simpler simulations\, and faster computations in the context of tsunami warning algorithms. \nIn a separate context\, an overview of tsunami studies and a report on a study of a meteotsunami are presented. These scenarios are evidence for the fact that tsunami studies are interdisciplinary fields of research that require coordinated efforts by investigators from various backgrounds. \nMICDE is co-hosting this seminar with the Earth and Environmental Sciences department. 
URL:https://micde.umich.edu/event/micde-seminar-brandon-johnson-purdue/
LOCATION:RM1528\, 1100 North University Building
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2020/01/Amir-Salaree.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200124T130000
DTEND;TZID=America/Detroit:20200124T140000
DTSTAMP:20260603T200736
CREATED:20230905T171341Z
LAST-MODIFIED:20230905T171341Z
UID:10000312-1579870800-1579874400@micde.umich.edu
SUMMARY:MICDE Seminar: Andrew Wetzel\, Assistant Professor\, Physics\, University of California\, Davis
DESCRIPTION:Bio: Professor Wetzel is an assistant professor in the physics department and in the astrophysics and cosmology group at the University of California\, Davis. He is a theoretical/computational astrophysicist and cosmologist. Using the world’s most powerful supercomputers\, he generates cosmological simulations to model the formation of cosmic structures\, including galaxies and their stars. He uses these simulations as theoretical laboratories to develop and test models of galaxy formation\, stellar dynamics\, and the nature of dark matter\, with emphasis on our own Milky Way galaxy. \nSimulating the Milky Way\nThe Gaia satellite mission\, together with a multitude of ground-based observational surveys\, now measure 6-D phase-space coordinates and multi-species elemental abundances for hundreds of millions of stars across the Milky Way. This new era of galactic archeology and near-field cosmology demands a new generation of simulations that achieve high dynamic range to resolve scales of individual stellar populations within a cosmological context. I will describe the new Latte suite of massively parallelized cosmological zoom-in simulations\, run on the nation’s most powerful supercomputers\, that model the formation of Milky Way-like galaxies at parsec-scale resolution\, using the FIRE (Feedback in Realistic Environments) model for star formation and feedback. First I will discuss the formation of the Milky Way disk\, including resolving for the first time the dynamics and lifetimes of giant molecular clouds and stars clusters at z = 0. These simulations also self-consistently resolve the formation of satellite dwarf galaxies around each Milky Way-like host. These low-mass galaxies have presented significant challenges to the cold dark matter model\, but I will show progress in addressing the “missing satellites” and “too-big-to-fail” problems. Finally\, I will discuss synthetic Milky Way surveys that we have created from the Latte simulations\, which are publicly available\, to provide theoretical modeling insight for the era of Gaia. \nProf. Wetzel is being hosted by Prof. Gnedin (Astronomy).  If you would like to meet with him during his visit\, please send an email to micde-events@umich.edu. If you are an MICDE graduate student and would like to join Prof. Wetzel for lunch please RSVP by Thursday\, January 23. 
URL:https://micde.umich.edu/event/micde-seminar-andrew-wetzel-uc-davis/
LOCATION:411 West Hall (1085 S. University)\, 1085 S. University 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/2019/12/Andrew-Wetzel.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20191028T160000
DTEND;TZID=America/Detroit:20191028T160000
DTSTAMP:20260603T200736
CREATED:20230905T171336Z
LAST-MODIFIED:20230905T171336Z
UID:10000297-1572278400-1572278400@micde.umich.edu
SUMMARY:Mid West Mechanics Seminar: Jacqueline H. Chen\, Senior Scientist\, Sandia National Laboratories
DESCRIPTION:Bio: Jacqueline H. Chen is a Senior Scientist at the Combustion Research Facility at Sandia National Laboratories. She has contributed broadly to research in turbulent combustion elucidating turbulence-chemistry interactions in combustion through direct numerical simulations. To achieve scalable performance of DNS on heterogeneous computer architectures she leads an interdisciplinary team of computer scientists\, applied mathematicians and computational scientists to develop an exascale direct numerical simulation capability for turbulent combustion with complex chemistry and multi- physics. She is a member of the National Academy of Engineering and a Fellow of the Combustion Institute and the Americal Physical Society. She received the Combustion Institute’s Bernard Lewis Gold Medal Award in 2018 and the Society of Women Engineers Achievement Award in 2018. \nTowards Exascale Simulation of Turbulent Combustion in Complex Flows Relevant to Efficient Clean Engines\nDirect numerical simulation (DNS) methodology and computing power have progressed to the point where it is feasible to perform DNS in mildly complex geometries representative of flow configurations encountered in practical combustors. These complex flows encompass effects of mean shear\, flow recirculation\, and wall boundary layers together with turbulent fluctuations which affect entrainment\, mixing and combustion. Recent DNS studies with complex flows relevant to efficient low emissions gas turbine and internal combustion engines will be presented. Through application co-design with computer scientists a data centric asynchronous programming system has been used to refactor the DNS code\, S3D\, resulting in improved time-to-solution and overall performance on heterogeneous architectures. The programming system also provides more efficient and effective composition of in situ analytics and machine learning techniques. \nContact Melissa McGeorge (mcgeorge@umich.edu) for more details.
