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SUMMARY:MICDE-IOE Seminar: Jong-Shi Pang\, Professor\, University of Southern California
DESCRIPTION:Bio: Elected a member of the National Academy of Engineering in February 2021 and appointed a Distinguished Professor in April 2023\, Jong-Shi Pang joined the University of Southern California as the Epstein Family Chair and Professor of Industrial and Systems Engineering in August 2013. Prior to this position\, he was the Caterpillar Professor and Head of the Department of Industrial and Enterprise Systems Engineering at the University of Illinois at Urbana-Champagne for six years between 2007 and 2013. He held the position of the Margaret A. Darrin Distinguished Professor in Applied Mathematics in the Department of Mathematical Sciences and was a Professor of Decision Sciences and Engineering Systems at Rensselaer Polytechnic Institute from 2003 to 2007. He was a Professor in the Department of Mathematical Sciences at the Johns Hopkins University from 1987 to 2003\, an Associate Professor and then Professor in the School of Management from 1982 to 1987 at the University of Texas at Dallas\, and an Assistant and then an Associate Professor in the Graduate School of Industrial Administration at Carnegie-Mellon University from 1977 to 1982. During 1999 and 2001 (full-time) and 2002 (part-time)\, he was a Program Director in the Division of Mathematical Sciences at the National Science Foundation. Professor Pang has served as the Department Academic Advisor of the Department of Mathematics at the Hong Kong Polytechnic University. He has given many distinguished lectures at universities worldwide and plenary lectures at international conferences. \nHeaviside Composite Optimization\, a new paradigm of optimization\nAbstract: This talk introduces the topic of Heaviside composite optimization and briefly covers its many facets: breadth in modeling\, roles in old and new applications\, theory of optimizers and stationary solutions\, bridge with discrete optimization\, and the progressive integer programming method. By definition\, a univariate Heaviside function is the (discontinuous) indicator of an interval. By its name\, a Heaviside composite function is the composition of a Heaviside function with a continuous multivariate function that may be nonconvex and nondifferentiable. While very natural in modeling many physical phenomena\, a Heaviside composite optimization problem\, possibly with Heaviside composite functional constraints\, has never been formally studied. Our work aims to fill this void with a comprehensive research program covering the applications\, theory\, and algorithms for this novel class of very challenging optimization problems. \nThis research has benefitted from previous collaboration with Ying Cui (UC Berkeley)\, Yue Fan (CUHK-SZ)\, Shaoning Han (NUS)\, Junyi Liu (Tsinghua)\, and Xinyao Zhang (USC)\, and is presently being organized in a monograph co-authored with Junyi Lui.
URL:https://micde.umich.edu/event/jong-shi-pang/
LOCATION:Johnson Rooms\, Lurie Engineering Center\, 3rd Floor LEC 3213ABC\, 1221 Beal Ave.\, Ann Arbor\, MI\, United States
CATEGORIES:Micde,Micde Seminar
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DTSTART;TZID=America/Detroit:20250128T160000
DTEND;TZID=America/Detroit:20250128T170000
DTSTAMP:20260522T151639Z
CREATED:20241011T222157Z
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SUMMARY:MICDE Seminar: Joshua Dolence\, Research Scientist\, Los Alamos National Lab
DESCRIPTION:Bio: Josh Dolence is a scientist in the Computational Physics & Methods Group at Los Alamos National Laboratory and a founding member of the LANL Michigan SPARC\, a permanent LANL presence at U-M in Ann Arbor. Before joining LANL\, he received a PhD in Astronomy from UIUC in 2011 and spent three years in Astrophysical Sciences at Princeton University where he worked in computational astrophysics\, studying topics like black hole accretion and supernovae. More recently\, he leads the Methods for Multiscale\, Multiphysics Accelerated Prediction project for LANL’s Advanced Simulation and Computing Program\, focusing efforts on enabling unprecedented fidelity and scale in modeling complex systems like high energy density physics experiments. \nParthenon: a flexible framework for rapid development of performance portable multiphysics codes\nAbstract: In many areas of computational science\, developing new\, state-of-the-art capabilities has become a high-cost\, risky proposition. The complexity and diversity of models\, methods\, algorithms\, and machines often lead to fundamental challenges in designing and building codes that enable advances in science and engineering. In fields like high energy density physics and astrophysics\, multiphysics simulations leveraging adaptive meshes\, particles\, and a variety of numerical methods are foundational to progress but difficult to realize performantly on ever-evolving high-performance computing platforms. In this talk\, I will present the Parthenon framework\, an open-source code base that aims to facilitate the development of highly adaptive\, multiphysics codes that are fast\, scalable\, and capable of leveraging modern platforms with both CPUs and GPUs. I will describe the basic principles behind its design and some of its most enabling features and highlight the ~10 downstream codes it already supports. \n 
URL:https://micde.umich.edu/event/joshua-dolence/
LOCATION:Johnson Rooms\, Lurie Engineering Center\, 3rd Floor LEC 3213ABC\, 1221 Beal Ave.\, Ann Arbor\, MI\, United States
CATEGORIES:Micde,Micde Seminar
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DTSTART;TZID=America/Detroit:20250117T160000
