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DTSTART;TZID=America/Detroit:20240403T090000
DTEND;TZID=America/Detroit:20240403T170000
DTSTAMP:20260605T164012
CREATED:20240115T212036Z
LAST-MODIFIED:20240226T163136Z
UID:10000667-1712134800-1712163600@micde.umich.edu
SUMMARY:SciFM24 Conference
DESCRIPTION:This event is the first of its kind\, dedicated to scientific foundation models (SciFM)\, that are set to revolutionize science in the same way Generative AI has transformed natural language.\nThis two-day conference will bring together some of the most renowned experts from the field of scientific foundation models who will share their insights and knowledge on various topics related to this field. The event will also feature engaging panel discussions\, informative workshops\, and a poster competition\, providing attendees\, with ample opportunities to learn\, network\, and engage.
URL:https://micde.umich.edu/event/conference-symposiumscifm24-conference-2/
LOCATION:Rackham Graduate School (Horace H.) – Amphitheater
CATEGORIES:Astronomy,Basic Science,Biology,Biomedical Engineering,Biosciences,Biostatistics,Chemistry,College Of Engineering,Complex Systems,Computational Science,Engineering Academic Calendar,Epidemiology,Evolutionary Biology,Faculty,Free,Information and Technology,Kinesiology,Lsaresearch,Mathematics,Medicine,Micde,Michigan Engineering,Michigan Robotics,Midas,Physics,Public Health,Rackham,Research,Science,Scientific Computing,Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20240412T150000
DTEND;TZID=America/Detroit:20240412T160000
DTSTAMP:20260605T164012
CREATED:20240115T212036Z
LAST-MODIFIED:20240604T125820Z
UID:10000668-1712934000-1712937600@micde.umich.edu
SUMMARY:MICDE/ MCAIM seminar: Boyce Griffith\, Professor at the University of North Carolina
DESCRIPTION:Bio: Boyce Griffith is a Professor in the Department of Mathematics and Department of Biomedical Engineering at the University of North Carolina\, where he is also an Adjunct Professor of Applied Physical Sciences and Associate Chair for Research in the Department of Mathematics. His research group focuses on the development and application of numerical methods for simulating fluid-structure interaction with a particular focus on models of the heart and its valves. Their core approach is based on extensions of the immersed boundary method fluid-structure interaction. \nImmersed methods for fluid-structure interaction\nThe immersed boundary (IB) method is a framework for modeling systems in which an elastic structure interacts with a viscous incompressible fluid. The fundamental feature of the IB approach to such fluid-structure interaction (FSI) problems is its combination of an Eulerian formulation of the momentum equation and incompressibility constraint with a Lagrangian description of the structural deformations and resultant forces. In conventional IB methods\, Eulerian and Lagrangian variables are linked through integral equations with Dirac delta function kernels\, and these singular kernels are replaced by regularized delta functions when the equations are discretized for computer simulation. This talk will focus on three related extensions of the IB method. I first detail an IB approach to structural models that use the framework of large-deformation nonlinear elasticity. I will focus on efficient numerical methods that enable finite element structural models in large-scale simulations\, with examples focusing on models of the heart and its valves. Next\, I will describe an extension of the IB framework to simulate soft material failure using peridynamics\, which is a nonlocal structural mechanics formulation. Numerical examples demonstrate constitutive correspondence with classical mechanics for non-failure cases along with essentially grid-independent predictions of fluid-driven soft material failure. Finally\, I will introduce a reformulation of the IB large-deformation elasticity framework that enables accurate and efficient fluid-structure coupling through a version of the immersed interface method\, which is a sharp-interface IB-type method. Computational examples demonstrate the ability of this methodology to simulate a broad range of fluid-structure mass density ratios without suffering from artificial added mass instabilities\, and to facilitate subgrid contact models. I will also present biomedical applications of the methodology\, including models of clot capture by inferior vena cava filters. \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)\, the Department of Mathematics and the Michigan Center for Applied and Interdisciplinary Mathematics (AIM). \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/workshop-seminarmicde-mcaim-seminar-prof-boyce-griffith/
LOCATION:East Hall – 1084
CATEGORIES:College Of Engineering,Computational Science,Free,Graduate School,Lsaresearch,Mathematics,Micde,Micde Seminar,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2024/01/Boyce-Griffith.png
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20240419T110000
DTEND;TZID=America/Detroit:20240419T120000
DTSTAMP:20260605T164012
CREATED:20240412T011911Z
LAST-MODIFIED:20240412T140752Z
UID:10000680-1713524400-1713528000@micde.umich.edu
SUMMARY:MICDE Fellowships Information Session
DESCRIPTION:Applications for the $4\,500 2024-2025 MICDE Graduate Fellowships will open May 1\, 2024. Please join this Zoom session to learn more about the fellowships and how to submit a great application! \nThese fellowships are sponsored by the Michigan Institute for Computational Discovery & Engineering. For more information\, see https://live-umor-micde.pantheonsite.io/academic-programs/fellowships/.