URL:https://micde.umich.edu/event/mid-west-mechanics-seminar-jacqueline-h-chen-sandia-national-laboratories/
LOCATION:107 Gorguze Family Laboratory\, 2609 Draper Dr\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://micde.umich.edu/wp-content/uploads/2023/02/JacquelineChen.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190410T080000
DTEND;TZID=America/Detroit:20190410T170000
DTSTAMP:20260603T200736
CREATED:20230905T171359Z
LAST-MODIFIED:20230905T171359Z
UID:10000141-1554883200-1554915600@micde.umich.edu
SUMMARY:The 2019 MICDE Symposium
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 Michigan Institute for Computational Discovery and Engineering 2019 Symposium will feature eminent scientists from around the world and the U-M campus. \n\n\nSPEAKERS\n\n\n\n\n\n\n\n\n\n\nMarsha Berger\nProfessor\, Computer Science and Mathematics\nNew York University Courant Institute of Mathematical Sciences \n\nMarisa Eisenberg\nAssociate Professor\, Epidemiology and Mathematics\nUniversity of Michigan \n\nCarla Gomes\nProfessor and Director\, Institute for Computational Sustainability\nCornell University \n\nJan Hesthaven\nDean\, School of Basic Sciences\nEPFL\, Switzerland \n\nNecmiye Ozay\nAssistant Professor\, Electrical Engineering and Computer Science\nUniversity of Michigan \n\nStephen Wolfram\nFounder and CEO\, Wolfram Research\nCreator of Mathematica \n\n\n\n\n\n\n\nA poster competition will be held\, open to post-docs and graduate students. \nMore information will be posted here as it becomes available. Also see micde.umich.edu/symposium19[/vc_column_text][/vc_column][/vc_row]
URL:https://micde.umich.edu/event/the-2019-micde-symposium/
LOCATION:Michigan League\, 911 N. University\, Ann Arbor\, MI\, 48104\, United States
CATEGORIES:Featured Events,Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190111T150000
DTEND;TZID=America/Detroit:20190111T160000
DTSTAMP:20260603T200736
CREATED:20230905T171422Z
LAST-MODIFIED:20230905T171422Z
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SUMMARY:MICDE Seminar: Yuri Bazilevs\, School of Engineering\, Brown University
DESCRIPTION:Bio: Yuri Bazilevs is the E. Paul Sorensen Chair in the School of Engineering at Brown University. He was previously a Professor and Vice Chair in the Structural Engineering Department at the University of California\, San Diego. Yuri is the original developer of Isogeometric Analysis (IGA)\, a new computational methodology that aims to integrate engineering design (CAD) and simulation (FEM). For his research contributions Yuri received a number of awards and honors\, including the 2018 ASCE Walter L. Huber Research Prize. He is included in the 2014-2018 lists of Highly Cited Researchers\, both in the Engineering and Computer Science categories. \nISOGEOMETRIC METHODS FOR SOLIDS\, STRUCTURES\, AND FLUID-STRUCTURE INTERACTION: FROM EARLY RESULTS TO RECENT DEVELOPMENTS\nThis presentation is focused on Isogeometric Analysis (IGA) with applications to solids and structures\, starting with early developments and results\, and transitioning to more recent work. Novel IGA-based thin-shell formulations are discussed\, and applications to progressive damage modeling in composite laminates due to low-velocity impact and their residual-strength prediction are shown. Fluid–structure interaction (FSI) employing IGA is also discussed\, and a novel framework for air-blast-structure interaction (ABSI) based on an immersed approach coupling IGA and RKPM-based Meshfree methods is presented and verified on a set of challenging examples. The presentation is infused with examples that highlight effective uses of IGA in advanced engineering applications. \nProf. Bazilevs is being hosted by Prof. Garikipati (Mechanical Engineering). If you would like to meet him during his visit please send an email to micde-events@umich.edu. If you are an MICDE or ME student and would like to join Prof. Bazilevs for lunch please RVSP here by Wednesday\, January 9.
