BEGIN:VCALENDAR VERSION:2.0 PRODID:-//Michigan Institute for Computational Discovery and Engineering - ECPv6.15.20//NONSGML v1.0//EN CALSCALE:GREGORIAN METHOD:PUBLISH X-WR-CALNAME:Michigan Institute for Computational Discovery and Engineering X-ORIGINAL-URL:https://micde.umich.edu X-WR-CALDESC:Events for Michigan Institute for Computational Discovery and Engineering REFRESH-INTERVAL;VALUE=DURATION:PT1H X-Robots-Tag:noindex X-PUBLISHED-TTL:PT1H BEGIN:VTIMEZONE TZID:America/Detroit BEGIN:DAYLIGHT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:EDT DTSTART:20170312T070000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:EST DTSTART:20171105T060000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:EDT DTSTART:20180311T070000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:EST DTSTART:20181104T060000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:EDT DTSTART:20190310T070000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:EST DTSTART:20191103T060000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:EDT DTSTART:20200308T070000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:EST DTSTART:20201101T060000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:EDT DTSTART:20210314T070000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:EST DTSTART:20211107T060000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:EDT DTSTART:20220313T070000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:EST DTSTART:20221106T060000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:EDT DTSTART:20230312T070000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:EST DTSTART:20231105T060000 END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTART;TZID=America/Detroit:20221031T153000 DTEND;TZID=America/Detroit:20221031T163000 DTSTAMP:20260603T190411 CREATED:20230714T153416Z LAST-MODIFIED:20230714T153416Z UID:10000603-1667230200-1667233800@micde.umich.edu 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 ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/07/Reese-Jones.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:20221027T153000 DTEND;TZID=America/Detroit:20221027T163000 DTSTAMP:20260603T190411 CREATED:20220825T193358Z LAST-MODIFIED:20230713T163634Z UID:10000578-1666884600-1666888200@micde.umich.edu 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 ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2022/08/John-Tramm.png END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Detroit:20220923T160000 DTEND;TZID=America/Detroit:20220923T170000 DTSTAMP:20260603T190411 CREATED:20220825T193358Z LAST-MODIFIED:20230810T200736Z UID:10000577-1663948800-1663952400@micde.umich.edu 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 ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2022/08/Pania-Newell.png GEO:42.292322;-83.713272 X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=1200 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:20220915T150000 DTEND;TZID=America/Detroit:20220915T160000 DTSTAMP:20260603T190411 CREATED:20220818T193725Z LAST-MODIFIED:20230713T164622Z UID:10000576-1663254000-1663257600@micde.umich.edu 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 ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2022/08/Andreas-Wachter.png GEO:42.2914823;-83.7138452 X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Johnson Rooms Lurie Engineering Center 3rd Floor LEC 3213ABC 1221 Beal Ave. Ann Arbor MI United States;X-APPLE-RADIUS=500;X-TITLE=1221 Beal Ave.:geo:-83.7138452,42.2914823 END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Detroit:20220414T103000 DTEND;TZID=America/Detroit:20220414T113000 DTSTAMP:20260603T190411 CREATED:20220322T145723Z LAST-MODIFIED:20230713T165804Z UID:10000553-1649932200-1649935800@micde.umich.edu 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 END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Detroit:20220405T150000 DTEND;TZID=America/Detroit:20220405T160000 DTSTAMP:20260603T190411 CREATED:20220111T193640Z LAST-MODIFIED:20260522T182816Z UID:10000552-1649170800-1649174400@micde.umich.edu 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 ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2022/01/Douglas-Spearot.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:20220401T150000 DTEND;TZID=America/Detroit:20220401T160000 DTSTAMP:20260603T190411 CREATED:20220302T210252Z LAST-MODIFIED:20230713T170700Z UID:10000558-1648825200-1648828800@micde.umich.edu 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:20220321T160000 DTEND;TZID=America/Detroit:20220321T170000 DTSTAMP:20260603T190411 CREATED:20210805T184953Z LAST-MODIFIED:20230713T170841Z UID:10000500-1647878400-1647882000@micde.umich.edu 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 END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Detroit:20220314T140000 DTEND;TZID=America/Detroit:20220314T150000 DTSTAMP:20260603T190411 CREATED:20220121T172527Z LAST-MODIFIED:20230713T171008Z