DTEND;TZID=America/Detroit:20250117T170000
DTSTAMP:20260522T182843Z
CREATED:20241224T044635Z
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SUMMARY:MICDE - NERS Seminar: Teresa Bailey\, Lawrence Livermore National Laboratory
DESCRIPTION:Bio: Teresa S. Bailey is the Associate Program Director of Computational Physics in LLNL’s Weapon Simulation and Computing program. She oversees the development of multiple multiphysics simulation tools across a wide range of applications. These codes span a broad range of physics\, chemistry\, and engineering application space. As required\, the codes are production-quality software products that are portable and computationally efficient on DOE’s most advanced HPC systems. \nBailey has been an LLNL employee since 2008. She began her career as a code physicist before moving into technical leadership roles as the Deterministic Transport project leader and the Nuclear Science program group leader. Bailey earned her B.S. in Nuclear Engineering from Oregon State University in 2002. She received the DOE Computational Science Graduate Fellowship to support her graduate work and earn her Ph.D. in Nuclear Engineering from Texas A&M in 2008. \nComputational Science and High-Performance Computing at Lawrence Livermore National Laboratory
URL:https://micde.umich.edu/event/workshop-seminarmicde-ners-seminar-teresa-bailey-lawrence-livermore-national-laboratory/
LOCATION:Johnson Rooms\, Lurie Engineering Center\, 3rd Floor LEC 3213ABC\, 1221 Beal Ave.\, Ann Arbor\, MI\, United States
CATEGORIES:College Of Engineering,Computational Science,Micde,Micde Seminar,Michigan Engineering,Nuclear Engineering and Radiological Sciences,Physics,Seminar
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20241007T140000
DTEND;TZID=America/Detroit:20241007T150000
DTSTAMP:20240920T130536Z
CREATED:20240920T130536Z
LAST-MODIFIED:20240920T130536Z
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SUMMARY:MICDE / MIDAS Graduate Information Session
DESCRIPTION:The educational programs represented are: \n\nPhD in Scientific Computing (MICDE)\nGraduate Certificate in Computational Discovery & Engineering (MICDE)\nGraduate Certificate in Computational Neuroscience (MICDE)\nGraduate Certificate in Data Science (MIDAS)\n\nThese programs are open to all U-M graduate students with an interest in scientific computing or data science. These methodologies can have a wide range of applications – current and past students have come from a variety of home departments including Aerospace Engineering\, Applied Physics\, Biostatistics\, Biomedical Engineering\, Civil & Environmental Engineering\, Chemistry\, Chemical Engineering\, Climate and Space Sciences and Engineering\, Computational Medicine and Bioinformatics\, Ecology and Evolutionary Biology\, Earth and Environmental Sciences\, Epidemiology\, Health Behavior and Health Education\, Health Infrastructures & Learning Systems\, Information\, Industrial & Operations Engineering\, Kinesiology\, Linguistics\, Macromolecular Science & Engineering\, Math\, Molecular\, Cellular\, and Developmental Biology\, Mechanical Engineering\, Materials Science & Engineering\, Naval Architecture & Marine Engineering\, Nuclear Engineering & Radiological Sciences\, Neuroscience\, Pharmaceutical Sciences\, Physics\, Political Science\, Psychology\, Environment and Sustainability\, Sociology and Statistics.\nIf you have any questions about these programs or about the information session\, please reach out to MICDE (micde-contact@umich.edu) or MIDAS (midas-contact@umich.edu).
URL:https://micde.umich.edu/event/micde-midas-graduate-information-session-2/
LOCATION:Johnson Rooms\, Lurie Engineering Center\, 3rd Floor LEC 3213ABC\, 1221 Beal Ave.\, Ann Arbor\, MI\, United States
CATEGORIES:Computation,Computational Modeling,Computational Science,Computational Social Science,data,Data Science,Deep Learning,Engineering,Free,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,In Person,Interdisciplinary,Machine Learning,Micde,Michigan Engineering,Midas,Neuroscience,Prospective Graduate Students,Rackham,Research,Science,Scientific Computing
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20240126T120000
DTEND;TZID=America/Detroit:20240126T130000
DTSTAMP:20240127T000733Z
CREATED:20240110T163210Z
LAST-MODIFIED:20240127T000733Z
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SUMMARY:MICDE / CEE Seminar: Michael D. Shields\, Associate Professor of Civil & Systems Engineering at Johns Hopkins University
DESCRIPTION:Bio: Michael D. Shields is an Associate Professor in the Department of Civil & Systems Engineering at Johns Hopkins University. He holds a secondary appointment in the Department of Materials Science and Engineering\, and is a fellow of the Hopkins Extreme Materials Institute. Prof. Shields conducts methodological research in uncertainty quantification (UQ) and probabilistic modeling for problems in mechanics\, materials science\, and physics with applications ranging from multi-scale material modeling to assessing the reliability and safety of large-scale structures. He received his Ph.D. in Civil Engineering and Engineering Mechanics from Columbia University in 2010\, after which he was employed as a Research Engineer in applied computational mechanics at Weidlinger Associates\, Inc. He joined the faculty at Johns Hopkins in 2013. For his work in UQ\, Prof. Shields has been awarded the ONR Young Investigator Award\, the NSF CAREER Award\, the DOE Early Career Award\, and the Johns Hopkins University Catalyst Award. Prof. Shields and his group also develop the open-source UQpy (Uncertainty Quantification with Python) software\, which is a general