URL:https://micde.umich.edu/event/livestream-virtualmicde-fellowships-information-session/
LOCATION:Zoom Event
CATEGORIES:Aerospace Engineering,Ai In Science And Engineering,Astronomy,big data,Biomedical Engineering,Biosciences,Biostatistics,Chemical Engineering,Chemistry,Civil and Environmental Engineering,Climate and Space Sciences and Engineering,College Of Engineering,Complex Systems,Computation,Computational Modeling,Computational Science,Computational Social Science,computer science,Data Science,Earth And Environmental Sciences,Ecology,Ecology And Evolutionary Biology,Economics,Education,Electrical And Computer Engineering,Electrical Engineering and Computer Science,Engineering,Engineering Academic Calendar,Epidemiology,Evolutionary Biology,Fellowship,Free,Funding,Generative Ai,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,Health Data,High Performance Computing,Industrial and Operations Engineering,Interdisciplinary,Kinesiology,Life Science,Lsaresearch,Machine Learning,Materials Science,Mathematics,Mechanical Engineering,Medicine,Micde,Natural Language Processing,Natural Sciences,Naval Architecture and Marine Engineering,Neuroscience,Nuclear Engineering and Radiological Sciences,parallel computing,Pharmacy,Physics,Politics,Prospective Graduate Students,Psychology,Public Health,Public Policy,Rackham,Research,Robotics,Scholarship,Science,Scientific Computing,Sciml,Sociology,Statistics,Virtual,Webcast,Workshops
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2024/04/Fellowships-2024-info-session.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20240930T150000
DTEND;TZID=America/Detroit:20240930T160000
DTSTAMP:20260605T164012
CREATED:20240920T130342Z
LAST-MODIFIED:20240920T130342Z
UID:10000750-1727708400-1727712000@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/micde-midas-graduate-information-session/
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
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20241001T150000
DTEND;TZID=America/Detroit:20241001T160000
DTSTAMP:20260605T164012
CREATED:20240925T142215Z
LAST-MODIFIED:20241011T124325Z
UID:10000772-1727794800-1727798400@micde.umich.edu
SUMMARY:MICDE/ME Seminar: Krishnan Mahesh\, Professor\, University of Michigan NAME
DESCRIPTION:Bio:  Krishnan Mahesh is a Richard B. Couch Professor of Naval Architecture and Marine Engineering at the University of Michigan. His research focuses on the simulation of complex\, multi-physics turbulent flows. Mahesh received his Bachelor’s degree in Mechanical Engineering from the Indian Institute of Technology (Mumbai)\, and in 1996 obtained his Ph.D. degree in Mechanical Engineering from Stanford University. He is a 2018 Fulbright-Nehru Specialist\, a Fellow of the American Physical Society\, an Associate Fellow of the American Institute of Aeronautics and Astronautics\, and a Fellow of the Minnesota Supercomputing Institute. Mahesh is a recipient of the CAREER Award from the National Science Foundation and the Francois N. Frenkiel Award from the American Physical Society. He has received the Taylor Award for Distinguished Research\, McKnight Presidential Fellowship\, Guillermo E. Borja Award\, and McKnight Land-Grant Professorship from the University of Minnesota. \nLarge Eddy Simulation of Turbulent Cavitating Flows\nCavitation is a complex multi-scale phenomenon that has implications from intense sound production to erosion in engineering applications. This talk will discuss our efforts at developing the large-eddy simulation capability for the simulation of turbulent cavitating flows. LES of cavitation is challenged by phase change modeling\, acoustic stiffness\, sharp multiphase fronts\, strong compressibility effects\, consistent accounting of nuclei\, broadband turbulence and subgrid effects. \nLES of partial cavitation will be discussed under the same conditions as experiments in a sharp wedge configuration.  