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-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: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 BEGIN:DAYLIGHT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:EDT DTSTART:20240310T070000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:EST DTSTART:20241103T060000 END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTART;TZID=America/Detroit:20231207T150000 DTEND;TZID=America/Detroit:20231207T160000 DTSTAMP:20260604T032605 CREATED:20231106T145227Z LAST-MODIFIED:20231215T040145Z UID:10000662-1701961200-1701964800@micde.umich.edu SUMMARY:MICDE Faculty seminar: Philip Roe\, Emeritus Professor\, Aerospace Engineering U-M DESCRIPTION:Zoom link \nBio:  Philip Roe is an Emeritus Professor of Aerospace Engineering at the University of Michigan. He is recognized for his pioneering work in the field of Computational Fluid Dynamics and Magnetohydrodynamics. Roe made many fundamental contributions to the development of high-resolution schemes for hyperbolic conservation laws. He is best known for his work on the flux difference splitting for compressible flows with shocks\, typically referred to as the Roe scheme. \nMusings of a Computational Philosopher\nPhilosophy sets a great story by asking the right questions. Indeed a correct answer to the wrong question is seldom of any value. You can even obtain tenure\, I am told\, by asking questions that you cannot yet answer. For the past decade\, I have been trying to ask the right questions about computing compressible flow\, and I hope here to provide a glimpse of the answers. \nA “good” algorithm should “obviously” be accurate\, cheap\, and robust. Of these three desiderata\, I will try here to clarify the notion of accuracy. Although clearly a good thing\, it is almost always defined asymptotically in terms of the behavior at small mesh size or low frequency. This sets precise goals for analysis\, and although accuracy can be achieved in this sense\, in practice we often cannot afford the asymptotic regime. Moreover\, when we deal with compressible flow\, we are forced to deal with high frequencies. We require in fact only rather modest accuracy at low frequency\, but must extend this into the high frequency regime\, and doing this will require answering different questions. I will discuss a double-pronged approach to finding these questions and their answers. \nThis approach demands that the information flow in the computer should closely match that in real life. A great advance toward this was made by introducing Godunov-type methods\, but these merely distinguish left from right\, and their reliance on one-dimensional physics has many drawbacks. However\, for many kinds of problem there are integral solutions to the linear initial-value problem in multiple dimensions. My first prong is to show how these can be used to derive algorithms for linear and nonlinear problems for compressible fluid flow and other applications. These algorithms have remarkable properties\, including true incompressible limits and automatic boundary conditions. The information flow is different for advective and non-advective modes of the solution. \nAs a second way to achieve correct information flow\, I employ solution derivatives as degrees of freedom. This Hermitian representation is common in computer graphics and signal processing but almost unknown in CFD. Its great benefit consists of keeping the stencil compact. This brings about sharp discontinuities\, extends the spectrum and reduces communication overheads. Recently\, with my graduate student Iman Samani\, I have used both prongs of my approach to produce fifth-order solutions for linear elastodynamics on unstructured grids with automatic handling of material interfaces and remote boundaries. I will present these results\, summarize what remains to be done and describe some target applications. URL:https://micde.umich.edu/event/micde-faculty-seminar-philip-roe-emeritus-professor-aerospace-engineering-u-m/ LOCATION:1109 FXB\, 1320 Beal Ave.\, Ann Arbor\, MI\, United States CATEGORIES:Aerospace Engineering,Micde Seminar,MICDE Seminar Series,Michigan Engineering ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/11/Philip-Roe.png GEO:42.290906;-83.713503 X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=1109 FXB 1320 Beal Ave. Ann Arbor MI United States;X-APPLE-RADIUS=500;X-TITLE=1320 Beal Ave.:geo:-83.713503,42.290906 END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Detroit:20231205T120000 DTEND;TZID=America/Detroit:20231205T130000 DTSTAMP:20260604T032605 CREATED:20230926T191303Z LAST-MODIFIED:20231204T192114Z UID:10000654-1701777600-1701781200@micde.umich.edu SUMMARY:MICDE Ph.D. Student Seminars 2023-2024: Jeffrey Hatch DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public\, but we ask that you register to attend the seminar. If you have any questions\, please email micde-events@umich.edu. \nComputational Methods in Chemistry\nAbstract coming soon… \nJeffrey Hatch\, Ph.D. candidate in Chemistry and Scientific Computing \nBio coming soon… \nRegister to attend this seminar URL:https://micde.umich.edu/event/phd-seminar-jeffrey-hatch/ LOCATION:2022 South Thayer Building CATEGORIES:Computation,Computational Modeling,Computational Science,Engineering,Free,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,In Person,Interdisciplinary,Michigan Engineering,Phd Seminar,Prospective Graduate Students,Rackham,Science,Scientific Computing,Seminar,Sessions,Talk ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/09/Template-Speaker-3.png END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Detroit:20231128T120000 DTEND;TZID=America/Detroit:20231128T130000 DTSTAMP:20260604T032605 CREATED:20230914T150100Z LAST-MODIFIED:20260522T152930Z UID:10000641-1701172800-1701176400@micde.umich.edu SUMMARY:MICDE Ph.D. Student Seminars 2023-2024: Guoer Liu DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public\, but we ask that you register to attend the seminar. If you have any questions\, please email micde-events@umich.edu. \nRegister to attend this seminar \nWhen Is Big Data Biased?\nUsing automation technology to gather and disseminate information to the public is commonly viewed as a government-led effort to enhance oversight and address the principal-agent problem in bureaucracy. However\, focusing on the expansion of China’s automatic ambient air quality monitoring network in the last decade (2012-2022)\, I argue that technology is being utilized as a tool to emphasize optics but overlook the substantive problems. I illustrate the idea with multiple original georeferenced data sets on the automatic monitoring network\, pollution sources\, and satellite-derived vegetation density across time and space. I show that\, while the automation initiative has improved the data quality in some ways\, the undersupply of automatic monitoring stations\, over-represented clean locations\, and non-random missing pollution records continue to contribute to inaccurate air pollution information. As long as political incentives to manipulate information persist\, actors can mold technology that operates without human intervention to serve their own interests. \nGuoer Liu\, Ph.D. candidate in Political Science and Scientific Computing\nGuoer Liu is a Ph.D. candidate in Political Science. Her dissertation project\, ‘‘From Oversight to Overlook’’ investigates how political determinants distort the technology infrastructure and create seemingly credible but inaccurate information to the public. \nAdvisors: Mary Gallagher\, Charles Shipan \nRegister to attend this seminar URL:https://micde.umich.edu/event/phd-seminar-guoer-liu/ LOCATION:2022 South Thayer Building CATEGORIES:Computation,Computational Modeling,Computational Science,Engineering,Free,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,In Person,Interdisciplinary,Michigan Engineering,Phd Seminar,Prospective Graduate Students,Rackham,Science,Scientific Computing,Seminar,Sessions,Talk ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/09/Template-Speaker-2.png END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Detroit:20231127T140000 DTEND;TZID=America/Detroit:20231127T170000 DTSTAMP:20260604T032605 CREATED:20230830T164539Z LAST-MODIFIED:20260522T154727Z UID:10000625-1701093600-1701104400@micde.umich.edu SUMMARY:Women in Computational Science Mini-Symposium (DISCOVER) DESCRIPTION:Women in Computational Science\n \n \n \n \n \n The Women in Computational Science Symposium is the inaugural event for MICDE’s DISCOVER (Diversity and Innovation in Scientific Computing: Opportunities for Valuing Exploration and Representation) mini-symposium series. This mini-symposium provides a unique opportunity to delve into the pioneering research conducted by women in computational science while also gaining insight into their personal experiences and the challenges they face as researchers.