toolbox and development environment for UQ in computational\, mathematical\, and physical systems. \nUQ for ML and ML for UQ: Why Uncertainty Quantification and Machine Learning Go Hand-in-Hand\nUncertainty Quantification (UQ) and Machine Learning (ML) play an increasingly important role in physics-based computational modeling. Especially with the recent rise of scientific machine learning (SciML) and physics-informed ML\, new computational tools are being harnessed to solve bigger and more challenging problems. Moreover\, UQ has become an integral part of any physics-based modeling effort because our models\, as carefully developed as they may be\, are rife with uncertainties (both epistemic and aleatory) in their parameters\, inputs/excitations\, and sometimes in the form of the models themselves. When SciML methods are then applied in these applications\, additional uncertainties are introduced. In this talk\, I will broadly introduce the interrelated roles that UQ and ML play in physics-based modeling. I specifically distinguish between “UQ for ML” and “ML for UQ” and describe the important role that each plays in the modern physics-based computational modeling paradigm – demonstrating the role of UQ/ML in various applications of interest ranging from multi-scale materials modeling to high energy-density physics. \n  \n\n  \nThe MICDE Winter 2024 Seminar Series is open to all. University of Michigan faculty and students interested in predicting and explaining the properties of materials using computer simulation are encouraged to attend. \nThis seminar is cohosted by the Michigan Institute for Computational Discovery & Engineering (MICDE) and the Department of Civil and Environmental Engineering (CEE). Dr. Shields will be hosted by Dr. Evgueni Filipov\, Associate Professor of Civil and Environmental Engineering. \nThis is an in-person event. \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-cee-seminar-michael-d-shields-associate-professor-of-civil-systems-engineering-at-johns-hopkins-university/
LOCATION:Johnson Rooms\, Lurie Engineering Center\, 3rd Floor LEC 3213ABC\, 1221 Beal Ave.\, Ann Arbor\, MI\, United States
CATEGORIES:Featured Events,Micde Seminar,MICDE Seminar Series
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20231005T140000
DTEND;TZID=America/Detroit:20231005T150000
DTSTAMP:20231004T170032Z
CREATED:20230915T193609Z
LAST-MODIFIED:20231004T170032Z
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SUMMARY:LANL XPS Seminar: Mark W. Schraad\, Division Leader for Computational Physics at Los Alamos National Laboratory
DESCRIPTION:Bio: Mark W. Schraad earned his Ph.D. in Aerospace Engineering from the University of Michigan and has nearly three decades of research and development experience at Los Alamos National Laboratory. He focused his research career on materials physics\, with specialization in structured materials and material instabilities\, while also gaining scientific leadership experience across theoretical and computational physics\, modeling and simulation\, and scientific software development for advanced computing architectures and hardware. Mark has balanced experience across Los Alamos Science\, Technology\, and Engineering and Weapons Directorates\, and across the Laboratory’s basic science and mission application portfolios. In his current position\, he serves as Division Leader for Computational Physics within the Weapons Physics Directorate at Los Alamos National Laboratory. In this role\, he is responsible for the development and delivery of LANL’s suite of mission-critical modeling and simulation software\, which is used in the design\, certification\, and assessment of the U.S. nuclear stockpile. \nHigh-Performance Computing and the Future of Big Science for Department of Energy Applications\nLos Alamos is the birthplace of computational physics and has been at the forefront of high-performance computing for nearly eight decades. Integrating physics theory and advanced numerical methods in the instantiation of multi-physics software has allowed Los Alamos to address a broad range of science and technology applications. Today\, as one of 17 Department of Energy National Laboratories\, Los Alamos continues to develop and deploy advanced software in the execution of a complex mission across national security\, energy security\, and environmental and climate science. As part of that endeavor\, the Computational Physics Division at Los Alamos develops and delivers a continuously evolving suite of production software products to design and analyze large-scale integrated physics experiments and to enable the design\, assessment\, and confident certification of the U.S. nuclear stockpile. These software products are deployed on leading-edge\, high-performance computing platforms\, such as the Trinity and Crossroads supercomputers at Los Alamos\, and the Sierra and El Capitan machines at Lawrence Livermore National Laboratory. With a shifting geopolitical landscape\, our software serves a national security mission of ever-increasing importance. Yet\, simultaneously\, the rapid pace of science and technology change places a premium on agility\, with a diversity of computing platforms and architectures coming online\, and with AI poised to revolutionize approaches to modern science. Ultimately\, an integration of artificial intelligence methodologies with the co-design of software and future computing architectures will allow new levels of physics fidelity\, numerical accuracy\, and efficiency in time to solution for the most challenging scientific workflows to address a broad spectrum of future\, big-science problems. \n  \nSnacks and refreshments will be provided!