UID:10000554-1647266400-1647270000@micde.umich.edu 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 ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2022/01/Marta-DElia.png END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Detroit:20220225T150000 DTEND;TZID=America/Detroit:20220225T160000 DTSTAMP:20260603T190411 CREATED:20230714T154821Z LAST-MODIFIED:20230714T154821Z UID:10000604-1645801200-1645804800@micde.umich.edu 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 ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/07/Blaise-Bourdin.png END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Detroit:20220225T150000 DTEND;TZID=America/Detroit:20220225T160000 DTSTAMP:20260603T190411 CREATED:20210805T194316Z LAST-MODIFIED:20230515T013050Z UID:10000501-1645801200-1645804800@micde.umich.edu 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:20260603T190411 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:20260603T190411 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:20260603T190411 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 END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Detroit:20211028T160000 DTEND;TZID=America/Detroit:20211028T170000 DTSTAMP:20260603T190411 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 END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Detroit:20210604T100000 DTEND;TZID=America/Detroit:20210604T110000 DTSTAMP:20260603T190411 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 END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Detroit:20200602T150000 DTEND;TZID=America/Detroit:20200602T160000 DTSTAMP:20260603T190411 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:20260603T190411 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 END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Detroit:20200320T150000 DTEND;TZID=America/Detroit:20200320T160000 DTSTAMP:20260603T190411 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:20260603T190411 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 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:20200225T113000 DTEND;TZID=America/Detroit:20200225T130000 DTSTAMP:20260603T190411 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:20260603T190411 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 ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2020/01/Osman-Basaran.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:20200131T153000 DTEND;TZID=America/Detroit:20200131T163000 DTSTAMP:20260603T190411 CREATED:20230905T171340Z LAST-MODIFIED:20230905T171340Z UID:10000331-1580484600-1580488200@micde.umich.edu 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:20260603T190411 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:20260603T190411 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:20260603T190411 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 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 END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Detroit:20190111T150000 DTEND;TZID=America/Detroit:20190111T160000 DTSTAMP:20260603T190411 CREATED:20230905T171422Z LAST-MODIFIED:20230905T171422Z UID:10000171-1547218800-1547222400@micde.umich.edu 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 ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2018/11/Yuri-Bazilevs.png GEO:42.292998;-83.7152904 X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=2540 G.G. Brown (2350 Hayward St.) 2300 Hayward St Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=2300 Hayward St:geo:-83.7152904,42.292998 END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Detroit:20181212T160000 DTEND;TZID=America/Detroit:20181212T170000 DTSTAMP:20260603T190411 CREATED:20230905T171422Z LAST-MODIFIED:20230905T171422Z UID:10000172-1544630400-1544634000@micde.umich.edu 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 ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2018/10/Aaron-Frank.png GEO:42.2780183;-83.7370191 X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=1210 Chemistry & Willard H Dow Laboratory 930 University Ave. Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=930 University Ave.:geo:-83.7370191,42.2780183 END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Detroit:20181126T150000 DTEND;TZID=America/Detroit:20181126T160000 DTSTAMP:20260603T190411 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 ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2019/07/Ali-Yilmaz.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:20181109T130000 DTEND;TZID=America/Detroit:20181109T140000 DTSTAMP:20260603T190411 CREATED:20230905T171421Z LAST-MODIFIED:20230905T171421Z UID:10000173-1541768400-1541772000@micde.umich.edu 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 X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=2540 G.G. Brown (2350 Hayward St.) 2300 Hayward St Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=2300 Hayward St:geo:-83.7152904,42.292998 END:VEVENT END:VCALENDAR