\nThis year’s Women in Computational Science Symposium features: \nKeynote speaker: Katrin Heitmann\, Deputy Division Director Argonne National Laboratory – @ 3 pm\nBio: Katrin Heitmann is the deputy director of Argonne’s High Energy Physics division\, and a physicist and computational scientist. She is also a Senior Associate for the Kavli Institute for Cosmological Physics at the University of Chicago and a member of NAISE at Northwestern. Before joining Argonne\, Katrin was a staff member at Los Alamos National Laboratory. Her research currently focuses on computational cosmology\, in particular on trying to understand the causes for the accelerated expansion of the Universe. She is responsible for large simulation campaigns with HACC and for the tools in the associated analysis library\, CosmoTools. Katrin is a member of several major astrophysical surveys that aim to shed light on this question and is currently the Spokesperson for the LSST Dark Energy Science Collaboration. \nExploring the Dark Universe \nCosmology – the study of the origin\, evolution\, and constituents of the Universe – is now entering one of its most scientifically exciting phases. Three decades of surveying the sky have culminated in the celebrated “Cosmological Standard Model”. Yet\, two of its key pillars\, dark matter\, and dark energy – together accounting for 95% of the mass-energy of the Universe – remain mysterious. Next-generation observatories will open new routes to understand the true nature of the “Dark Universe”. These observations will pose tremendous challenges on many fronts – from the sheer size of the data that will be collected to its modeling and interpretation. The interpretation of the data requires sophisticated simulations on the world’s largest supercomputers. The cost of these simulations\, the uncertainties in our modeling abilities\, and the fact that we have only one Universe that we can observe opposed to carrying out controlled experiments\, all come together to create a major test for statistical methods of data analysis. In this talk\, I will give a brief introduction to the Dark Universe and outline the challenges ahead. I will describe how complex\, large-scale simulations will be used to extract the cosmological information from ongoing and next-generation surveys. \nGuest speakers @ 2 pm\nLiz Livingston\, PhD candidate in Mechanical Engineering and Scientific Computing at U-M \nTitle: Data to Differential Equations – Discovering Mathematical Models for Biological Systems \nBio: Liz Livingston is a 5th year PhD candidate in Mechanical Engineering and Scientific Computing at the University of Michigan\, advised by Professor Krishna Garikipati and Professor Alberto Figueroa. Her research focuses on data-driven modeling of biological systems. This work spans a range of topics including biomechanics\, numerical methods\, and high-performance computing. She received her BS and MS degrees from the University of Illinois at Urbana-Champaign where she studied the strength and microstructure of bone. Liz enjoys teaching and cultivates this interest through hands-on experience\, outreach\, and involvement in the American Society for Engineering Education (ASEE). \nAbstract: Complex phenomena\, such as those observed in biological systems\, can typically be modeled with partial differential equations (PDEs). Finding governing equations can be a daunting task\, often involving simplifications to the system such that the PDE does not fully capture the physics of the problem. Instead of reducing the complexity of the system with successive approximations\, the governing PDE can be discovered using data. One of the fastest and most popular techniques is machine learning\, where a surrogate is found as an approximation to the function. Alternatively\, inference techniques may be used to identify the strong or weak form of the governing equation via parameter estimation. The tools we develop for the discovery of governing equations have applications in many complex systems\, including biological ones such as flow through a stenosed artery and fracture in soft tissues. The goal of my PhD thesis is to develop and improve these mathematical methods to help expand our understanding of complex biological systems. \n  \nRachel Niemer\, Managing Director of WISE (Women in Science and Engineering) \nTitle: Who is WISE for and what should we do? Exploring levers of change to foster equity in STEM \nWISE info: The University of Michigan is at the forefront of equality in science and engineering\, and our focus on diversity\, equity\, and inclusion spans multiple dimensions\, including gender\, race\, SES\, first generation status\, to name a few. The University of Michigan’s Women in Science and Engineering (WISE) unit aims to increase the participation by women and gender minorities in careers in science\, technology\, engineering and mathematics\, and to foster their academic and professional success. We do this by cultivating students’ skills to thrive in STEM\, strengthening the community working toward STEM equity\, and working to mitigate systemic forces that impede retention of women\, and individuals from other historically underrepresented groups\, in STEM. \nAbstract: As we look at the evolving landscape of where women\, and other individuals from historically marginalized groups\, thrive and persist in STEM\, it makes sense to ask why more progress hasn’t been made. Women in Science and Engineering has been a resource for U-M students in STEM since 1980. Over that time\, WISE\, and similar units at other institutions\, have experimented with a range of interventions to help women thrive in STEM. What if we chose the wrong levers for change? Are there radically new ways we might support efforts to graduate more STEM majors from minoritized communities? This presentation will explore different models for advancing STEM equity. \nPanel discussion on navigating scientific careers – @ 4:10 pm\n\n\n\nKatrin Heitmann\, Deputy Division Director Argonne National Laboratory\nLisa Mesaros\, Vice President\, Product Management\, Simulation and Test Solutions at Siemens Digital Industries Software\nLiz Livingston\, Clare Boothe Luce Fellow & PhD candidate in Mechanical Engineering and Scientific Computing\, University of Michigan\nRachel Niemer\, Managing Director of WISE (Women in Science and Engineering)\, University of Michigan URL:https://micde.umich.edu/event/conference-symposiummicde-discover-mini-symposium/ LOCATION:West Hall – 340 CATEGORIES:Discover,DISCOVER Series,Featured Events,Micde,Micde Seminar END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Detroit:20231114T123000 DTEND;TZID=America/Detroit:20231114T130000 DTSTAMP:20260604T032605 CREATED:20230914T150100Z LAST-MODIFIED:20231103T200940Z UID:10000640-1699965000-1699966800@micde.umich.edu SUMMARY:MICDE Ph.D. Student Seminars: Jamie Holber DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public\, but we ask that you register to attend the seminar. If you have any questions\, please email micde-events@umich.edu. \nActive Learning for Physics Informed Data Sampling and Construction of Free Energy Representations\nUsing automation technology to gather and disseminate information to the public is commonly viewed as a government-led effort to enhance oversight and address the principal-agent problem in bureaucracy. However\, focusing on the expansion of China’s automatic ambient air quality monitoring network in the last decade (2012-2022)\, I argue that technology is being utilized as a tool to emphasize optics but overlook the substantive problems. I illustrate the idea with multiple original georeferenced data sets on the automatic monitoring network\, pollution sources\, and satellite-derived vegetation density across time and space. I show that\, while the automation initiative has improved the data quality in some ways\, the undersupply of automatic monitoring stations\, over-represented clean locations\, and non-random missing pollution records continue to contribute to inaccurate air pollution information. As long as political incentives to manipulate information persist\, actors can mold technology that operates without human intervention to serve their own interests. \nJamie Holber\, Ph.D. candidate in Applied Physics and Scientific Computing \nJamie Holber is a PhD Candidate in Applied Physics and Scientific Computing working in the Computational Physics Group in the Mechanical Engineering Department. \nAdvisor: Krishna Garikipati \nRegister to attend this seminar URL:https://micde.umich.edu/event/phd-seminar-jamie-holber/ LOCATION:2022 South Thayer Building CATEGORIES:Computation,Computational Modeling,Computational Science,Engineering,Free,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,In Person,Interdisciplinary,Michigan Engineering,Phd Seminar,Prospective Graduate Students,Rackham,Science,Scientific Computing,Seminar,Sessions,Talk ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/09/20231114-Jamie-Holber.png END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Detroit:20231114T080000 DTEND;TZID=America/Detroit:20231114T190000 DTSTAMP:20260604T032605 CREATED:20231020T163041Z LAST-MODIFIED:20231020T163041Z UID:10000660-1699948800-1699988400@micde.umich.edu SUMMARY:Conference / Symposium:U-M Data Science & AI Summit 2023 DESCRIPTION:The U-M Data Science and AI Summit is the largest annual data science and AI event on campus. This event brings together the U-M data science and AI research community and their external collaborators to build research vision and collaboration. It also showcases the breadth and depth of U-M data science and AI research\, from theory and methodology development to the transformative use of data and AI to address scientific and societal challenges in all domains. The event is free for all attendees (U-M faculty\, staff\, and trainees\, as well as industry\, government and community members).\nTo view full Summit schedule\, please visit the event webpage at https://midas.umich.edu/midas-summit-2023/.