URL:https://micde.umich.edu/event/lanl-xps-seminar-mark-w-schraad-division-leader-los-alamos-national-laboratory/
LOCATION:Johnson Rooms\, Lurie Engineering Center\, 3rd Floor LEC 3213ABC\, 1221 Beal Ave.\, Ann Arbor\, MI\, United States
CATEGORIES:Micde Seminar,MICDE Seminar Series,Scientific Computing
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DTSTART;TZID=America/Detroit:20230123T150000
DTEND;TZID=America/Detroit:20230123T160000
DTSTAMP:20230810T200557Z
CREATED:20221222T184418Z
LAST-MODIFIED:20230810T200557Z
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SUMMARY:MICDE Seminar: Albert Berahas Assistant Professor of Industrial and Operations Engineering at the University of Michigan
DESCRIPTION:Albert S. Berahas is an Assistant Professor in the Industrial and Operations Engineering department at the University of Michigan. Before joining the University of Michigan\, he was a Postdoctoral Research Fellow in the Industrial and Systems Engineering department at Lehigh University working with Professors Katya Scheinberg\, Frank Curtis and Martin Takáč. Prior to that appointment\, he was a Postdoctoral Research Fellow in the Industrial Engineering and Management Sciences department at Northwestern University working with Professor Jorge Nocedal. Berahas completed his PhD studies in the Engineering Sciences and Applied Mathematics (ESAM) department at Northwestern University in 2018\, advised by Professor Jorge Nocedal. He received his undergraduate degree in Operations Research and Industrial Engineering (ORIE) from Cornell University in 2009\, and in 2012 obtained an MS degree in Applied Mathematics from Northwestern University. Berahas’ research broadly focuses on designing\, developing and analyzing algorithms for solving large scale nonlinear optimization problems. Specifically\, he is interested in and has explored several sub-fields of nonlinear optimization such as: (i) general nonlinear optimization algorithms\, (ii) optimization algorithms for machine learning\, (iii) constrained optimization\, (iv) stochastic optimization\, (v) derivative-free optimization\, and (vi) distributed optimization. \n  \nALGORITHMS FOR DETERMINISTICALLY CONSTRAINED STOCHASTIC OPTIMIZATION \nStochastic gradient and related methods for solving stochastic optimization problems have been studied extensively in recent years. It has been shown that such algorithms and much of their convergence and complexity guarantees extend in straightforward ways when one considers problems involving simple constraints\, such as when one can perform projections onto the feasible region of the problem. However\, settings with general nonlinear constraints have received less attention\, and many of the approaches that have been proposed for solving such problems resort to using penalty or (augmented) Lagrangian methods\, which are often not the most effective strategies. In this work\, we propose and analyze stochastic optimization algorithms for deterministically constrained problems based on the sequential quadratic optimization (commonly known as SQP) methodology. We discuss the rationale behind our proposed techniques\, convergence in expectation and complexity guarantees for our algorithms\, and the results of preliminary numerical experiments that we have performed. This is joint work with Raghu Bollapragada\, Frank E. Curtis\, Michael O’Neill\, Daniel P. Robinson\, Jiahao Shi and Baoyu Zhou. \n  \n\nThe MICDE Winter 2023 Seminar Series is open to all. \nThis seminar is hosted by the Michigan Institute for Computational Discovery & Engineering (MICDE). Prof. Berahas will be hosted by Prof. Siqian Shen\, Associate Professor of Industrial and Operations Engineering and Associate Professor of Civil and Environmental Engineering. \nGraduate Certificate in Computational Discovery and Engineering\, and MICDE fellows\, please use this form to record your attendance. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/albert-berahas-assistant-professor-of-industrial-and-operations-engineering-university-of-michigan/
LOCATION:Johnson Rooms\, Lurie Engineering Center\, 3rd Floor LEC 3213ABC\, 1221 Beal Ave.\, Ann Arbor\, MI\, United States
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
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DTSTART;TZID=America/Detroit:20220915T150000
DTEND;TZID=America/Detroit:20220915T160000
DTSTAMP:20230713T164622Z
CREATED:20220818T193725Z
LAST-MODIFIED:20230713T164622Z
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SUMMARY:MICDE / IOE Seminar: Andreas Wächter\, Professor of Industrial Engineering and Management Sciences\, Northwestern University
DESCRIPTION:WATCH THE RECORDING HERE. \nAndreas Wächter is a Professor in the Department of Industrial Engineering and Management Sciences at Northwestern University. His research interests include the design\, analysis\, implementation and application of numerical algorithms for nonlinear continuous and mixed-integer optimization. He obtained his master’s degree in Mathematics at the University of Cologne\, Germany\, in 1997\, and this Ph.D. in Chemical Engineering at Carnegie Mellon University in 2002. Before joining Northwestern University in 2011\, he was a Research Staff Member in the Department of Mathematical Sciences at IBM Research in Yorktown Heights\, NY. He is a recipient of the 2011 Wilkinson Prize for Numerical Software and the 2009 Informs Computing Society Prize for his work on the open-source optimization package Ipopt. \n\n\n\nTHE ARPA-E GRID OPTIMIZATION COMPETITION\nIn recent years\, the US Advanced Research Projects Agency-Energy (ARPA-E) has been organizing the “Grid Optimization Competition.” To participate\, teams from academia and industry submitted computer program implementations of specialized algorithms for solving large realistic Security-Constrained Optimal Power Flow (SCOPF) problems. The performance of the solvers was tested and ranked independently by the organizers\, using large-scale real-life instances. The goal of SCOPF is the determination of the most cost-efficient operation of an electrical power grid in a such way that it can withstand contingencies in the form of outages of any its components. Mathematically\, this is an extremely large-scale two-stage nonlinear and nonconvex optimization problem. In this presentation\, the approach of several teams will be described\, including that of our own GO-SNIP team that placed second in the first challenge. \nFollowing the seminar IOE is holding a small reception in IOE Commons – 1709\, snacks and refreshments will be served. \n\nThe MICDE Fall 2022 Seminar Series is open to all. University of Michigan faculty and students interested in power grid optimization are encouraged to attend. \nThis seminar is cohosted by the Michigan Institute for Computational Discovery & Engineering (MICDE) and the Department of Industrial and Operations Engineering. Prof. Wächter will be hosted by Dr. Salar Fattahi\, Assistant Professor of Industrial and Operations Engineering and Dr. Siqian Shen\, Associate Professor of Industrial and Operations Engineering and Associate Professor of Civil and Environmental Engineering. \nThis event is in-person only! \nGraduate Certificate in Computational Discovery and Engineering\, and MICDE fellows\, please use this form to record your attendance. \nQuestions? Email MICDE-events@umich.edu \n 
URL:https://micde.umich.edu/event/micde-ioe-seminar-andreas-wachter-professor-of-industrial-engineering-and-management-sciences-northwestern-university/
LOCATION:Johnson Rooms\, Lurie Engineering Center\, 3rd Floor LEC 3213ABC\, 1221 Beal Ave.\, Ann Arbor\, MI\, United States
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
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DTSTART;TZID=America/Detroit:20200115T120000
DTEND;TZID=America/Detroit:20200115T130000
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SUMMARY:MICDE Seminar: Allen Sanderson\, Research Scientist\, Scientific Computing and Imaging Institute\, The University of Utah
DESCRIPTION:Bio: Allen Sanderson\, Ph.D. is a Research Scientist at the University of Utah’s Scientific Computing and Imaging Institute. His interest lies in visualization and analysis of large data coming from application areas ranging from plasma physics to combustion. Recently he has focused on new ways to utilize in situ data analysis and visualization which often has him working directly on the science application infrastructure. \nTeasing out Ephemeral Data from HPC Applications for In Situ Visualization and Analysis\nIt is well known that as HPC applications have grown\, I/O has become a bottleneck\, which has required scientists to turn to in situ tools for data exploration. The focus of this exploration has typically been on simulation data. However\, applications also produce ephemeral data that is optionally written to disk for post hoc analysis\, but not otherwise saved or utilized by the application in subsequent time steps. One example of ephemeral data is runtime performance data. In this talk I will present the infrastructure implemented for efficiently collecting this and other data within the Uintah framework which was coupled to VisIt’s in situ toolkit for analysis and visualization. This collection and coupling allows performance data to be visualized using multiple domains giving insight previously not possible. As part this coupling\, we take advantage of VisIt’s in situ custom user interface to create a “simulation dashboard” that allows for in situ computational steering and visual debugging allowing for improvements in the development and simulation workflow. \nDr. Sanderson is being hosted by the Scientific Computing Student Club [SC2].  If you would like to meet with him during his visit\, please send an email to micde-events@umich.edu. Limited lunch will be provided. 