URL:https://micde.umich.edu/event/micde-seminar-yuri-bazilev-school-of-engineering-brown-university/
LOCATION:2540 G.G. Brown (2350 Hayward St.)\, 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:20181212T160000
DTEND;TZID=America/Detroit:20181212T170000
DTSTAMP:20260603T200736
CREATED:20230905T171422Z
LAST-MODIFIED:20230905T171422Z
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SUMMARY:MICDE Seminar: Aaron Frank\, Chemistry and Biophysics\, University of Michigan
DESCRIPTION:Bio: Aaron Frank is originally from Grenada\, a small island in the Caribbean. After moving to the US in 2001\, Aaron received his BA in chemistry from Brooklyn College in 2006\, where he carried out research in the groups of Professors Charlene Forest\, Shaneen Singh\, and Alexander Greer. He then moved to Michigan to attend graduate school at the University of Michigan and then\, with his Ph.D advisor Professor Ioan Andricioaei\, moved to UC Irvine in 2008. Aaron received his Ph.D in chemistry in 2011. Following a 2 year stint at Nymirum Inc. — a small biotech company in Ann Arbor founded by a close collaborator\, Professor Hashimi Al-Hashimi — he returned to the University of Michigan as a Presidential Postdoctoral Fellow where he was mentored by Professor Charles L. Brooks\, III. Aaron is now an Assistant Professor at the University of Michigan in the Chemistry Department and the Biophysics Department. \nDATA SCIENCE AT THE INTERFACE OF BIOLOGY\, CHEMISTRY\, AND PHYSICS\nIn this talk\, I will describe examples of how my research group uses data science tools to tackle research problems that fall at the interface between Biology\, Chemistry\, and Physics. First\, I will describe ongoing research focused on mapping the structure-landscape of functional ribonucleic acids (or RNAs). In this project\, we combined machine learning and secondary structure modeling tools to predict the structure of RNAs conditioned on available NMR chemical shift data. This method now enables us to model individual conformational states\, including previously invisible states of an RNA\, based on its sequence and available chemical shift data. Second\, I will describe ongoing research centered around decoding structure-kinetic relationships (SKRs) in sparse datasets. There is now immense interest in developing drugs that exhibit elevated residence times on their target. In this project\, we used machine learning to encapsulate SKRs for CDK2\, a prominent cancer target\, from a dataset containing only fourteen (14) samples. I will describe our efforts to build and test CDK2-specific SKR models that take as input\, the atomic structure of receptor-ligand complexes and output estimates of their residence times. Additionally\, I will describe proof-of-concept studies that demonstrate the utility of our CDK2-specific SKR models as tools to help efficiently explore chemical space in search of novel chemical scaffolds that are enriched with high-residence time and potent inhibitors of CDK2.
URL:https://micde.umich.edu/event/micde-seminar-aaron-frank-chemistry-and-biophysics-university-of-michigan/
LOCATION:1210 Chemistry & Willard H Dow Laboratory\, 930 University Ave.\, 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:20181126T150000
DTEND;TZID=America/Detroit:20181126T160000
DTSTAMP:20260603T200736
CREATED:20230905T171421Z
LAST-MODIFIED:20230905T171421Z
UID:10000162-1543244400-1543248000@micde.umich.edu
SUMMARY:CANCELLED --MICDE Seminar: Ali Yilmaz\, Electrical Engineering\, University of Texas at Austin
DESCRIPTION:CANCELLED\nBio: Ali Yilmaz is an Associate Professor of Electrical and Computer Engineering and a core faculty member at the Institute for Computational Engineering and Sciences at the University of Texas at Austin. \nDr. Yilmaz received the Ph.D. degree in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign in 2005. He spent 2005 to 2006 as a post-doctoral research associate with the Center for Computational Electromagnetics at the University of Illinois; in 2006\, he joined the faculty of The University of Texas at Austin. \nHis research interests include computational electromagnetics (particularly fast frequency- and time-domain integral equation solvers)\, parallel algorithms\, antenna and scattering analysis\, bioelectromagnetics\, geoelectromagnetics\, and electronic packages. He has authored or co-authored over 170 papers in refereed journals and international conferences on these topics. \nUSING (SUPER) COMPUTERS JUDICIOUSLY FOR HIGHER FIDELITY ELECTROMAGNETIC ANALYSIS\nIncreasing the fidelity of the electromagnetic models generally increases the predictive power of the analyses based on the models. It also generally increases the results’ sensitivity to model features/parameters as well as the difficulty of constructing the models\, accurately solving the governing equations\, and interpreting the resulting data. Therefore\, one should base the analysis on the lowest-fidelity model one can get away with or\, equivalently\, the highest-fidelity model one can afford. The sweet spot for the tradeoff\, “the appropriate model”\, has changed over time in part because past successes in simulation-based science and engineering have increased expectations/requirements from electromagnetic analysis and in part because tremendous improvements in computing infrastructure and advances in computational methods have increased the affordability of complex analysis. Finding the appropriate model requires understanding both the benefits and the costs of analysis when a lower- or higher-fidelity model is used; neither side of the ledger\, however\, is known beforehand (unless one is repeating previously established analyses). A possible approach to revealing these unknowns is to construct models by gradually increasing their fidelity\, performing analysis at each fidelity level\, and comparing the analysis results and costs to those from the previous steps. I will show examples of this “analysis-driven modeling” in bioelectromagnetics (using the AustinMan and AustinWoman human body models) and signal integrity (using an electronic package example) by employing parallel algorithms and advanced integral-equation solvers on leading-edge supercomputers. \nThe examples will highlight many of the challenges arising from this approach to modeling. An important one is that “the appropriate method” of analysis generally depends on the model\, e.g.\, a method can outperform alternatives for low-fidelity models but underperform them for high-fidelity ones; indeed\, inappropriate (but convenient) methods can not only inflate the cost side of the ledger but also deflate the benefit side\, leading to misjudgment of the appropriate model fidelity. Thus\, not surprisingly\, the development of appropriate electromagnetic models and appropriate computational methods are tightly linked (aka “if all you have is a hammer\, everything looks like a nail”). Unfortunately\, evaluating computational methods to find the appropriate one for a given model is surprisingly difficult\, even for unbiased experts\, as method performances depend not just on the models but also on the computers\, the software realizations of the methods\, and the users/developers of the software. On the one hand\, theoretical comparisons (e.g.\, of asymptotic complexities\, error convergence rates\, parallel scalability limits) are often incapable of factoring in the large impact of software and hardware infrastructure on the realized/observed performance of a computational method—a problem that has worsened as the traditional Dennard scaling of clock frequencies ended in the last decade. On the other hand\, empirical comparisons are beset by the same problems that physical measurements face (including irreproducible and uncertain results)\, require many (potentially low-efficiency) computations\, and suffer from the large number of alternative methods. I will discuss whether benchmark suites can improve the judicious use of computational methods for electromagnetic analysis and what the necessary ingredients for such benchmarks are. \nProf. Yilmaz is being hosted by Prof. Michielssen (EECS). If you would like to meet with him during his visit\, please send an email to micde-events@umich.edu. If you are an MICDE student and would like to join Prof. Yilmaz for lunch\, please fill out this form.