\nKeynotes:\nSuresh Venkatasubramanian\, Director\, Center for Technological Responsibility\, Reimagination\, and Redesign\, Data Science Institute at Brown University; Professor of Data Science and Computer Science\, Brown University – Key player for the White House Blueprint of an AI Bill of Rights\nJulianne Dalcanton\, Director\, Center for Computational Astrophysics\, Flatiron Institute – The origina and evolution of galaxies\nEmre Kiciman\, Senior Principal Researcher\, Microsoft Research – A New Frontier at the Intersection of Causality and LLMs\nSummit Sessions:\nA panel discussion on: Federal priorities and opportunities in data science and AI\nPanelists:\n– Laura Biven\, Data Science Technical Lead\, Office of Data Science Strategy\, National Institutes of Health\n– Michael Molnar\, Director\, Advanced Manufacturing National Program Office\, National Institute of Standards and Technology\n– Hector Muñoz-Avila\, Program Director and Cluster Lead\, the Information Integration and Informatics Program\, National Science Foundation\n– Alvaro Velasquez\, Program Manager\, Information Innovation Office\, Defense Advanced Research Projects Agency\nResearch vision talks by University of Michigan faculty researchers\nThe Propelling Original Data Science grant awardees showcase\nPoster session\, lightning talks\, and awards\nUniversity of Michigan data science and AI organizations showcase URL:https://micde.umich.edu/event/conference-symposiumu-m-data-science-ai-summit-2023-2/ LOCATION:Rackham Graduate School (Horace H.) CATEGORIES:Ai In Science And Engineering,Applications,Artificial Intelligence,big data,Biostatistics,Climate and Space Sciences and Engineering,Computational Modeling,Computational Science,Computational Social Science,computing,Data Curation,Data Science,data visualization,Deep Learning,Electrical And Computer Engineering,Electrical Engineering and Computer Science,Engineering,Faculty,Free,Graduate,Graduate Students,Industrial and Operations Engineering,Information and Technology,Interdisciplinary,Lecture,Machine Learning,Michigan Engineering,Midas,Natural Language Processing,Networking,Science,Social Impact,symposium END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Detroit:20231113T080000 DTEND;TZID=America/Detroit:20231113T190000 DTSTAMP:20260604T032605 CREATED:20231020T163040Z LAST-MODIFIED:20231020T163040Z UID:10000659-1699862400-1699902000@micde.umich.edu SUMMARY:Conference / Symposium:U-M Data Science & AI Summit 2023 DESCRIPTION:The U-M Data Science and AI Summit is the largest annual data science and AI event on campus. This event brings together the U-M data science and AI research community and their external collaborators to build research vision and collaboration. It also showcases the breadth and depth of U-M data science and AI research\, from theory and methodology development to the transformative use of data and AI to address scientific and societal challenges in all domains. The event is free for all attendees (U-M faculty\, staff\, and trainees\, as well as industry\, government and community members).\nTo view full Summit schedule\, please visit the event webpage at https://midas.umich.edu/midas-summit-2023/.\nKeynotes:\nSuresh Venkatasubramanian\, Director\, Center for Technological Responsibility\, Reimagination\, and Redesign\, Data Science Institute at Brown University; Professor of Data Science and Computer Science\, Brown University – Key player for the White House Blueprint of an AI Bill of Rights\nJulianne Dalcanton\, Director\, Center for Computational Astrophysics\, Flatiron Institute – The origina and evolution of galaxies\nEmre Kiciman\, Senior Principal Researcher\, Microsoft Research – A New Frontier at the Intersection of Causality and LLMs\nSummit Sessions:\nA panel discussion on: Federal priorities and opportunities in data science and AI\nPanelists:\n– Laura Biven\, Data Science Technical Lead\, Office of Data Science Strategy\, National Institutes of Health\n– Michael Molnar\, Director\, Advanced Manufacturing National Program Office\, National Institute of Standards and Technology\n– Hector Muñoz-Avila\, Program Director and Cluster Lead\, the Information Integration and Informatics Program\, National Science Foundation\n– Alvaro Velasquez\, Program Manager\, Information Innovation Office\, Defense Advanced Research Projects Agency\nResearch vision talks by University of Michigan faculty researchers\nThe Propelling Original Data Science grant awardees showcase\nPoster session\, lightning talks\, and awards\nUniversity of Michigan data science and AI organizations showcase URL:https://micde.umich.edu/event/conference-symposiumu-m-data-science-ai-summit-2023/ LOCATION:Rackham Graduate School (Horace H.) CATEGORIES:Ai In Science And Engineering,Applications,Artificial Intelligence,big data,Biostatistics,Climate and Space Sciences and Engineering,Computational Modeling,Computational Science,Computational Social Science,computing,Data Curation,Data Science,data visualization,Deep Learning,Electrical And Computer Engineering,Electrical Engineering and Computer Science,Engineering,Faculty,Free,Graduate,Graduate Students,Industrial and Operations Engineering,Information and Technology,Interdisciplinary,Lecture,Machine Learning,Michigan Engineering,Midas,Natural Language Processing,Networking,Science,Social Impact,symposium END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Detroit:20231109T110000 DTEND;TZID=America/Detroit:20231109T130000 DTSTAMP:20260604T032605 CREATED:20231102T175811Z LAST-MODIFIED:20231115T151403Z UID:10000661-1699527600-1699534800@micde.umich.edu SUMMARY:SciML Webinar: Lenz Fiedler - Efficient calculations of electronic structures with machine-learning models DESCRIPTION:https://umich.zoom.us/j/95111677727?pwd=V1Q5MkUwT2NpOFVhd0ZRVGR1YTM3Zz09 \n\nSpeaker: Lenz Fiedler (Helmholtz-Zentrum Dresden-Rossendorf)\nSession Chair: Michael Herbst (EPFL) \nAbstract: Quantum mechanical calculations of the electronic structure of matter enable accessing interesting thermodynamical properties without the need for prior experimental measurements. Therefore\, electronic structure calculations are of great interest in fields such as materials discovery or drug design. At the forefront of such simulations lies density functional theory (DFT)\, due to its excellent balance between computational accuracy and efficiency. Yet\, as pressing environmental and social issues shift the research focus to increasingly complicated systems and conditions\, even the most efficient of DFT implementations are approaching their limitations in terms of computational feasibility. A possible route to enable more complex calculations lies with machine learning (ML)\, i.e.\, algorithms that are capable of capturing complicated relationships based on large amounts of data.\nIn this talk\, Lenz Fiedler will talk about current contributions of Center for Advanced Systems Understanding\, Helmholtz-Zentrum Dresden-Rossendorf (CASUS) w.r.t. building ML models that replace conventional DFT calculations. More precisely\, Lenz will talk about the current state of the Materials Learning Algorithms library (MALA)\, which allows easy training and inference for ML-DFT models that are developed by CASUS in cooperation with Sandia National Laboraties and Oak Ridge National Laboratory. In contrast to comparable frameworks\, MALA allows full access to the electronic structure of compounds\, including volumetric data as well as scalar quantities of interest\, such as energies. It will be shown how MALA models can operate efficiently across phase boundaries\, length scales and temperature ranges. URL:https://micde.umich.edu/event/sciml-webinar-lenz-fiedler-efficient-calculations-of-electronic-structures-with-machine-learning-models/ LOCATION:MI CATEGORIES:Micde,Scientific Computing,Sciml,SciML Webinar Series,Webinar END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Detroit:20231107T120000 DTEND;TZID=America/Detroit:20231107T130000 DTSTAMP:20260604T032605 CREATED:20230914T150100Z LAST-MODIFIED:20231019T200916Z UID:10000639-1699358400-1699362000@micde.umich.edu SUMMARY:MICDE Ph.D. Student Seminars: Bernardo Pacini & Srinivasan Arunachalam DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public\, but we ask that you register to attend the seminar. If you have any questions\, please email micde-events@umich.edu. \nRegister to attend this seminar \nGradient-Based Multidisciplinary Design Optimization for Propeller Design\nUrban air mobility (UAM) vehicles have taken form as advanced rotorcraft with sets of wings\, rotors\, canards\, and other appendages. Noise generation is an important technical barrier that must be addressed to prevent these vehicles from causing excessive disturbance to the communities they are intended to service. To understand the noise these vehicles generate\, and to develop designs that can minimize disturbance\, there is a need for analysis and optimization tools specifically for the conceptual design and sizing phase of urban air mobility vehicle development. Such tools must be computationally efficient to allow for the repeated analyses needed for design optimization. This presentation will review the work being carried out at the University of Michigan\, coupling aerodynamic\, structural\, and aeroacoustic disciplines within the multidisciplinary gradient-based design optimization framework OpenMDAO. While aerostructural optimization has been performed previously\, coupling with aeroacoustics is challenging given the requirement for time accurate simulations and the associated computational cost of such analyses. By leveraging multiple model fidelities and utilizing efficient gradient calculation techniques\, such as the adjoint method and algorithmic differentiation\, these disciplines can be formulated into an optimization framework that can be applied to UAM vehicle designs. This presentation will review the work completed to date\, including preliminary results\, and expand on the future goals of the project\, working towards a broader optimization framework for rotorcraft vehicle design optimization. \nBernardo Pacini\, Ph.D. candidate in Mechanical Engineering and Scientific Computing \nBernardo Pacini is a Ph.D. Candidate at the University of Michigan focusing his research on aerodynamic\, structural\, and aeroacoustic modeling for multidisciplinary design optimization of urban air mobility vehicles. He is a member of the Multidisciplinary Design Optimization Laboratory led by Professor Joaquim R. R. A. Martins and of the Computational Aerosciences Laboratory led by Professor Karthik Duraisamy. Bernardo’s work to date is on developing an aero-structural-acoustic analysis framework that can be implemented within the multidisciplinary design optimization process for rotorcraft and urban air mobility vehicle design. \nRegister to attend this seminar \nValidation