Physical mechanisms of cavity transition observed in the experiments\, i.e.\, re-entrant jet and bubbly shock waves\, are both captured in the LES over their respective regimes. Vapor volume fraction data obtained from the LES will be quantitatively compared to X-ray densitometry\, and the results will be discussed. Cavitation nuclei are likely to be introduced through the free-stream as well as at solid surfaces. We will present a novel approach based on Gibbs free energy minimization to predict nuclei concentrations. The results from the proposed work will be applied to account for dissolved gas content in CSM measurements and predict several decades of experimentally observed trends in nuclei concentrations. Cavitating flows possess a range of vapor length scales ranging from tiny vapor bubbles to large vapor pockets. We will discuss a compressible hybrid model to capture both sub-grid vapor nuclei and massive sheet cavity dynamics. Finally\, physical aspects of inception due to the interaction of a counter–rotating vortex pair generated behind a pair of hydrofoils will be presented. \n\n  \nThe MICDE Fall 2025 Seminar Series is open to all. University of Michigan faculty and students. \nThis is an in-person event. \nGraduate Certificate in Computational Discovery and Engineering\, please use this form to record your attendance. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-me-seminar-krishnan-mahesh-professor-university-of-michigan-name/
LOCATION:2150 H.H. Dow\, 2300 Hayward St\, Ann Arbor\, 48109\, United States
CATEGORIES:Computational Science,Engineering,Featured Events,Free,Mechanical Engineering,Micde Seminar,MICDE Seminar Series,Michigan Engineering,Naval Architecture and Marine Engineering
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2024/05/Mahesh-Krishnan-NAME.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:20241007T140000
DTEND;TZID=America/Detroit:20241007T150000
DTSTAMP:20260605T164012
CREATED:20240920T130536Z
LAST-MODIFIED:20240920T130536Z
UID:10000751-1728309600-1728313200@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/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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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:20241022T132000
DTEND;TZID=America/Detroit:20241022T170000
DTSTAMP:20260605T164012
CREATED:20241018T223652Z
LAST-MODIFIED:20241018T223652Z
UID:10000786-1729603200-1729616400@micde.umich.edu
SUMMARY:Conference / Symposium:MICDE ACES Mini-Symposium 2024
DESCRIPTION:This year’s focus of the Advanced Computational Science & Engineering Showcase (ACES) mini-symposium is connecting advanced algorithms\, artificial intelligence (AI)\, and high-performance computing (HPC) architectures to advance scientific discovery. The event showcases the work of the University of Michigan faculty members at the intersection of AI\, HPC\, and advanced algorithms. It also includes a panel discussion on the current trends in AI\, novel algorithms\, and computer architectures for efficient scientific applications.\nACES is an event that promotes state-of-the-art research at the University of Michigan and the current trends and hot topics in computational science and engineering. Furthermore\, it is the nucleus for increasing collaboration at the University of Michigan by offering an opportunity for faculty members to share their ideas and network during a reception. Take advantage of this exciting opportunity to connect\, learn\, and be inspired!