URL:https://micde.umich.edu/event/micde-seminar-ali-yilmaz-electrical-engineering-university-of-texas-at-austin/
LOCATION:1311 EECS\, 1301 Beal Ave.\, 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:20181109T130000
DTEND;TZID=America/Detroit:20181109T140000
DTSTAMP:20260603T200736
CREATED:20230905T171421Z
LAST-MODIFIED:20230905T171421Z
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SUMMARY:SC2 Alumni Seminar Series: Eric Harper\, NRC Research Associate\, AFRL
DESCRIPTION:Bio: Dr. Eric Harper is a Postdoctoral Fellow at the Air Force Research Laboratories (AFRL) at Wright-Patterson Air Force Base (WPAFB) in Dayton\, Ohio as part of the Air Force Science and Technology Fellowship Program (STFP). He is a member of the Optical Theory Group (OTG)\, simulating optical metamaterials to optimize their design using scientific computing techniques. He earned his B.S. in Chemical Engineering at the University of Dayton (2011) and his M.S. (2014) and Ph.D. at the University of Michigan (2017). \nMachine Accelerated Nano-targeted Inhomogenous Structures\nThe ability for nanoscale materials to control the propagation of light is well-known\, both in biological systems and synthetic applications. However\, the possible “solution-space” to search for nanoscale designs is near-infinite\, requiring advanced computational techniques to optimize structures for targeted device performance. Here we consider a subset of the infinite design space\, a simple bilayer structure of nanocylinders\, to demonstrate the capabilities of machine learning to accelerate the design process. We compare the performance of human-driven optimization to a genetic algorithm based optimization routine. We also consider potential machine-learning tools to further accelerate the design of these structures. \nThe SC2 is holding a Meet the Speaker lunch at noon. If you would like to attend\, please RSVP here.
URL:https://micde.umich.edu/event/sc2-alumni-seminar-series-eric-harper-nrc-research-associate-afrl/
LOCATION:2540 G.G. Brown (2350 Hayward St.)\, 2300 Hayward St\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,SC2,Seminar
ATTACH;FMTTYPE=image/jpeg:https://micde.umich.edu/wp-content/uploads/2023/02/EricHaperatAFRL.jpeg
GEO:42.292998;-83.7152904
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20181023T113000
DTEND;TZID=America/Detroit:20181023T130000
DTSTAMP:20260603T200736
CREATED:20230905T171421Z
LAST-MODIFIED:20230905T171421Z
UID:10000166-1540294200-1540299600@micde.umich.edu
SUMMARY:Complex Systems Seminar: Giovanni Fantuzzi\, Aeronautics\, Imperial College London
DESCRIPTION:Bio: Giovanni Fantuzzi is an EPSRC Doctoral Prize Fellow in the Department of Aeronautics\, Imperial College London\, from which he received an MEng degree in 2014 and a PhD in 2018. During his PhD he developed optimization-based methods and software for studying stability and time-averaged properties of dynamical systems\, with applications to fluid flows. In 2015 he was awarded a Geophysical Fluid Dynamics Fellowship from Woods Hole Oceanographic Institution and was subsequently a Research Assistant at the University of Oxford\, where he worked on fast algorithms for structured semidefinite programmes and sum-of-squares optimization. His current research spans fluid dynamics and convex optimization\, and he is especially interested in scalable convex approaches to hydrodynamic analysis. \nBeyond numerical integration: studying nonlinear dynamics with polynomial optimization\nSystems characterized by complex nonlinear dynamics lie at the heart of 21st century technology. Examples are turbulent flows in the transport and aviation industries\, smart energy networks\, and models of cell dynamics used in synthetic biology. Quantitative analysis of such systems using direct numerical simulations sometimes requires prohibitively large computational resources even when one is interested only in some average properties\, such as mean power consumption\, because all time and length scales across which the system evolves must be resolved. In addition\, while numerical simulations offer detailed information starting from a specific initial state\, they cannot provide safety-critical performance or stability guarantees that hold for all possible initial states. In this talk\, I will describe an alternative approach to studying nonlinear systems with polynomial dynamics\, which combines ideas from Lyapunov’s stability theory with recent numerical tools for polynomial optimization. In particular\, I will present a range of examples that demonstrate how this optimization-based method enables the efficient algorithmic construction of stability certificates and the computation of rigorous bounds on performance-related system properties. Other applications\, including optimal control and disturbance amplification analysis\, will be discussed along with open problems and future research directions.