URL:https://micde.umich.edu/event/micde-seminar-allen-sanderson/
LOCATION:Johnson Rooms\, Lurie Engineering Center\, 3rd Floor LEC 3213ABC\, 1221 Beal Ave.\, Ann Arbor\, MI\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190924T160000
DTEND;TZID=America/Detroit:20190924T170000
DTSTAMP:20230905T171404Z
CREATED:20230905T171404Z
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SUMMARY:Graduate Studies in Computational & Data Sciences Info Session – North Campus
DESCRIPTION:Learn about graduate programs that will prepare you for success in computationally intensive fields — pizza and pop provided \n\nThe Ph.D. in Scientific Computing is open to all Ph.D. students who will make extensive use of large-scale computation\, computational methods\, or algorithms for advanced computer architectures in their studies. It is a joint degree program\, with students earning a Ph.D. from their current departments\, “… and Scientific Computing” — for example\, “Ph.D. in Aerospace Engineering and Scientific Computing.”\nThe Graduate Certificate in Computational Discovery and Engineering trains graduate students in computationally intensive research so they can excel in interdisciplinary HPC-focused research and product development environments. The certificate is open to all students currently pursuing Master’s or Ph.D. degrees at the University of Michigan.\nThe Graduate Certificate in Computational Neuroscience trains the next generation of interdisciplinary neuroscientists. The certificate program is open to all students pursuing Master’s or Ph.D. degrees at the University of Michigan.\nThe Graduate Certificate in Data Science is focused on developing core proficiencies in data analytics:\n1) Modeling — Understanding of core data science principles\, assumptions and applications;\n2) Technology — Knowledge of basic protocols for data management\, processing\, computation\, information extraction\, and visualization;\n3) Practice — Hands-on experience with real data\, modeling tools\, and technology resources.
URL:https://micde.umich.edu/event/info-session-fall2019-north/
LOCATION:Johnson Rooms\, Lurie Engineering Center\, 3rd Floor LEC 3213ABC\, 1221 Beal Ave.\, Ann Arbor\, MI\, United States
CATEGORIES:Info Session
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190912T143000
DTEND;TZID=America/Detroit:20190912T153000
DTSTAMP:20230905T171404Z
CREATED:20230905T171404Z
LAST-MODIFIED:20230905T171404Z
UID:10000242-1568298600-1568302200@micde.umich.edu
SUMMARY:MICDE Seminar: Ramanathan Vishnampet\, Senior Research Engineer\, ExxonMobil Upstream Integrated Solutions
DESCRIPTION:Bio: Ramanathan Vishnampet is a Computational Data Scientist at the Global Business Lines Analytics & Optimization group at ExxonMobil Upstream Integrated Solutions. He graduated with a Ph.D. in Theoretical and Applied Mechanics from the University of Illinois at Urbana-Champaign\, where his dissertation focused on an exact and consistent adjoint method for high-fidelity discretization of the compressible flow equations. Ramanathan started as a Senior Research Engineer at ExxonMobil in 2015\, where he worked in the Process Stratigraphy team\, an integrated team including Computational Scientists\, Geoscientists\, Seismic Interpreters\, and Stratigraphers. He helped develop a physics-based stratigraphic model for studying deepwater stratigraphy and showed the emergence of chaotic dynamics and self-organization that limit the ability of traditional model inversion techniques to be applied to the forward model. In his current team\, Ramanathan is working on a scheduling problem for ExxonMobil’s Unconventionals asset base using heuristics and discrete optimization. He is also leading his section’s efforts in adopting lean and agile software development practices\, cloud-based deployment using a service architecture\, and DevOps processes. Ramanathan’s hobbies include cooking\, traveling\, and spending time with his daughter. \nPrediction under chaos using a depth-averaged model of turbidity currents\nIn this talk\, I will demonstrate a forward stratigraphic model based on depth-averaged governing equations for the flow of submarine turbidity currents over an erodible bed. This model is being used with some success by the Process Stratigraphy team at ExxonMobil to generate stratigraphic models for deepwater environments of deposition. The mathematical model consists of a system of nonlinear hyperbolic PDEs\, with an additional so-called Exner equation for modeling the flow-bed sediment exchange and their bedload transport. The Exner equation plays a key role since a (slow time scale) change in the gradient of the bed influences the (fast time scale) momentum of the flow. The transport equations\, along with closure models for sediment transport\, TKE balance\, and water entrainment\, are solved using a first-order finite-volume method with a HLLC approximate Riemann solver and integrated using an explicit Euler scheme. The model shows the emergence of self-organized patterns in the deposits\, including the creation of bedforms\, channel formation\, and avulsions\, consistent with observations of modern systems and lab experiments. These occur even with uniform boundary conditions and symmetric initial conditions. The initial disturbances that trigger these mechanisms are ostensibly sourced by floating-point roundoff errors. An ensemble of simulations with slightly different initial conditions are used to analyze statistics on shapes of geomorphic elements and grain size distributions. The objective is to assess whether and under what conditions such a numerical model can be predictive and quantify the uncertainty in the results arising due to the irreducible chaos in the dynamical system. \nDr. Vishnampet is being hosted by Prof. Capecelatro (ME). If you would like to meet with him during his visit\, please send an email to micde-events@umich.edu.  