URL:https://micde.umich.edu/event/conference-symposiummicde-aces-mini-symposium-2024/
LOCATION:Lurie Robert H. Engin. Ctr – Johnson Rooms\, 3rd floor
CATEGORIES:Aces,Ai In Science And Engineering,Artificial Intelligence,Computation,Computational Science,Engineering,Free,High Performance Computing,In Person,Interdisciplinary,Micde,Michigan Engineering,parallel computing,Research,Science,Scientific Computing,symposium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20241107T180000
DTEND;TZID=America/Detroit:20241107T190000
DTSTAMP:20260605T164012
CREATED:20241029T230120Z
LAST-MODIFIED:20241030T170447Z
UID:10000787-1731002400-1731006000@micde.umich.edu
SUMMARY:Taking the Next Step: Graduate Studies in Computation/AI for Science and Engineering at U-M
DESCRIPTION:PhD in Scientific Computing director Eric Johnsen will speak about opportunities for undergraduate or master’s students seeking a graduate education in Computation and Artificial Intelligence for Science and Engineering at the University of Michigan. Food will be provided. Please register to attend. \nPlease register via the link: https://sessions.studentlife.umich.edu/p/track/12857 \nZoom option available after registering.
URL:https://micde.umich.edu/event/taking-the-next-step-2024/
LOCATION:GG Brown Laboratory – 2147
CATEGORIES:Aerospace Engineering,Ai In Science And Engineering,Artificial Intelligence,Astronomy,Biology,Biomedical Engineering,Biosciences,Biostatistics,Chemical Engineering,Chemistry,Civil and Environmental Engineering,Climate and Space Sciences and Engineering,College Of Engineering,Complex Systems,Computation,Computational Science,Computational Social Science,computer science,computing,Earth And Environmental Sciences,Ecology And Evolutionary Biology,Economics,Education,Electrical And Computer Engineering,Electrical Engineering and Computer Science,Engineering,Epidemiology,Free,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,High Performance Computing,Industrial and Operations Engineering,Interdisciplinary,Kinesiology,Machine Learning,Materials Science,Mathematics,Mechanical Engineering,Medicine,Micde,Michigan Engineering,Naval Architecture and Marine Engineering,Neuroscience,Nuclear Engineering and Radiological Sciences,Pharmacy,Physics,Politics,Prospective Graduate Students,Psychology,Public Health,Public Policy,Rackham,Research,Robotics,Scientific Computing,Statistics,Talk,Undergraduate,Undergraduate Students,Virtual,Workshop
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2024/10/Happening@UM.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20250924T150000
DTEND;TZID=America/Detroit:20250924T170000
DTSTAMP:20260605T164012
CREATED:20250822T192306Z
LAST-MODIFIED:20260522T151523Z
UID:10000828-1758726000-1758733200@micde.umich.edu
SUMMARY:MICDE Nobel Prize Lectures
DESCRIPTION:Speakers:\n\nCharles Brooks\, Warner-Lambert/Parke-Davis Professor of Chemistry\, Cyrus Levinthal Distinguished University Professor of Chemistry and Biophysics\, will talk about the 2024 Nobel Prizes in Chemistry.\nVeera Sundararaghavan\, Professor of Aerospace Engineering and the director of Multiscale Structural Simulations Laboratory\, will talk about the 2024 Nobel Prizes in Physics.\n\nNobel Prize Lectures\nThe 2024 Nobel Prizes in Physics and Chemistry spotlight the reciprocal influence between artificial intelligence and the natural sciences. This MICDE special event examines the science and scientists recognized for foundational advances in neural networks that underpin modern machine learning (Physics)\, and for AI-enabled breakthroughs in protein structure prediction and computational protein design (Chemistry). The lectures will be followed by a moderated panel and an open\, cross-disciplinary discussion. \nPanel Discussion:\nThe panel discussion\, followed by the lectures\, will address questions such as: What can AI do for science? How can it support existing ideas and create new ones? What can science do for AI? \nPanelists:\n\nJames Wells\, Professor of Physics\, University of Michigan\nIndika Rajapakse\, Professor of Computational Medicine and Bioinformatics\, and Professor of Mathematics\, University of Michigan\nCharles Brooks\, Warner-Lambert/Parke-Davis Professor of Chemistry\, Cyrus Levinthal Distinguished University Professor of Chemistry and Biophysics\nVeera Sundararaghavan\, Professor of Aerospace Engineering and the director of Multiscale Structural Simulations Laboratory\n\nModerator:\n\nKarthik Duraisamy\, Professor of Aerospace Engineering\, Mechanical Engineering and Nuclear Engineering and Radiological Sciences and Samir and Puja Kaul Director of the Michigan Institute for Computational Discovery and Engineering