URL:https://micde.umich.edu/event/complex-systems-seminar-giovanni-fantuzzi-aeronautics-imperial-college-london/
LOCATION:Weiser Hall\, Room 747\, 500 Church St\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/02/GiovanniFantuzzi2018.png
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20180914T150000
DTEND;TZID=America/Detroit:20180914T160000
DTSTAMP:20260603T200736
CREATED:20230905T171420Z
LAST-MODIFIED:20230905T171420Z
UID:10000158-1536937200-1536940800@micde.umich.edu
SUMMARY:AIM Seminar: Robert Krasny\, Mathematics\, University of Michigan
DESCRIPTION:Two topics in computational fluid dynamics\n1. The Lamb dipole is a steady propagating solution of the inviscid fluid equations with opposite-signed vorticity in a circular disk. We compare finite-difference solutions of the Navier-Stokes equation (NSE) and the linear diffusion equation (LDE) using the Lamb dipole as the initial condition. We find some expected and some unexpected results; among the latter is that the maximum core vorticity decreases at the same rate for the NSE and LDE\, but at higher Reynolds numbers\, convection enhances the viscous cancellation of opposite-signed vorticity.\n(This is joint work with Ling Xu.) \n2. We discuss a new implementation of the vortex method for the incompressible Euler equations. The vorticity is carried by Lagrangian particles and the velocity is recovered by a regularized Biot-Savart integral. The new work employs remeshing and adaptive refinement to resolve small-scale features in the vorticity as well as a treecode for efficiency. The method is demonstrated for vortex dynamics on a rotating sphere (with Peter Bosler) and axisymmetrization of an elliptical vortex (with Ling Xu).
URL:https://micde.umich.edu/event/aim-seminar-robert-krasny-mathematics-university-of-michigan/
LOCATION:1084 East Hall\, 530 Church St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Seminar
GEO:42.2757302;-83.7351764
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=1084 East Hall 530 Church St. Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=530 Church St.:geo:-83.7351764,42.2757302
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20180907T150000
DTEND;TZID=America/Detroit:20180907T160000
DTSTAMP:20260603T200736
CREATED:20230905T171421Z
LAST-MODIFIED:20230905T171421Z
UID:10000157-1536332400-1536336000@micde.umich.edu
SUMMARY:AIM Seminar: Alex Gorodetsky\, Aerospace Engineering\, University of Michigan
DESCRIPTION:Low-rank tensor approaches for adaptive function approximation: algorithms and examples\nIn this talk\, we present an adaptive method for approximating high-dimensional low-rank functions. Taking advantage of low-rank structure in approximation problems has been shown to prove advantageous for scaling numerical algorithms and computation to higher dimensions by mitigating the curse-of-dimensionality. The method we describe is an extension of the tensor-train cross approximation algorithm to the continuous case of multivariate functions that enables both global and local adaptivity. Our approach relies on a new adaptive algorithm for computing the CUR/skeleton decomposition of bivariate functions. We then extend this technique to the multidimensional case of the function-train decomposition. We demonstrate the benefits of our approach compared with the standard methodology that computes low-rank approximations by decomposing coefficients of tensor-product basis functions. We finish by demonstrating a wide range of applications that include machine learning\, uncertainty quantification\, stochastic optimal control\, and Bayesian filtering.