URL:https://micde.umich.edu/event/fall2019-vishnampet-exxonmobil/
LOCATION:Johnson Rooms\, Lurie Engineering Center\, 3rd Floor LEC 3213ABC\, 1221 Beal Ave.\, Ann Arbor\, MI\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
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BEGIN:VEVENT
DTSTART;TZID=UTC:20190124T163000
DTEND;TZID=UTC:20190124T173000
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SUMMARY:Graduate Studies in Computational & Data Sciences Info Session - North Campus
DESCRIPTION:Learn about graduate programs that will prepare you for success in computationally intensive fields — pizza and pop provided \n\nThe Ph.D. in Scientific Computing is open to all Ph.D. students who will make extensive use of large-scale computation\, computational methods\, or algorithms for advanced computer architectures in their studies. It is a joint degree program\, with students earning a Ph.D. from their current departments\, “… and Scientific Computing” — for example\, “Ph.D. in Aerospace Engineering and Scientific Computing.”\nThe Graduate Certificate in Computational Discovery and Engineering trains graduate students in computationally intensive research so they can excel in interdisciplinary HPC-focused research and product development environments. The certificate is open to all students currently pursuing Master’s or Ph.D. degrees at the University of Michigan.\nThe Graduate Certificate in Data Science is focused on developing core proficiencies in data analytics:\n1) Modeling — Understanding of core data science principles\, assumptions and applications;\n2) Technology — Knowledge of basic protocols for data management\, processing\, computation\, information extraction\, and visualization;\n3) Practice — Hands-on experience with real data\, modeling tools\, and technology resources.\nThe Graduate Certificate in Computational Neuroscience provides training in interdisciplinary computational neuroscience to graduate students in experimental neuroscience programs and to graduate students in quantitative science programs\, such as physics\, biophysics\, mathematics and engineering. The curriculum includes required core computational neuroscience courses and coursework outside of the student’s home department research focus\, i.e. quantitative coursework for students in experimental programs\, and neuroscience coursework for students in quantitative programs.
URL:https://micde.umich.edu/event/graduate-studies-in-computational-data-sciences-info-session-north-campus-f2018-2/
LOCATION:Johnson Rooms\, Lurie Engineering Center\, 3rd Floor LEC 3213ABC\, 1221 Beal Ave.\, Ann Arbor\, MI\, United States
CATEGORIES:Info Session
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20180924T163000
DTEND;TZID=UTC:20180924T173000
DTSTAMP:20230905T171420Z
CREATED:20230905T171420Z
LAST-MODIFIED:20230905T171420Z
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SUMMARY:Graduate Studies in Computational & Data Sciences Info Session - North Campus
DESCRIPTION:Learn about graduate programs that will prepare you for success in computationally intensive fields — pizza and pop provided \n\nThe Ph.D. in Scientific Computing is open to all Ph.D. students who will make extensive use of large-scale computation\, computational methods\, or algorithms for advanced computer architectures in their studies. It is a joint degree program\, with students earning a Ph.D. from their current departments\, “… and Scientific Computing” — for example\, “Ph.D. in Aerospace Engineering and Scientific Computing.”\nThe Graduate Certificate in Computational Discovery and Engineering trains graduate students in computationally intensive research so they can excel in interdisciplinary HPC-focused research and product development environments. The certificate is open to all students currently pursuing Master’s or Ph.D. degrees at the University of Michigan.\nThe Graduate Certificate in Data Science is focused on developing core proficiencies in data analytics:\n1) Modeling — Understanding of core data science principles\, assumptions and applications;\n2) Technology — Knowledge of basic protocols for data management\, processing\, computation\, information extraction\, and visualization;\n3) Practice — Hands-on experience with real data\, modeling tools\, and technology resources.