URL:https://micde.umich.edu/event/nobel-prize-lecture/
LOCATION:Forum Hall\, Palmer Commons\, 100 Washtenaw Ave\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Chemistry,College Of Engineering,Computation,Computational Modeling,Computational Science,computing,Engineering,Featured Events,Free,Generative Ai,Graduate,Graduate and Professional Students,Graduate Students,Lecture,Machine Learning,Micde,Micde Seminar,Physics
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X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Forum Hall Palmer Commons 100 Washtenaw Ave Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=100 Washtenaw Ave:geo:-83.7338523,42.2807039
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20251007T114500
DTEND;TZID=America/Detroit:20251007T124500
DTSTAMP:20260605T164012
CREATED:20250926T143945Z
LAST-MODIFIED:20251008T041229Z
UID:10000833-1759837500-1759841100@micde.umich.edu
SUMMARY:Ph.D. in Scientific Computing Seminar Series
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. Lunch will be served. These events are open to the public\, but we request that all who plan to attend register in advance. Planned sessions will be canceled if no one signs up to present\, and registered attendees will be notified. \nIf you have any questions\, please email micde-phd@umich.edu. \nRegister to attend \n\nBridging Wavefunctions and Density Functionals: Unlocking Accurate Data for Functional Development\nDensity Functional Theory (DFT) is one of the most widely used electronic structure methods in chemistry\, physics\, and materials science\, striking a balance between accuracy and computational efficiency. However\, its accuracy is fundamentally limited by the choice of the exchange-correlation (XC) functional\, which remains an approximation in all practical applications. A key shortcoming of existing functionals is their failure to reproduce critical features of the exact XC potential\, such as the asymptotic -1/r decay and the step at integer electron transitions—features essential for correctly describing ionization energies\, band gaps\, and dissociation limits. In this work\, we take a data-driven approach to improving DFT by generating XC potentials from full configuration interaction (FCI) calculations. Using a large Slater basis\, we systematically recover key features of the exact XC potential across atomic systems and analyze their behavior. Additionally\, we compute exchange-correlation energy densities via an aufbau path integral\, ensuring consistency with total XC energy values from FCI. These highly accurate DFT quantities establish a benchmark for diagnosing errors in existing functionals and guiding the development of new approximations that incorporate wavefunction-level accuracy while retaining DFT’s efficiency. \nVaibhav Khanna (Chemistry and Scientific Computing)\nVaibhav Khanna is a Ph.D. candidate in Chemistry and Scientific Computing at the University of Michigan\, where he works under the supervision of Prof. Paul Zimmerman. His research focuses on developing improved density functionals that bridge the gap between highly accurate but computationally expensive wavefunction methods and the efficiency of the popular Density Functional Theory (DFT). By incorporating wavefunction-level accuracy\, his work aims to significantly improve the predictive power of DFT\, a widely used computational method in chemistry\, physics\, and materials science. \n\nTurbulence transport and size segregation of shock-driven multiphase flows\nThe phenomena of a shock-wave interacting with a particle suspension is observed in applications such as pulse detonation engines\, volcanic eruptions\, coal dust explosions and plume-surface interactions during spacecraft landings. Compressibility effects during these interactions give rise to complicated dynamics in the suspensions. While there has been a lot of effort and progress in modeling incompressible flows\, much less work has been done in modeling the microscale physics in turbulent flows at finite Mach numbers. Particle-resolved numerical simulations of shock passing through monodisperse suspensions are used to guide the development of subgrid-scale models for turbulence transport. Turbulent kinetic energy (TKE) is found to contribute to a significant portion of the resolved kinetic energy. A two-equation model is proposed and implemented within a hyperbolic Eulerian-based two-fluid model. The model is found to be accurate across a wide range of volume fractions and Mach numbers. Additionally\, to analyse particle dispersion and segregation in bidisperse suspensions with extreme diameter size ratios\, a hybrid numerical framework is developed\, combining an immersed boundary method for large particles with Lagrangian particle tracking of small particles.  \nArchana Sridhar (Aerospace Engineering and Scientific Computing)\nArchana is a 5th year PhD student in the Aerospace Engineering department. She is a MICDE Fellow working with Dr. Jesse Capecelatro. Her focus is on computational fluid dynamics of multiphase compressible flows. \n\n 