of a multivariate non-Gaussian\, non-stationary wind pressure simulation model for performance-based wind engineering\nWith a growing interest in probabilistic performance assessments of building systems subjected to wind loads\, there is a demand for accurately representing building-specific wind loads\, considering their non-Gaussian and non-stationary features. While typical wind tunnel data collected for a set of discrete wind directions provide a single realization of stationary pressures\, there is currently no experimentally validated model for the stochastic simulation of non-Gaussian and non-stationary wind pressures that can be calibrated to wind tunnel datasets. Such a model is essential for simulating building aerodynamics\, especially the stochastic\, path-dependent responses associated with time-varying wind speed and direction experienced by a building during hurricane wind events. This talk will review a recently developed theoretical formulation for generating these stochastic pressures. Through carefully designed tests conducted at the University of Florida wind tunnel facility\, the formulation was extensively validated with respect to its ability to capture trends over time\, occurrences of peaks\, and time-varying frequency content. \nSrinivasan Arunachalam\, Ph.D. candidate in Civil and Environmental Engineering and Scientific Computing \nSrinivasan Arunachalam is a PhD candidate in Civil and Environmental Engineering. His research interests lie in uncertainty quantification and understanding the inelastic behavior of wind-excited structures. He is excited about the algorithmic developments that enable efficient reliability assessments\, as well as the evolving insights into the physics of extreme responses and their implications for structural design. \nRegister to attend this seminar URL:https://micde.umich.edu/event/phd-seminar-bernardo-pacini-srinivasan-arunachalam/ LOCATION:2022 South Thayer Building CATEGORIES:Computation,Computational Modeling,Computational Science,Engineering,Free,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,In Person,Interdisciplinary,Michigan Engineering,Phd Seminar,Prospective Graduate Students,Rackham,Science,Scientific Computing,Seminar,Sessions,Talk ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/09/2023117-Bernardo-Pacini-and-SrinivasanArunachalam-1.png END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Detroit:20231101T150000 DTEND;TZID=America/Detroit:20231101T160000 DTSTAMP:20260604T032605 CREATED:20230913T004822Z LAST-MODIFIED:20231112T191452Z UID:10000628-1698850800-1698854400@micde.umich.edu SUMMARY:MICDE / NERS Seminar: Larry Aagesen\, Computational Scientist at Idaho National Laboratory DESCRIPTION:Bio: Dr. Larry Aagesen is a Computational Scientist at Idaho National Laboratory (INL)\, and is the leader of the Computational Microstructure Science group there. He is a member of the development team for Marmot\, INL’s application for simulating microstructural evolution in nuclear fuels and reactor structural materials\, which is based on MOOSE\, INL’s framework for solving partial differential equations using the finite element method. His primary area of expertise is in the phase-field method\, having developed phase-field models for a variety of physical phenomena\, including fission gas bubble evolution\, solid-state precipitation\, solidification and coarsening in metallic alloys and ceramics\, and semiconductor growth. He received his undergraduate degree in Physics at the University of California\, Berkeley in 1997\, followed by service in the U. S. Navy’s nuclear propulsion program and work in industry. He then returned to graduate school\, completing his Ph.D. in Materials Science and Engineering at Northwestern University in 2010. This was followed by appointment as a postdoctoral researcher and Assistant Research Scientist in the Department of Materials Science and Engineering at the University of Michigan from 2010 to 2015\, after which he joined INL. \nMulti-scale modeling of the evolution of structure and properties in materials for nuclear energy applications\nNuclear energy is an important component of an overall strategy to address climate change. Idaho National Laboratory (INL) is the U.S. Department of Energy’s primary facility for research and development in nuclear science and technology for energy generation\, supporting the improvement and life extension of the existing reactor fleet and the development and licensing of new reactor designs. Computational modeling is an important component of these activities\, particularly in the area of materials for nuclear applications\, where experimental data can be very challenging and expensive to acquire\, and where data is especially scarce for new reactor designs. INL has used multi-scale modeling – linking atomistic\, mesoscale\, and engineering scales – to improve the ability to predict the performance of materials for nuclear energy applications. These modeling efforts make extensive of MOOSE (Multiphysics Object-Oriented Simulation Environment)\, a general-purpose open source finite element framework developed at INL. In this talk\, I will give an overview of the approach and tools used\, and several examples of application\, including performance of nuclear fuels\, understanding radiation-driven formation of nanoscale void and gas bubble superlattices\, and powder densification through electric field assisted sintering. \n  \n\n  \nThe MICDE Fall 2023 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 Nuclear Engineering and Radiological Sciences\, (NERS). Dr. Aagesen will be hosted by Dr. Kevin Field\, Associate Professor of Nuclear 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. \n  URL:https://micde.umich.edu/event/larry-aagesen-computational-scientist-idaho-national-laboratory-inl/ LOCATION:2150 H.H. Dow\, 2300 Hayward St\, Ann Arbor\, 48109\, United States CATEGORIES:Featured Events,Micde Seminar,MICDE Seminar Series ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/09/Larry-Aagesen.png GEO:42.2929214;-83.7154247 X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=2150 H.H. Dow 2300 Hayward St Ann Arbor 48109 United States;X-APPLE-RADIUS=500;X-TITLE=2300 Hayward St:geo:-83.7154247,42.2929214 END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Detroit:20231027T160000 DTEND;TZID=America/Detroit:20231027T170000 DTSTAMP:20260604T032605 CREATED:20230913T002456Z LAST-MODIFIED:20231112T073101Z UID:10000627-1698422400-1698426000@micde.umich.edu SUMMARY:MICDE / ME Seminar: Erik Draeger\, Director of the High Performance Computing Innovation Center and RADIUSS project at Lawrence Livermore National Laboratory DESCRIPTION:Bio: Dr. Erik Draeger is the Director of the High Performance Computing Innovation Center and RADIUSS project at Lawrence Livermore National Laboratory as well as the Scientific Computing group leader at the Center for Applied Scientific Computing. He is also the Deputy Director of Application Development for the Exascale Computing Project\, jointly overseeing a portfolio of 22 Office of Science applications\, 4 NNSA applications\, and 7 co-design projects. Erik earned a Bachelor’s degree in Physics from the University of California\, Berkeley in 1995 and received a PhD in theoretical condensed matter physics from the University of Illinois\, Urbana-Champaign in 2001. He has over a decade of experience developing scientific applications to achieve maximum scalability and time to solution on next-generation architectures. He has been a finalist for the Gordon Bell Prize six times since 2005 and won the prize in 2006. \nSupercomputing at the exascale and beyond: future trends and challenges\nFor the past seven years\, the U.S. Department of Energy’s Exascale Computing Project (ECP) has funded a comprehensive push to refactor 24 application projects to efficiently utilize exascale computing hardware to solve a varied set of complex science and engineering problems. Ambitious performance and capability goals were set for each application that demanded end-to-end rethinking of traditional approaches. Through detailed performance analysis\, integration with optimized co-design frameworks and software libraries\, and the use of programming abstractions to manage data placement and kernel execution\, ECP applications recently demonstrated substantial capability and performance improvements on newly-available exascale machines. Despite significant diversity in the methods and algorithms underlying the ECP application portfolio\, several common themes emerged in how to best adapt computational workloads to heterogeneous architectures. In this talk\, an overview of best practices and lessons learned on effectively utilizing exascale hardware from the perspective of ECP applications will be presented. Strategies for developing portable\, performant code will be discussed and examples of reexamining traditional algorithms and methods will be described. Armed with this knowledge\, researchers can go beyond simply surviving an uncertain and turbulent computing future to instead leading a wave of scientific and computational innovation as traditional approaches are reexamined and new approaches adopted. \n  \n\n  \nThe MICDE Fall 2023 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 Mechanical Engineering (ME). Dr. Draeger will be hosted by Dr. Vikram Gavini\, Professor of Mechanical 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-me-seminar-erik-draeger-director-hpc-innovation-center-llnl-deputy-director-doe-exascale-computing-project/ LOCATION:1670 Bob and Betty Beyster Building\, 2260 Hayward Street\, Ann Arbor\, MI\, 48109\, United States CATEGORIES:Featured Events,Micde,Micde Seminar,MICDE Seminar Series ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/09/Erik-Draeger.png GEO:42.2930138;-83.716372 X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=1670 Bob and Betty Beyster Building 2260 Hayward