URL:https://micde.umich.edu/event/graduate-studies-in-computational-data-sciences-info-session-north-campus-f2018/
LOCATION:Johnson Rooms\, Lurie Engineering Center\, 3rd Floor LEC 3213ABC\, 1221 Beal Ave.\, Ann Arbor\, MI\, United States
CATEGORIES:Info Session
GEO:42.2914823;-83.7138452
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20180410T143000
DTEND;TZID=America/Detroit:20180410T153000
DTSTAMP:20230905T171419Z
CREATED:20230905T171419Z
LAST-MODIFIED:20230905T171419Z
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SUMMARY:MICDE Seminar: Raul Radovitzky\, Department of Aeronautics and Astronautics\, Massachusetts Institute of Technology
DESCRIPTION:Bio: Raul Radovitzky is the Raymond L. Bisplinghoff Professor of Aeronautics and Astronautics at the Massachusetts Institute of Technology. He also serves as the Associate Director of the MIT Institute for Soldier Nanotechnologies\, where he also leads research efforts on Blast and Ballistic Protection. He received a Civil Engineer degree from the University of Buenos Aires in 1991\, A S. M. in Applied Mathematics from Brown University in 1995 and a Ph.D. in Aeronautical Engineering from the California Institute of Technology in 1998. His research interests are in the development of numerical methods for multi-scale modeling of complex material response as well as in the formulation and implementation of algorithms for large-scale simulation of the dynamic response of materials to extreme loading conditions with emphasis on material and structural failure. The methods his group has developed have led to significant advances in our understanding of the physical effects of blast waves on the brain. This has helped to develop strategies to protect against Traumatic Brain Injury. Dr. Radovitzky is an Associate Fellow of the American Institute of Aeronautics and Astronautics and a member of the National Football League Head\, Neck and Spine Injury Research Committee. \nExtension of the peridynamic theory of solids for the simulation of materials under extreme loadings\nThe prediction of material and structural failure remains one of the most difficult challenges in structural and solid mechanics. Complexity emerges from the fundamental multiscale aspect of the mechanics of fracture\, where the small-scale response is usually responsible for large-scale system damage and failure. In addition\, significant algorithmic challenges remain\, including the difficulty in representing fracture\, some fundamental numerical convergence issues in the presence of material damage; and computational robustness and scalability enabling large-scale simulations.\nIn this presentation\, I will describe our efforts on the investigation of the theory of peridynamics and its numerical implementation\, as a promising alternative approach for simulating extreme material response. Peridynamics is a relatively new\, nonlocal formulation of continuum mechanics based on integral equations. It includes a physical length scale and naturally supports the presence of discontinuities in the solution field. As part of our work in this area\, we have proposed an extended formulation of the state theory of peridynamics addressing some fundamental issues present in the original theory. Specifically\, we have found that unphysical energy modes that do not contribute to the strain energy are allowed in the original formulation\, which\, in turn\, are responsible for the numerical instabilities commonly observed in peridynamic particle discretizations. In order to address this issue\, we introduce an extension of the constitutive correspondence framework based on bond-level nonlinear strain measures of the Seth-Hill type\, in direct analogy to local measures of deformation in continuum mechanics. We show that the numerical instabilities are eliminated when the numerical discretization is based on the extended theory.\nIn addition\, we have explored different approaches for incorporating material damage and fracture within the context of peridynamics formulations. I will describe one approach based on continuum damage models and another one particularly suited for brittle fracture.\nThe algorithms resulting from a particle discretizations of the proposed extended peridynamics framework have been implemented in our research code ΣMIT. I will provide examples illustrating the key numerical properties of the method. In addition\, I will show numerical results that demonstrate the ability of the method to capture experimentally observed ballistic limit curves for ductile materials\, as well as realistic fracture patterns in brittle materials subjected to projectile impact loadings. \nProf. Radovitzky is being hosted by Prof. Garikipati (Mechanical Engineering). If you would like to meet with him\, please send an email to micde-contact@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-raul-radovitzky-mit/
LOCATION:Johnson Rooms\, Lurie Engineering Center\, 3rd Floor LEC 3213ABC\, 1221 Beal Ave.\, Ann Arbor\, MI\, United States
CATEGORIES:MICDE Seminar Series
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20180402T140000
DTEND;TZID=America/Detroit:20180402T150000
DTSTAMP:20230905T171419Z
CREATED:20230905T171419Z
LAST-MODIFIED:20230905T171419Z
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SUMMARY:MICDE Seminar: Amanda Randles\, Department of Biomedical Engineering\, Duke University
DESCRIPTION:Bio: Amanda Randles is an assistant professor of Biomedical Engineering at Duke University. She has courtesy appointments in the departments of Mechanical Engineering and Material Science\, Computer Science and Mathematics\, and is a member of the Duke Cancer Institute. She got her Ph.D. from Harvard University in 2013\, and has been the recipient of the Lawrence Fellowship (Lawrence Livermore National Lab.)