URL:https://micde.umich.edu/event/aim-seminar-alex-gorodetsky-aerospace-engineering-university-of-michigan/
LOCATION:1084 East Hall\, 530 Church St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Seminar
GEO:42.2757302;-83.7351764
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=1084 East Hall 530 Church St. Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=530 Church St.:geo:-83.7351764,42.2757302
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20180806T083000
DTEND;TZID=America/Detroit:20180806T163000
DTSTAMP:20260603T200736
CREATED:20230905T171419Z
LAST-MODIFIED:20260401T200727Z
UID:10000148-1533544200-1533573000@micde.umich.edu
SUMMARY:Single-Cell Data Analytics Symposium 2018
DESCRIPTION:Please join us for the second annual Single-cell Genomic Data Analytics Symposium. The day long symposium will highlight researchers from U-M and around the world whose work is on the leading edge of innovation and discovery. This symposium is organized by the Michigan Center for Single-Cell Genomic Data Analytics and sponsored by the Michigan Institute for Data Science. \n\n\n\n\n  \nFEATURED SPEAKERS\n\nPeter Kharchenko\, Assistant Professor of Biomedical Informatics Harvard Medical School\nJohn Marioni\, Research Group Leader\, European Bioinformatics Institute\nDana Pe’er\, Scientific Director\, GMTEC; Chair\, Computational and Systems Biology Program\, Memorial Loan Kettering Cancer Center\nChristina Kendziorski\, Professor\, Biostatistics and Medical Informatics\, University of Wisconsin
URL:https://micde.umich.edu/event/single-cell-data-analytics-symposium-2018/
LOCATION:Palmer Commons\, Great Lakes Central Room\, 100 Washtenaw Ave.\, Ann Arbor\, MI\, United States
CATEGORIES:Conference,Seminar
GEO:42.2807096;-83.7338753
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Palmer Commons Great Lakes Central Room 100 Washtenaw Ave. Ann Arbor MI United States;X-APPLE-RADIUS=500;X-TITLE=100 Washtenaw Ave.:geo:-83.7338753,42.2807096
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20180406T150000
DTEND;TZID=America/Detroit:20180406T160000
DTSTAMP:20260603T200736
CREATED:20230905T171419Z
LAST-MODIFIED:20230905T171419Z
UID:10000138-1523026800-1523030400@micde.umich.edu
SUMMARY:CEE/MICDE Seminar: Khachik Sargsyan\, Sandia National Laboratories
DESCRIPTION:Bio: Khachik Sargsyan is a Principal Member of Technical Staff at Sandia National Laboratories (SNL) in Livermore\, CA. Before staff and postdoctoral positions at SNL\, he received his Ph.D. in Applied and Interdisciplinary Mathematics from University of Michigan\, Ann Arbor\, in 2007. His Bachelors degree\, awarded in 2002\, is in Applied Math and Physics from Moscow Institute of Physics and Technology. Dr. Sargsyan’s research evolves around uncertainty quantification (UQ) and predictability analysis of physical and computational models. He has developed and applied methods for model reduction\, UQ and data assimilation\, targeting fundamental challenges such as structural errors\, intrinsic stochasticity\, high-dimensionality\, limited data\, discontinuities and rare events\, with applications in climate modeling\, chemical kinetics\, hardware architecture simulators and turbulent combustion. He is one of the lead developers of UQTk (www.sandia.gov/uqtoolkit)\, a lightweight C++/Python software toolkit for quantification of uncertainties in model predictions.\n \nDr. Sargsyan is being hosted by Prof. Ivanov (Civil and Env. Engineering). If you would like to meet him\, please send an email to Chase Dwelle at dwellem@umich.edu \nProbabilistic Methods for Uncertainty Quantification in Computational Models\nOver the last decade\, improved measurement capabilities and computational resources have led to significant algorithmic developments toward efficient uncertainty quantification (UQ) for computational models. Such models of physical systems often involve input parameters that exhibit certain degree of uncertainty. Estimation and propagation of these uncertainties are crucial for model validation\, computational/experimental design and decision making. ​This talk will focus on probabilistic methods with emphasis on Polynomial Chaos (PC) expansions as a means for functional representation of random variables. The talk will highlight the use of PC methods both for forward propagation of uncertainties and for inverse problems\, such as parameter estimation via Bayesian inference. I will list associated major challenges\, including the curse of dimensionality and model structural error estimation\, in the context of computationally expensive models of physical systems. Both fundamental and more recent methods will be introduced and demonstrated\, impacting a wide range of applications\, such as climate modeling\, turbulent combustion and chemical kinetics.
URL:https://micde.umich.edu/event/cee-micde-seminar-khachik-sargsyan-sandia-national-laboratories/
LOCATION:1311 EECS\, 1301 Beal Ave.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2018/03/Khachik-Sargsyan.png
GEO:42.292322;-83.713272
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=1311 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:20180406T150000
DTEND;TZID=America/Detroit:20180406T160000
DTSTAMP:20260603T200736
CREATED:20230905T171419Z
LAST-MODIFIED:20230905T171419Z
UID:10000139-1523026800-1523030400@micde.umich.edu
SUMMARY:AIM Seminar: Christoph Börgers\, Mathematics\, Tufts University
DESCRIPTION:Bio: Christoph Börgers is a Professor of Mathematics at Tufts University. He got his Ph.D. under Prof. Charles Peskin at the Courant Institute of Mathematical Sciences\, in 1985. Prof. Börgers was a professor in the University of Michigan department of Mathematics until 1996 when he moved to Tufts. His expertise is in mathematical neuroscience\, applied dynamical systems\, numerical analysis\, scientific computing\, and during the past decade\, most of his work has been in the area of Computational Neuroscience. \nRhythms in neuronal networks with recurrent excitation\nInteracting excitatory and inhibitory neuronal populations often generate oscillations in electrical fields in the brain. I will briefly review this mechanism and the reasons to believe that it is important in brain function. Most of the talk will be focused on the effects of recurrent excitation\, i.e.\, of the neurons of a local network in the brain exciting each other. Recurrent excitation can sustain activity in a network that would otherwise be quiescent; this is believed to be the basis of working memory. It can also lead to a runaway process\, with excitation generating more excitation etc.\, much as the presence of a quadratic term on the right-hand side of a differential equation can lead to blow-up in finite time; this may be related to epileptic seizures. For model problems\, we prove that abrupt transitions to runaway activity require recurrent excitation with fast kinetics\, while working memory activity is more robust with recurrent excitation with slow kinetics. \nProf. Börgers is being hosted by Prof. Robert Krasny (Mathematics).