Street Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=2260 Hayward Street:geo:-83.716372,42.2930138 END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Detroit:20231026T110000 DTEND;TZID=America/Detroit:20231026T130000 DTSTAMP:20260604T032605 CREATED:20231017T170318Z LAST-MODIFIED:20231107T231334Z UID:10000658-1698318000-1698325200@micde.umich.edu SUMMARY:SciML Webinar: Bowen Deng - CHGNet: pretrained universal interatomic potential to study electron coupled ionic systems. DESCRIPTION:https://umich.zoom.us/j/95111677727?pwd=V1Q5MkUwT2NpOFVhd0ZRVGR1YTM3Zz09 \n\nSpeaker: Bowen Deng (UC Berkeley)\nSession Chair: Sakidja Ridwan (Missouri State University) \nAbstract: Large-scale simulations with complex electron interactions remain one of the greatest challenges for atomistic modeling. Although classical force fields often fail to describe the\ncoupling between electronic states and ionic rearrangements\, the more accurate ab-initio molecular dynamics suffers from computational complexity that prevents long-time and large-\nscale simulations\, which are essential to study technologically relevant phenomena. Our work presents the Crystal Hamiltonian Graph Neural Network (CHGNet)\, a graph-neural-\nnetwork-based machine-learning interatomic potential (MLIP) that models the universal potential energy surface. CHGNet is pretrained on the energies\, forces\, stresses\, and magnetic moments\nfrom the Materials Project Trajectory Dataset\, which consists of over 10 years of density functional theory calculations of ∼ 1.5 million inorganic structures. The explicit inclusion of\nmagnetic moments enables CHGNet to learn and accurately represent the orbital occupancy of electrons\, enhancing its capability to describe both atomic and electronic degrees of freedom.\nWe demonstrate several applications of CHGNet in solid-state materials and energy storage applications. URL:https://micde.umich.edu/event/sciml-webinar-bowen-deng/ LOCATION:MI CATEGORIES:Micde,Scientific Computing,Sciml,SciML Webinar Series,Webinar END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Detroit:20231019T110000 DTEND;TZID=America/Detroit:20231019T130000 DTSTAMP:20260604T032605 CREATED:20230915T150343Z LAST-MODIFIED:20231025T194805Z UID:10000646-1697713200-1697720400@micde.umich.edu SUMMARY:SciML Webinar Ji Qi: DImensionality-Reduced Encoded Clusters with sTratified (DIRECT) sampling for Robust Training of Machine Learning Interatomic Potentials DESCRIPTION:https://umich.zoom.us/j/95111677727?pwd=V1Q5MkUwT2NpOFVhd0ZRVGR1YTM3Zz09 \n\nSpeaker: Ji Qi (UC San Diego and LLNL)\nSession Chair: Daniel Schwalbe-Koda (UC Los Angeles) \nAbstract: Machine learning interatomic potentials (MLIPs) enable accurate simulations of materials at scales beyond conventional first-principles approaches\, and they have played increasingly important roles in understanding and design of materials. However\, MLIPs are only as accurate and robust as the data they are trained on. In this seminar\, I will present DImensionality-Reduced Encoded Clusters with sTratified (DIRECT) sampling as an approach to select a robust training set of structures from a large and complex configuration space. By applying DIRECT sampling on the Materials Project relaxation trajectories dataset with over one million structures and 89 elements\, we develop an improved materials 3-body graph network (M3GNet) universal potential that extrapolate more reliably to unseen structures. We further show that molecular dynamics (MD) simulations with universal potentials such as M3GNet can be used in place of expensive ab initio MD to rapidly create a large configuration space for target materials systems. For demonstration\, we combined this scheme with DIRECT sampling to develop a reliable moment tensor potential for titanium hydrides without the need for iterative augmentation of training structures. \nIn this seminar\, I will walk through two Jupiter notebooks to showcase DIRECT sampling with the two example cases demonstrated in our manuscript\, so that audience can expect to reproduce our major results with no trouble. Hopefully\, DIRECT sampling will serve as a straightforward\, efficient\, useful plug-in for the robust training of MLIPs across any compositional complexity. URL:https://micde.umich.edu/event/workshop-seminarsciml-webinar-ji-qi-2/ LOCATION:MI CATEGORIES:Micde,Scientific Computing,Sciml,SciML Webinar Series,Webinar END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Detroit:20231012T110000 DTEND;TZID=America/Detroit:20231012T130000 DTSTAMP:20260604T032605 CREATED:20230915T150330Z LAST-MODIFIED:20231018T173554Z UID:10000644-1697108400-1697115600@micde.umich.edu SUMMARY:SciML Webinar Justin Beroz: A closed-form mathematical framework for modeling turbulent fluids DESCRIPTION:Speaker: Justin Beroz (ReynKo Inc.) \n\nSession Chair: Varun Shankar (Physics Inverted Mataerials) \nAbstract: Despite significant advances over the past two centuries\, a complete general mathematical framework for turbulent fluid motion has yet to be put forth\, and remains the longest standing unsolved problem in classical physics. I will present such a framework\, which is based on constructing a spectral decomposition for the fluid’s kinetic energy from first principles. The approach departs from the usual Reynolds decomposition and yields a set of closed and solvable ordinary differential equations in matrix form. Within this prescription\, the linear terms in the Navier-Stokes equations correspond to a symmetric matrix operator\, and the nonlinear convective term enters as an anti-symmetric operator that provides coupling between eigenstates of turbulent fluctuation. Specifically\, I will present a derivation for the turbulent energy spectrum\, including the Kolmogorov energy cascade; elucidate instability mechanisms for the transition to turbulence;  and detail the analytical solution for turbulence in a box. Careful attention will be given to the physical picture and scaling\, in addition to the rigorous mathematical program. The talk will conclude with a forward look into current efforts implementing the model into a numerical simulation within my company\, ReynKo Inc. URL:https://micde.umich.edu/event/workshop-seminarsciml-webinar-justin-beroz/ LOCATION:MI CATEGORIES:Micde,Scientific Computing,Sciml,SciML Webinar Series,Webinar END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Detroit:20231011T110000 DTEND;TZID=America/Detroit:20231011T120000 DTSTAMP:20260604T032605 CREATED:20230927T154544Z LAST-MODIFIED:20231211T234457Z UID:10000655-1697022000-1697025600@micde.umich.edu SUMMARY:MICDE / LANL T Division - James Patrick Colgan\, Deputy Division Leader Los Alamos National Laboratory Theoretical Division DESCRIPTION:Join us to learn more about the Theoretical Division of Los Alamos National Laboratory.  Are you familiar with the Oppenheimer movie?\nYou can also hear about the exciting opportunities available for graduate students and post docs at LANL. \nSpeaker: James Patrick Colgan\, Deputy Division Leader Los Alamos National Laboratory \n  \nBio: James Colgan is the Deputy Division Leader of Theoretical Division at Los\nAlamos National Laboratory. James received his BSc and PhD degrees in Theoretical\nPhysics from Queen’s University\, Belfast\, Northern Ireland. After a post-doctoral\nposition at Auburn University\, he joined LANL in 2003 as a post-doctoral researcher\nand was converted to a staff scientist position in 2005 in Theoretical Division. James\nbecame Group Leader of the Physics and Chemistry of Materials (T-1) in 2017 and\nbecame Deputy Division Leader in 2022. James has published extensively in atomic\nand plasma physics and was elected a Fellow of the American Physical Society (APS)\nin 2012 and a Fellow of the U.K. Institute of Physics (IOP) in 2021 \nAn overview of Los Alamos National Laboratory and the Theoretical Division\nAbstract: An overview of the activities of Los Alamos National Laboratory (LANL)\nare presented. LANL was founded in 1943 under the leadership of J. Robert\nOppenheimer to direct the “Manhattan Project” – a top-secret project to create the\natomic bomb. Now 80 years later\, in 2023\, LANL is tasked by the nation through the\nDepartment of Energy and National Nuclear Security Administration to deliver\nnational security solutions to address the issues faced by the nation and world.\nLANL achieves its mission by applying multidisciplinary science\, technology and\nengineering capabilities using unique experimental\, computational\, and nuclear\nfacilities.