\, the Anita Borg Memorial Scholarship (Google)\, and the George Michael Memorial High Performance Computing Fellowship (ACM/IEEE) among many accomplishments in her early career. Her research in biomedical simulation and high performance computing focuses on the development of new computational tools that she uses to provide insight into the localization and development of human diseases ranging from atherosclerosis to cancer. \nMassively Parallel Simulations of Hemodynamics in the Human Vasculature\nThe recognition of the role hemodynamic forces have in the localization and development of disease has motivated large-scale efforts to enable patient-specific simulations. When combined with computational approaches that can extend the models to include physiologically accurate hematocrit levels in large regions of the circulatory system\, these image-based models yield insight into the underlying mechanisms driving disease progression and inform surgical planning or the design of next generation drug delivery systems. Building a detailed\, realistic model of human blood flow\, however\, is a formidable mathematical and computational challenge. The models must incorporate the motion of fluid\, intricate geometry of the blood vessels\, continual pulse-driven changes in flow and pressure\, and the behavior of suspended bodies such as red blood cells. In this talk\, I will discuss the development of HARVEY\, a parallel fluid dynamics application designed to model hemodynamics in patient-specific geometries. I will cover the methods introduced to reduce the overall time-to-solution and enable near-linear strong scaling on up to 1\,572\,864 core of the IBM Blue Gene/Q supercomputer. Finally\, I will present the expansion of the scope of projects to address not only vascular diseases\, but also treatment planning and the movement of circulating tumor cells in the bloodstream. \nProf. Randles is being hosted by Dr. Carrasco-Teja (MICDE). If you would like to meet her during her visit please send an email to mcteja@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-amanda-randles-duke-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
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20180122T163000
DTEND;TZID=America/Detroit:20180122T173000
DTSTAMP:20230905T171417Z
CREATED:20230905T171417Z
LAST-MODIFIED:20230905T171417Z
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SUMMARY:Graduate programs in computational science — INFO SESSIONS
DESCRIPTION:Students interested in computational science are invited to learn about graduate programs that will prepare them for success in computationally intensive fields. Pizza and pop will be provided. \nTwo sessions are scheduled:\n\nMonday\, Jan. 22\, 4:30 – 5:30 p.m.\, Johnson Rooms\, Lurie Engineering Center (North Campus)\nThursday\, Jan. 25\, 4:30 – 5:30 p.m.\, 2001 LSA Building (Central Campus)\n\nThe sessions will address:\n\n\nThe Ph.D. in Scientific Computing\, which is open to all Ph.D. students who will make extensive use of large-scale computation\, computational methods\, or algorithms for advanced computer architectures in their studies. It is a joint degree program\, with students earning a Ph.D. from their current departments\, “… and Scientific Computing” — for example\, “Ph.D. in Aerospace Engineering and Scientific Computing.” \n\n\nThe Graduate Certificate in Computational Discovery and Engineering\, which trains graduate students in computationally intensive research so they can excel in interdisciplinary HPC-focused research and product development environments. The certificate is open to all students currently pursuing Master’s or Ph.D. degrees at the University of Michigan. The practicum option for Master’s students through the Multidisciplinary Design Program will be explained.
URL:https://micde.umich.edu/event/graduate-studies-in-computational-data-sciences-info-session-north-campus-3/
LOCATION:Johnson Rooms\, Lurie Engineering Center\, 3rd Floor LEC 3213ABC\, 1221 Beal Ave.\, Ann Arbor\, MI\, United States
CATEGORIES:Featured Events
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20171019T153000
DTEND;TZID=America/Detroit:20171019T163000
DTSTAMP:20230905T171415Z
CREATED:20230905T171415Z
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SUMMARY:MICDE Seminar: Panos Papadopoulos\, Department of Mechanical Engineering\, University of California\, Berkeley
DESCRIPTION:Bio: Panos Papadopoulos is a Professor of Mechanical Engineering at the University of California\, Berkeley\, and director of the Computational Solid Mechanics Laboratory. After obtaining his Diploma in Civil Engineering from the Aristotle University\, Greece\, he moved to California to pursue his graduate studies. He obtained his M. Sc. and Ph.D. in Civil Engineering from UC Berkeley. His research involves experimental\, analytical and computational studies of several mechanics systems. Prof. Papadopoulus develops and applied the finite element method to problems in biomechanics\, dynamics of pseudo-rigid bodies\, mechanics of continues media\, plasticity\, materials science and contact mechanics. \nMultiscale Modeling in Continuum Mechanics: A connection to the Irving-Kirkwood procedure\nThis talk describes a method for extending the classical Irving-Kirkwood procedure used in statistical mechanics for extracting local fluxes to the problem of continuum-on-continuum multiscale modeling. Expressions for stress and heat flux derived here are contrasted to those obtained using the standard Hill-Mandel approach. The polar nature of the macroscopic solid and the role of multiscale invariance are also addressed in the context of this method. Applications are explored within the finite element-based homogenization of solids. \nProf. Papadopoulos is being hosted by Prof. Garikipati (Mechanical Engineering). If you would like to meet with him please send an email to mcteja@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-panos-papadopoulos-department-of-mechanical-engineering-university-of-california-berkeley/
LOCATION:Johnson Rooms\, Lurie Engineering Center\, 3rd Floor LEC 3213ABC\, 1221 Beal Ave.\, Ann Arbor\, MI\, United States
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20170620T090000
DTEND;TZID=America/Detroit:20170620T100000
DTSTAMP:20230905T171438Z
CREATED:20230905T171438Z
LAST-MODIFIED:20230905T171438Z
UID:10000088-1497949200-1497952800@micde.umich.edu
SUMMARY:ARC-TS Town Hall on Next Generation HPC Cluster
DESCRIPTION:The University of Michigan is beginning the process of building our next generation HPC platform\, “Big House.”  Flux\, the shared HPC cluster\, has reached the end of its useful life. Flux has served us well for more than five years\, but as we move forward with replacement\, we want to make sure we’re meeting the needs of the research community. \nARC-TS will be holding a series of town halls to take input from faculty and researchers on the next HPC platform to be built by the University.  These town halls are open to anyone. \nYour input will help to ensure that U-M is on course for providing HPC\, so we hope you will make time to attend one of these sessions. If you cannot attend\, please email hpc-support@umich.edu with any input you want to share.
URL:https://micde.umich.edu/event/arc-ts-town-hall-on-next-generation-hpc-cluster/
LOCATION:Johnson Rooms\, Lurie Engineering Center\, 3rd Floor LEC 3213ABC\, 1221 Beal Ave.\, Ann Arbor\, MI\, United States
CATEGORIES:Flux,High Performance Computing
ORGANIZER;CN="Advanced Research Computing":MAILTO:arc-contact@umich.edu
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END:VEVENT
END:VCALENDAR