URL:https://micde.umich.edu/event/aim-seminar-christoph-borgers-mathematics-tufts-university/
LOCATION:1084 East Hall\, 530 Church St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2018/03/Christoph-Borgers.png
GEO:42.2757302;-83.7351764
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=1084 East Hall 530 Church St. Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=530 Church St.:geo:-83.7351764,42.2757302
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20180116T160000
DTEND;TZID=America/Detroit:20180116T170000
DTSTAMP:20260603T200736
CREATED:20230905T171416Z
LAST-MODIFIED:20230905T171416Z
UID:10000098-1516118400-1516122000@micde.umich.edu
SUMMARY:MICDE Seminar: Theresa Windus\, Chemistry\, Iowa State University
DESCRIPTION:Bio: Theresa Windus is a professor of Chemistry at Iowa State University. She earned her Ph.D. from Iowa State University in 1993 and did post-doctoral research at Northwestern University. Theresa was also the Director of Computational Chemistry/Training at Ohio Supercomputer Center and the Computational Chemistry lead at the Wright Patterson Air Force Base Major Shared Resource Center. Most recently\, she was the manager of the Molecular Science Software Group and the Visualization and User Services group in the Molecular Science Computing Facility in the Environmental Molecular Sciences Laboratory of Pacific Northwest National Laboratory. \nThe challenges of the exascale from the view of a molecular chemist\nThis talk will focus on the challenges that computational chemistry faces in taking the equations that model the very small (molecules and the reactions they undergo) to efficient and scalable implementations on the very large computers of today andtomorrow. In particular\, how do we take advantage of the newest architectures while preparing for the next generation of computers? How do we increase programmer productivity while ensuring excellent performance\, efficiency and portability across multiple platforms? How do we take advantage of the work of mathematicians\, computer scientists and other computational scientists to enable our science\, while ensuring maintainability and usability of the software? How do we ensure that the algorithms that we develop are making wise use of the computational resources? How do help the next generation of computational chemists to be ready for the complex computing environments that they will face? While not claiming to have answers to all (or any!) of these questions\, we will explore some possible solutions and their implications as we go forward and face the current petascale and the future exascale challenges. These will be in the context of several Department of Energy funded computational chemistry Exascale Computing Projects (NWChemEx and GAMESS) and the NSF funded Molecular Sciences Software Institute. \nProf. Windus is being hosted by Prof. Geva (Chemistry). If you would like to meet with him Prof. Windus during her visit please email mcteja@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-theresa-windus-chemistry-iowa-state-university/
LOCATION:CHEM 1640\, 930 N University\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2017/09/Theresa-Windus.png
GEO:42.2780183;-83.7370191
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=CHEM 1640 930 N University Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=930 N University:geo:-83.7370191,42.2780183
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20171206T120000
DTEND;TZID=America/Detroit:20171206T130000
DTSTAMP:20260603T200736
CREATED:20230905T171416Z
LAST-MODIFIED:20230905T171416Z
UID:10000118-1512561600-1512565200@micde.umich.edu
SUMMARY:ME Faculty Candidate Seminar Series: Xun (Ryan) Huan\, Combustion Research Facility at Sandia National Laboratories
DESCRIPTION:Bio: Xun (Ryan) Huan is a postdoctoral researcher in the Combustion Research Facility at Sandia National Laboratories. He received a Ph.D. in Computational Science and Engineering from MIT Department of Aeronautics and Astronautics. He also has a master’s degree from MIT and a bachelor’s degree from the University of Toronto\, both in Aerospace Engineering. Xun’s research interests broadly revolve around uncertainty quantification\, decision-making under uncertainty\, data-driven modeling\, and optimization for engineering applications. Outside work\, he is an ice hockey player and a pilot. \nFinding the Most Informative Data Using Model-based Optimal Experimental Design\nExperimental data play a crucial role in developing and refining models of physical systems. However\, some experiments produce more useful data than others\, and well-chosen experiments can provide substantial resource savings. Optimal experimental design (OED) thus seeks to systematically quantify and maximize the value of experiments. We introduce general mathematical frameworks and algorithmic approaches for OED with nonlinear models. The formalism employs Bayesian statistics and an information-theoretic objective\, and rigorously defines the conditions under which batch experiments (experiments chosen simultaneously) and sequential experiments (forward-looking designs with data feedback) are truly optimal. Finding these optimal designs using conventional means is generally intractable. We develop practical numerical methods for OED by advancing computational techniques on several fronts\, including stochastic optimization\, polynomial chaos surrogate modeling\, approximate dynamic programming\, and transport maps. Using the overall algorithm\, we design combustion experiments for optimal learning of Arrhenius kinetic parameters\, and sequential sensor placement for contaminant source inversion.\n\n* Lunch won’t be provided but you are welcome to bring your own\n\n\n\nThis is a talk of potential interest to the MICDE community. The speakers in this seminar series are Faculty Candidates in the department of Mechanical Engineering for a Computational Science search that is being carried out with the active engagement of MICDE. We expect that the successful candidate will be a highly engaged affiliate of MICDE.