\nThis overview will provide a brief survey of LANL’s activities and then will focus on\nthe research & development portfolio of LANL’s Theoretical (T) Division (part of the\nDirectorate for Simulation & Computation). T Division\, which has existed since the\ninception of LANL\, aims to provide excellence in basic and applied theoretical\nresearch across many disciplines\, notably computational materials science and the\ndevelopment of cutting-edge computational tools to support the national security\nmission of the Laboratory. URL:https://micde.umich.edu/event/workshop-seminaran-overview-of-los-alamos-national-laboratory-and-the-theoretical-division/ LOCATION:Lurie Robert H. Engin. Ctr – Johnson Rooms (LEC 3213) CATEGORIES:Micde,Micde Seminar,MICDE Seminar Series ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/09/LANL-Logo.png END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Detroit:20231010T130000 DTEND;TZID=America/Detroit:20231010T170000 DTSTAMP:20260604T032605 CREATED:20230817T202937Z LAST-MODIFIED:20231009T151118Z UID:10000611-1696942800-1696957200@micde.umich.edu SUMMARY:MICDE ACES Mini-Symposium: MICDE Catalyst Grant Showcase DESCRIPTION:MICDE is excited to present the Advanced Computational Science & Engineering Showcase (ACES) mini-symposium. ACES is a highly anticipated event aiming to highlight current trends and hot topics in computational science\, machine learning and AI. This event showcases the outstanding research supported by the MICDE Catalyst Grant and provides a unique opportunity to share your ideas and network with fellow faculty members during a networking reception. \nThis year’s mini-symposium features the following exceptional faculty: \n\n\n\n\n\n\n\n\nGary Luker\, Professor | Department of Radiology | Department of Biomedical Engineering | Department of Microbiology and Immunology\nSalar Fattahi\, Assistant Professor | Department of Industrial and Operations Engineering\nJesse Capecelatro\, Associate Professor | Department of Mechanical Engineering | Department of Aerospace Engineering\n\n\n\n\n\n\n\nVenkat Viswanathan\, Associate Professor | Department of Aerospace Engineering\nGeorge Tzimpragos\, Assistant Professor | Department of Computer Science and Engineering\nGokul Ravi\, Assistant Professor | Department of Electrical Engineering and Computer Science\n\n\n\n  \nSchedule: \n\n\n\nSpeaker\nDepartment \nTime\nTitle\n\n\nVancho Kocevski\nMICDE\n1:00 pm\nMICDE Welcome\n\n\n\n\n1:05 pm\nFelicitation of Krishna Garikipati for his contributions to Computational Science & Engineering @ UM\n\n\nGary Luker\nRadiology | Biomedical Engineering | Microbiology and Immunology\n1:30 pm\nA physics-constrained AI framework for cancer cell migration\n\n\nSalar Fattahi\nIndustrial and Operations Engineering\n1:55 pm\nScalable Inference of Dynamic Graphical Models with Combinatorial Structures\n\n\nBreak\n \n2:20 pm\n\n\n\nJesse Capecelatro\nMechanical Engineering | Aerospace Engineering\n2:30 pm\nParticle-laden flows: simulations and data-driven modeling\n\n\nVenkat Viswanathan\nAerospace Engineering\n2:55 pm\nAI Foundation models for materials science\n\n\nBreak\n \n3:20 pm\n\n\n\nGeorge Tzimpragos\nElectrical Engineering and Computer Science \n3:30 pm\nBeating Resistance\n\n\nGokul Ravi\nElectrical Engineering and Computer Science \n3:55 pm\nA Hybrid Quantum-Classical Computing Ecosystem\n\n\nNetworking Session\n \n4:30 pm\n\n\n\nAdjourn\n \n5:15 pm\n\n\n\n\n  \nThe event finishes with a networking reception\, where faculty members can share their research ideas and future plans\, sparking collaborations. URL:https://micde.umich.edu/event/conference-symposiummicde-aces-mini-symposium/ LOCATION:Lurie Robert H. Engin. Ctr – Johnson Rooms\, 3rd floor CATEGORIES:Aces,Computation,Computational Modeling,Computational Science,Computational Social Science,computing,Research,Science,Scientific Computing,symposium END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Detroit:20231005T140000 DTEND;TZID=America/Detroit:20231005T150000 DTSTAMP:20260604T032605 CREATED:20230915T193609Z LAST-MODIFIED:20231004T170032Z UID:10000647-1696514400-1696518000@micde.umich.edu 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 ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/09/Mark-W.-Schraad.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:20231005T110000 DTEND;TZID=America/Detroit:20231005T123000 DTSTAMP:20260604T032605 CREATED:20230918T024126Z LAST-MODIFIED:20231018T165056Z UID:10000649-1696503600-1696509000@micde.umich.edu SUMMARY:SciML Webinar: Jianke Yang - Generative Adversarial Symmetry Discovery DESCRIPTION:Speaker: Jianke Yang (UC San Diego) \n\n\nSession Chair: Bharath Ramsundar (Deep Forest Sciences) \nAbstract:Despite the success of equivariant neural networks in scientific applications\, they require knowing the symmetry group a priori. Automatic symmetry discovery methods aim to relax this constraint and learn invariance and equivariance from data.  We propose a framework\, LieGAN\, to automatically discover equivariances from a dataset using a paradigm akin to generative adversarial training. Specifically\, a generator learns a group of transformations applied to the data\, which preserves the original distribution and fools the discriminator. LieGAN represents symmetry as an interpretable Lie algebra basis and can discover various symmetries such as the rotation group and the restricted Lorentz group in trajectory prediction and top-quark tagging tasks. More generally\, LieGAN can also be extended to discover the nonlinear symmetries in high-dimensional dynamics. The learned symmetry can be readily used in several existing equivariant neural networks to improve prediction accuracy and generalization. It can also improve the symbolic equation discovery and long-term forecasting for various dynamical systems. \n\n\n  URL:https://micde.umich.edu/event/sciml-webinar-jianke-yang-generative-adversarial-symmetry-discovery/ LOCATION:MI CATEGORIES:Sciml,SciML Webinar Series END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Detroit:20231002T160000 DTEND;TZID=America/Detroit:20231002T170000 DTSTAMP:20260604T032605 CREATED:20230913T145953Z LAST-MODIFIED:20231013T144409Z UID:10000632-1696262400-1696266000@micde.umich.edu SUMMARY:MICDE / ME Seminar: Olivier Desjardins\, Professor of Mechanical and Aerospace Engineering at Cornell University DESCRIPTION:Bio: Olivier Desjardins is a Professor at the Sibley School of Mechanical and Aerospace Engineering at Cornell University. He joined the Cornell MAE faculty in July 2011. Prior to that\, he was on the Mechanical Engineering faculty at the University of Colorado at Boulder. He received a Master of Science in Aeronautics and Astronautics from ENSAE (Supaero) in Toulouse\, France\, in 2004. The same year\, he received a Master of Science in Mechanical Engineering from Stanford University\, then in 2008 he obtained a Ph.D. in Mechanical Engineering from Stanford University. He received an NSF CAREER award in 2014 to work on turbulence modeling around liquid-gas interfaces\, and he was presented with the Junior Award from the International Conference on Multiphase Flow in 2016. \nResearch Interests: Prof. Desjardins’ research focuses on large-scale numerical modeling of turbulent reacting multiphase flows with industrial application. Using world-class parallel computers\, his group develops numerical methods and models to investigate the multi-scale and multi-physics fluid mechanics problems that arise in a range of engineering devices\, such as combustors or biomass reactors. \nHigh-fidelity computational techniques such as large-eddy simulations and direct numerical simulations are at the heart of Dr. Desjardins’ research. By enabling the exploration of complex non-linear flow physics from first principles\, these techniques have the potential to guide the development of highly optimized energy and propulsion systems. \nMulti-scale modeling of topology change in multiphase flow simulations\nLiquid atomization and spray formation are ubiquitous processes in nature as well as engineered system. Predicting droplet size distributions from first principle simulations presents a fantastic challenge due to the wide range of scales involved in topology change. In this talk\, we present new developments to the geometric volume of fluid method that enable the tracking of sub-grid scale interfacial features. By reconstructing the interface with multiple planar surfaces or with paraboloid surfaces\, we show that ligaments and sheets can be represented accurately independently of mesh resolution while preserving exact conservation\, good computational efficiency\, and easy integration with finite-volume-based flow solvers. A consequence of such strategies is that lack of mesh resolution no longer induces topology change\, which then needs to be reintroduced explicitly using physics-based models. We discuss various flavors of such models in the context of the break-up of thin liquid films\, a common feature in aerodynamic liquid atomization. \n  \n\n  \nThe MICDE Fall 2023 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 Mechanical Engineering (ME). Prof. Desjardins will be hosted by Dr. Jesse Capecelatro\, Associate Professor of Mechanical and Aerospace 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/workshop-seminarmicde-me-seminar-olivier-desjardins/ LOCATION:1109 FXB\, 1320 Beal Ave.\, Ann Arbor\, MI\, United States CATEGORIES:Aerospace Engineering,College Of Engineering,Mechanical Engineering,Micde Seminar,MICDE Seminar Series ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/09/Olivier-Desjardins.png GEO:42.290906;-83.713503 X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=1109 FXB 1320 Beal Ave. Ann Arbor MI United States;X-APPLE-RADIUS=500;X-TITLE=1320 Beal Ave.:geo:-83.713503,42.290906 END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Detroit:20230929T120000 DTEND;TZID=America/Detroit:20230929T130000 DTSTAMP:20260604T032605 CREATED:20230817T202936Z LAST-MODIFIED:20230912T223037Z UID:10000610-1695988800-1695992400@micde.umich.edu 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/presentationgraduate-studies-in-computational-data-sciences-information-session-2-2/ LOCATION:1100 North University Building – 1528 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 ATTACH;FMTTYPE=image/gif:https://micde.umich.edu/wp-content/uploads/2023/08/Info-session.gif END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Detroit:20230928T110000 DTEND;TZID=America/Detroit:20230928T123000 DTSTAMP:20260604T032605 CREATED:20230918T023335Z LAST-MODIFIED:20231018T163755Z UID:10000648-1695898800-1695904200@micde.umich.edu SUMMARY:SciML Webinar: Bob Carpenter - Multiscale Generalized Hamiltonian Monte Carlo with Delayed Rejection DESCRIPTION:Speaker: Bob Carpenter (Flatiron Institute) \n\n\nSession Chair: Sam Livingstone (University College London) \n\n\nAbstract: In this talk\, I will demonstrate how we can combine two ideas\, generalized Hamiltonian Monte Carlo and delayed rejection\, to derive a sampler that is as efficient as Hamiltonian Monte Carlo\, but is able to adapt its step size to deal with multiscale distributions\, much like a standard integrator for ordinary differential equations. A distribution is multiscale if its curvature has different scales in the posterior; a textbook example is Radford Neal’s funnel example derived from hierarchical priors\, which has a very flat mouth (corresponding to high population variance) and very highly curved neck (low population variance). No fixed step size allows exploration of its posterior. Generalized HMC allows us to take a single Hamiltonian step along the gradient at a time (which is equivalent to Metropolis-adjusted Langevin dynamics)\, but only refresh momentum partially (which makes it underdamped). The naive form of this algorithm does not work because momentum must be reversed to maintain detailed balance if the Metropolis step rejects. To maintain directed exploration\, we apply delayed rejection\, which allows a proposal rejected due to divergence of the Hamiltonian (from too large a step size in the first-order approximation of the dynamics) to be retried with a smaller step size (with a Hastings-style adjustment for the retry). We show that the combination of delayed rejection and GHMC allows sampling multiscale distributions which otherwise lead to biased samples in standard Hamiltonian Monte Carlo (including dynamic forms such as the no-U-turn sampler). In conclusion\, I will discuss some preliminary work on applying the the automatic tuning method using complementary parallel chains developed by Matt Hoffman and Pavel Sountsov for their sampler MEADS (which also uses generalized HMC\, but with an alternative approach to maintaining directed exploration based on work of Radford neal\, which will also describe). \n\nSlides: https://statmodeling.stat.columbia.edu/wp-content/uploads/2023/09/carpenter-sciml-webinar-2023.pdf URL:https://micde.umich.edu/event/sciml-webinar-bob-carpenter-multiscale-generalized-hamiltonian-monte-carlo-with-delayed-rejection/ LOCATION:MI CATEGORIES:Sciml,SciML Webinar Series END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Detroit:20230927T160000 DTEND;TZID=America/Detroit:20230927T170000 DTSTAMP:20260604T032605 CREATED:20230817T202936Z LAST-MODIFIED:20230912T222916Z UID:10000612-1695830400-1695834000@micde.umich.edu 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/presentationgraduate-studies-in-computational-data-sciences-information-session/ LOCATION:Lurie Robert H. Engin. Ctr – Johnson Rooms\, 3rd floor 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 ATTACH;FMTTYPE=image/gif:https://micde.umich.edu/wp-content/uploads/2023/08/Info-session.gif END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Detroit:20230926T123000 DTEND;TZID=America/Detroit:20230926T130000 DTSTAMP:20260604T032605 CREATED:20230913T145952Z LAST-MODIFIED:20230921T195259Z UID:10000631-1695731400-1695733200@micde.umich.edu SUMMARY:MICDE Ph.D. Student Seminar: Haowei Sun DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public\, but we ask that you register to attend the seminar. If you have any questions\, please email micde-events@umich.edu. \nRegister to attend this seminar \nTera City: Accurate and Efficient AV Safety Performance Evaluation\nThis talk is aiming at mitigating current simulation-based AV safety performance evaluation approaches. Tera City is composed of naturalistic driving environment construction and intelligent testing environment construction\, which provided accuracy and efficiency\, respectively. \nHaowei Sun\, Ph.D. candidate in Civil and Environmental Engineering and Scientific Computing \nHaowei Sun is a Ph.D. candidate at Civil Engineering\, Next Generation Transportation System Program. His research focus is mainly on the safety validation and verification of autonomous vehicles. \nRegister to attend this seminar URL:https://micde.umich.edu/event/phd-seminar-haowei-sun/ LOCATION:2022 South Thayer Building CATEGORIES:Civil and Environmental Engineering,Computation,Computational Science,Engineering,Free,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,In Person,Interdisciplinary,Michigan Engineering,Phd Seminar,Prospective Graduate Students,Rackham,Science,Scientific Computing,Seminar,Talk ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/09/Haowei-Sun.png END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Detroit:20230922T150000 DTEND;TZID=America/Detroit:20230922T160000 DTSTAMP:20260604T032605 CREATED:20230823T205958Z LAST-MODIFIED:20231002T135627Z UID:10000624-1695394800-1695398400@micde.umich.edu SUMMARY:MICDE / AIM Seminar: Lin Lin\, Professor of Mathematics at University of California Berkeley DESCRIPTION:Bio: Lin Lin is a Professor in the Department of Mathematics at UC Berkeley\, and a Faculty Scientist in the Mathematics Group at Lawrence Berkeley National Laboratory. His research centers on solving quantum many-body problems by employing both classical and contemporary methods. These techniques prove valuable across various domains\, including quantum chemistry\, quantum physics\, materials science\, and quantum information theory. He has received the Sloan Research Fellowship (2015)\, the National Science Foundation CAREER award (2017)\, the Department of Energy Early Career award (2017)\, the (inaugural) SIAM Computational Science and Engineering (CSE) early career award (2017)\, the Presidential Early Career Awards for Scientists and Engineers (PECASE) (2019)\, the ACM Gordon Bell Prize (Team\, 2020)\, and the Simons Investigator in Mathematics award (2021). \nQuantum algorithms for eigenvalue problems\nThe problem of finding the smallest eigenvalue of a Hermitian matrix\, known as the ground state energy in quantum physics\, has broad applications. Recent years have witnessed significant algorithmic progresses including near-optimal asymptotic complexity\, algorithms with a minimal number of required logical qubits\, and even optimized preconstants. In this talk\, I will first introduce basic quantum algorithm concepts for a non-expert audience and overview these advancements. I will then introduce a recent progress in leveraging ideas from open quantum systems to solve the eigenvalue problem\, which allows us to start from a state with zero overlap with the target state. \n  \n\n  \nThe MICDE Fall 2023 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 Applied & Interdisciplinary Mathematics (AIM). Prof. Lin will be hosted by Dr. Emanuel Gull\, Associate Professor of Theoretical Condensed Matter Physics. \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/workshop-seminaraim-seminar-lin-lin/ LOCATION:East Hall – 1084 CATEGORIES:Featured Events,Mathematics,Micde Seminar,MICDE Seminar Series ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/08/Lin-Lin-small.png END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Detroit:20230921T110000 DTEND;TZID=America/Detroit:20230921T123000 DTSTAMP:20260604T032605 CREATED:20230914T172942Z LAST-MODIFIED:20231018T162319Z UID:10000643-1695294000-1695299400@micde.umich.edu SUMMARY:SciML Webinar: David Ruhe - Geometric Clifford Algebra Networks DESCRIPTION:Speaker: David Ruhe (University of Amsterdam) \n\n\nSession Chair: Erik Bekkers (University of Amsterdam) \n\nAbstract: In this talk\, I will present Clifford Group Equivariant Neural Networks\, an innovative method for building E(n)-equivariant networks based on Clifford (geometric) algebras. First\, I will give an introduction to the Clifford algebra and its geometric applications. Then\, I will introduce the Clifford group and how it always acts through the orthogonal group. As such\, a parameterization that is equivariant to the Clifford group will automatically be equivariant to the orthogonal group of\, e.g.\, rotations and reflections. We show that any polynomial (under the algebra’s geometric product) is such a parameterization.  We propose several layers from these insights and conduct experiments in three-\, four-\, and five-dimensional spaces. One of these experiments even includes equivariance to the nondefinite O(1\,3) Lorentz group from the same code implementation. Finally\, I will provide guidance on how to utilize our codebase for implementing these algorithms. URL:https://micde.umich.edu/event/sciml-webinar-david-ruhe-geometric-clifford-algebra-networks/ LOCATION:MI CATEGORIES:SciML Webinar Series END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Detroit:20230920T150000 DTEND;TZID=America/Detroit:20230920T170000 DTSTAMP:20260604T032605 CREATED:20230822T205955Z LAST-MODIFIED:20230912T214901Z UID:10000623-1695222000-1695229200@micde.umich.edu SUMMARY:MICDE Fellow Welcome Event DESCRIPTION:MICDE is organizing a welcome event for its new fellows. During this event we will share with you the guidelines and process for utilizing your fellowship award funds\, as well as the resources and benefits you now have access to as a part of the MICDE community of fellows. Additionally\, you will receive a professionally-taken headshot free of charge (please dress accordingly). You will also have some time to introduce yourselves and get to know one another. Sandwiches\, cookies\, and beverages will be provided. URL:https://micde.umich.edu/event/othermicde-fellow-welcome-event/ LOCATION:Rackham Graduate School (Horace H.) – Earl Lewis CATEGORIES:Micde ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/08/MICDE-Fellow-Welcome-Event.png END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Detroit:20230817T080000 DTEND;TZID=America/Detroit:20230817T170000 DTSTAMP:20260604T032605 CREATED:20230816T164443Z LAST-MODIFIED:20230831T171725Z UID:10000608-1692259200-1692291600@micde.umich.edu SUMMARY:Other:MICDE website launch DESCRIPTION:New MICDE website will be going live. URL:https://micde.umich.edu/event/othermicde-website-launch/ LOCATION:Off Campus Location END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Detroit:20230412T160000 DTEND;TZID=America/Detroit:20230412T170000 DTSTAMP:20260604T032605 CREATED:20230714T151826Z LAST-MODIFIED:20260522T152717Z UID:10000602-1681315200-1681318800@micde.umich.edu SUMMARY:MICDE Seminar: Paul Kent\, PhD\, Distinguished Research Scientist at Oak Ridge National Laboratory DESCRIPTION:Dr Kent`s research is focusing on predicting and explaining the properties