URL:https://micde.umich.edu/event/me-faculty-candidate-seminar-series-xun-ryan-huan/
LOCATION:MI
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://micde.umich.edu/wp-content/uploads/2023/02/XunRyanHuan-e1583777526832.jpg
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20171204T100000
DTEND;TZID=America/Detroit:20171204T110000
DTSTAMP:20260603T200736
CREATED:20230905T171416Z
LAST-MODIFIED:20230905T171416Z
UID:10000117-1512381600-1512385200@micde.umich.edu
SUMMARY:ME Faculty Candidate Seminar Series: Maziar Raissi\, Brown University
DESCRIPTION:Bio: Maziar Raissi is an Assistant Professor of Applied Mathematics (research) in the Division of Applied Mathematics at Brown University. He received his Ph.D. in Applied Mathematics & Statistics\, and Scientific Computations from University of Maryland — College Park in December 2016. Raissi’s expertise lies at the intersection of Probabilistic Machine Leaning\, Deep Learning\, and Data Drive Scientific Computing. \nHidden Physics Models: Machine Learning of Non-linear Partial Differential Equations\n\nA grand challenge with great opportunities is to develop a coherent framework that enables blending conservation laws\, physical principles\, and/or phenomenological behaviours expressed by differential equations with the vast data sets available in many fields of engineering\, science\, and technology. At the intersection of probabilistic machine learning\, deep learning\, and scientific computations\, this work is pursuing the overall vision to establish promising new directions for harnessing the long-standing developments of classical methods in applied mathematics and mathematical physics to design learning machines with the ability to operate in complex domains without requiring large quantities of data. To materialize this vision\, this work is exploring two complimentary directions: (1) designing data-efficient learning machines capable of leveraging the underlying laws of physics\, expressed by time dependent and non-linear differential equations\, to extract patterns from high-dimensional data generated from experiments\, and (2) designing novel numerical algorithms that can seamlessly blend equations and noisy multi-fidelity data\, infer latent quantities of interest (e.g.\, the solution to a differential equation)\, and naturally quantify uncertainty in computations. The latter is aligned in spirit with the emerging field of probabilistic numerics. \n\n\nThis is a talk of potential interest to the MICDE community. The speakers in this seminar series are Faculty Candidates in the department of Mechanical Engineering for a Computational Science search that is being carried out with the active engagement of MICDE. We expect that the successful candidate will be a highly engaged affiliate of MICDE.
URL:https://micde.umich.edu/event/me-faculty-candidate-seminar-series-maziar-raissi-brown-university/
LOCATION:MI
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://micde.umich.edu/wp-content/uploads/2023/02/MaziarRaissi.jpg
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20171201T083000
DTEND;TZID=America/Detroit:20171201T173000
DTSTAMP:20260603T200736
CREATED:20230905T171416Z
LAST-MODIFIED:20230905T171416Z
UID:10000105-1512117000-1512149400@micde.umich.edu
SUMMARY:2017 U-M Data Science Research Forum
DESCRIPTION:Forum Highlights \n\nOral and poster presentations on\n\nTheoretical foundations of data science\nData science methodology\nData science applications in any research domain\nSocial impact of data science research\n\n\n\n\nHow to engage industry workshop\n\nAdrian Fortino\, Partner (Mercury Fund)\nMike Psarouthakis\, Director (U-M Venture Center)\nKevyn Collins-Thompson\, Associate Professor\, U-M School of Information\nMike Cafarella\, Associate Professor\, U-M Computer Science Engineering\n\n\n\n\nKeynote by Chris Rozell\n\n\nNetworking Reception\n\nAll presentations will come from submissions in response to our call for abstracts\n Abstract Submission Deadline: October 23\, 2017\n We welcome submission from all U-M data science researchers (faculty\, staff\, trainees) \nPlease register for this event.  Please also see the call for abstracts for instruction\, and submit through the Abstract Submission Form. \nPreliminary Schedule
URL:https://micde.umich.edu/event/data-science-research-forum/
LOCATION:Michigan League\, 911 N. University\, Ann Arbor\, MI\, 48104\, United States
CATEGORIES:Conference,Data Science,Seminar
GEO:42.2796269;-83.7374973
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Michigan League 911 N. University Ann Arbor MI 48104 United States;X-APPLE-RADIUS=500;X-TITLE=911 N. University:geo:-83.7374973,42.2796269
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