of materials using computer simulation. Over the last two decades\, advances in simulation techniques coupled with increasing computer power have led to several methods that are able to predict physical properties of real materials to a useful accuracy. Moreover\, these methods use little or no experimental data\, making them especially valuable for the study of new materials and devices. Dr. Kent specializes in the application and development of these so-called “first principles” methods. \nHis research interests are broadly focused on atomistic materials simulation. His ongoing research projects include: \n\nQuantum Monte Carlo for real materials\nLarge length and timescale quantum molecular dynamics calculations\nCharacterization\, optimization\, and design of nanoscale systems with desired properties\nCombined density functional and many-body calculations of correlated electron systems such as the copper-oxide superconductors\nReactive classical molecular dynamics\nSimulation methods for exploitation of Exascale supercomputers and emergent architectures\n\n\n\n\n\n\nDr. Kent is the director of  the Center for Predictive Simulation of Functional Materials. He also leads the  development of the QMCPACK application for exascale computing as part of the Exascale Computing Project. QMCPACK is a high-performance Quantum Monte Carlo code for computing the electronic structure of atoms\, molecules and solids\, including metals. QMCPACK is open source and available on GitHub. \nDr Kent is a member of the Nanotheory Institute at the Center for Nanophase Materials Sciences (CNMS) and the Computational Chemical and Materials Science group in the Computational Science and Engineering Division. He spent three years at NREL with Alex Zunger after completing his PhD with Richard Needs at the University of Cambridge. For several years he worked with Mark Jarrell at the University of Cincinnati on high-temperature cuprate superconductors. In 2009 he transitioned from JICS/UT Knoxville to ORNL. \nAwards: \n\nORNL Director’s Award for Outstanding Individual Accomplishment in Science and Technology\, 2020.\nAPS Fellowship\, nominated by the Division of Computational Physics\, 2017.\nACM Gordon Bell Prize\, 2008.\n\nProfessional Service: \n\nGrant reviewer for US DOE and NSF\nReviewer for APS\, ACS\, IOP\, Elsevier\, Springer Nature etc.\n\nAccurate Quantum Materials  Predictions on the Largest Supercomputers\nAdvances in the field of computational materials science have helped to predict\, understand\, and optimize the properties of many classes of materials. These include new battery electrodes\, catalysts\, and arguably even higher-temperature superconductors. However\, we still lack a widely usable method where all the key uncertainties and approximations in the predictions can be assessed and systematically reduced. This is critical where the approximations in established methods fail\, such as in quantum materials\, or simply where greater accuracy is desired. In this talk I will first describe our recent advances in Quantum Monte Carlo methods that promise to meet this challenge. Second\, I will describe the new algorithms and performance portable software design and development strategies we have adopted to run efficiently on the largest supercomputers powered by GPU accelerators from NVIDIA\, AMD and Intel. The lessons learned can be applied in any area of scientific software development. \n\nThe MICDE Winter 2023 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 Physics. Dr. Kent will be hosted by Dr. Emanuel Gull\, Associate Professor of Theoretical Condensed Matter Physics. \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-seminar-paul-kent-phd-distinguished-research-scientist-at-oak-ridge-national-laboratory/ LOCATION:411 West Hall (1085 S. University)\, 1085 S. University 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/Paul-Kent.png END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Detroit:20230316T163000 DTEND;TZID=America/Detroit:20230316T170000 DTSTAMP:20260604T032605 CREATED:20230123T090003Z LAST-MODIFIED:20230809T181913Z UID:10000601-1678984200-1678986000@micde.umich.edu SUMMARY:PhD Seminar: Xintao Yan DESCRIPTION:The Ph.D. in Scientific Computing program is intended for students who will make extensive use of large-scale computation\, computational methods\, or algorithms for advanced computer architectures in their doctoral studies. This seminar series showcases the breadth of research covered by the program.  \nFeatured Speaker:\nXintao Yan\, PhD Candidate\, Civil and Environmental Engineering and Scientific Computing\nXintao Yan is currently a Ph.D. candidate in the Department of Civil and Environmental Engineering at the University of Michigan\, Ann Arbor\, advised by Professor Henry Liu. He received his bachelor’s degree from the Department of Automotive Engineering at Tsinghua University\, China in 2018. His research interests are mainly about the safety of connected and automated vehicles\, including naturalistic driving behavior modeling and automated driving system evaluation. \nSimulating Naturalistic Driving Environment for Autonomous Vehicles\nSimulation provides a controllable\, efficient\, and low-cost venue for both developing and testing autonomous vehicles (AV). But for simulation to be an effective tool\, statistical realism of the simulated driving environment is a must. In this talk\, we will introduce methods to simulate naturalistic driving environment for AV testing purposes. \n\n  \nThis event is part of MICDE’s seminar series featuring Ph.D. students in the Scientific Computing program. This series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nQuestions? Email MICDE-events@umich.edu \n  URL:https://micde.umich.edu/event/phd-seminar-xintao-yan/ LOCATION:Venue TBA\, MI\, 48109\, United States CATEGORIES:Featured Events,MICDE PhD Seminar Series,Seminar ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/02/2023-Winter-Yan.png GEO:42.3053253;-83.6694169 END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Detroit:20230316T160000 DTEND;TZID=America/Detroit:20230316T163000 DTSTAMP:20260604T032605 CREATED:20230123T090003Z LAST-MODIFIED:20230809T182009Z UID:10000597-1678982400-1678984200@micde.umich.edu SUMMARY:PhD Seminar: Xingmin Wang DESCRIPTION:The Ph.D. in Scientific Computing program is intended for students who will make extensive use of large-scale computation\, computational methods\, or algorithms for advanced computer architectures in their doctoral studies. This seminar series showcases the breadth of research covered by the program.  \nFeatured Speaker:\nXingmin Wang\, PhD Candidate\, Civil and Environmental Engineering and Scientific Computing\nXingmin Wang is currently a Ph.D. candidate in the Department of Civil and Environmental Engineering at the University of Michigan\, Ann Arbor\, advised by Professor Henry Liu. He obtained his bachelor’s degree in the school of vehicle and mobility from Tsinghua University\, in 2018. His research interests include traffic state estimation and traffic network optimization with connected and automated vehicles. \nTraffic signal optimization with connected vehicle trajectories\nTraffic signal retiming is one of the most cost-effective methods for reducing congestion and energy consumption in urban areas based on the existing road infrastructure. However\, high installation and maintenance costs of vehicle detectors have prevented the widespread implementation of adaptive traffic control systems (ATSC). Therefore\, most intersections are still controlled by fixed-time traffic signals which are not updated regularly due to the lack of traffic monitoring capabilities. In the past few years\, vehicle trajectory data has become increasingly available and offers many advantages over detectors and other infrastructure-based sensors for traffic monitoring; but using such data for automatic traffic signal diagnosis and optimization at scalable implementable levels is relatively unexplored. To fill this gap\, this work proposes Optimizing Traffic Signals as a Service (OSaaS)\, an integrated traffic signal re-timing system that uses vehicle trajectories as the main input. OSaaS addresses many of the current challenges relating to signal retiming with trajectory data such as incomplete observation due to limited penetration rates. The system builds a queueing model that reconstructs the overall average traffic state\, calibrated from performance measurements directly obtained from vehicle trajectories. The calibrated queueing model then predicts and evaluates network performance under different traffic signal parameters to provide diagnostics and direct traffic signal retiming guidance. In April 2022\, a citywide field test of OSaaS was conducted in Birmingham\, Michigan\, with 34 signalized intersections. This resulted in decreases in both the delay and number of stops by up to 20% and 30%\, respectively. OSaaS provides a more scalable\, sustainable\, resilient\, and efficient solution to traffic signal retiming without requiring any additional infrastructure through the exclusive utilization of currently available trajectory data. As a result\, it presents the possibility of upgrading all existing fixed-time traffic signals to dynamic systems with periodical parameter updates\, something that is not currently possible without significant investments in infrastructure-based traffic flow sensors. \n\n  \nThis event is part of MICDE’s seminar series featuring Ph.D. students in the Scientific Computing program. This series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nQuestions? Email MICDE-events@umich.edu \n  URL:https://micde.umich.edu/event/phd-seminar-xingmin-wang/ LOCATION:Venue TBA\, MI\, 48109\, United States CATEGORIES:Featured Events,MICDE PhD Seminar Series,Seminar ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/02/2023-Winter-Wang-1.png GEO:42.3053253;-83.6694169 END:VEVENT END:VCALENDAR