URL:https://micde.umich.edu/event/workshop-seminarph-d-in-scientific-computing-seminar-series/
LOCATION:North Quad – 2185
CATEGORIES:Astronomy,Chemical Engineering,Chemistry,College Of Engineering,Computational Science,computing,Electrical And Computer Engineering,Electrical Engineering and Computer Science,Engineering,Free,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,In Person,Interdisciplinary,Mechanical Engineering,Micde,Michigan Engineering,Networking,Phd Seminar,Political Science,Prospective Graduate Students,Rackham,Research,Science,Scientific Computing,Seminar,Talk
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2025/09/2025-10-07-Khanna-Sridhar.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20251028T114500
DTEND;TZID=America/Detroit:20251028T124500
DTSTAMP:20260605T164012
CREATED:20250926T143950Z
LAST-MODIFIED:20251027T214532Z
UID:10000837-1761651900-1761655500@micde.umich.edu
SUMMARY:Ph.D. in Scientific Computing Seminar Series
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. Lunch will be served. These events are open to the public\, but we request that all who plan to attend register in advance. Planned sessions will be canceled if no one signs up to present\, and registered attendees will be notified. \nIf you have any questions\, please email micde-phd@umich.edu. \nRegister to attend \n\nAutomated removal of artifactual false positive High Frequency Oscillations in intracranial EEG\nHigh frequency oscillations (HFOs) are a promising biomarker of the epileptogenic zone. Automated HFO detectors alleviate manual labeling but false positives\, artifacts\, remain. Clinicians recognize artifacts readily while viewing the EEG at standard resolution across channels\, and observing artifacts at the times of HFO events leads to a loss of trust in the detections. In this work\, we collect a new gold standard of HFO labeling using clinician expertise\, train several machine learning algorithms\, and develop an artifact filter compatible with any HFO detector to distinguish between true and false positives. \nAshley Tan (Mechanical Engineering and Scientific Computing)\nHer research involves developing engineering tools to control epilepsy. She is currently developing machine learning methods for artifact detection of a potential biomarker and investigating the effects of electrical brain stimulation on pathological activity. \n\nEmergence of three-dimensional structures from vortex pair instabilities in shocked interfacial flows\nThe Crow instability is a vortex-line instability that leads to the three-dimensional growth of perturbations in counter-rotating vortices\, with pinch-off leading to the generation of vortex rings at late time. Classically\, two incompressible\, inviscid vortices are studied in this context; in the present work\, we use numerical simulations to demonstrate that the cores which are generated from the compressible multi-material Richtmyer-Meshkov instability are subject to the Crow instability. Thus\, the onset of the Crow instability from the Richtmyer-Meshkov-induced cores can act as a mechanism for transitioning a nominally two-dimensional Richtmyer-Meshkov flow to three dimensions. \nWilliam White (Mechanical Engineering and Scientific Computing)\nWilliam is a PhD student in the Scientific Computing and Flow Physics Lab working on high-order numerical methods for compressible interfacial flows\, as well as interfacial and vortex-line hydrodynamic instabilities. \n\n 
URL:https://micde.umich.edu/event/workshop-seminarph-d-in-scientific-computing-seminar-series-3/
LOCATION:North Quad – 2185
CATEGORIES:Astronomy,Chemical Engineering,Chemistry,College Of Engineering,Computational Science,computing,Electrical And Computer Engineering,Electrical Engineering and Computer Science,Engineering,Free,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,In Person,Interdisciplinary,Mechanical Engineering,Micde,Michigan Engineering,Networking,Phd Seminar,Political Science,Prospective Graduate Students,Rackham,Research,Science,Scientific Computing,Seminar,Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20251104T114500
DTEND;TZID=America/Detroit:20251104T124500
DTSTAMP:20260605T164012
CREATED:20250926T143951Z
LAST-MODIFIED:20251009T184957Z
UID:10000838-1762256700-1762260300@micde.umich.edu
SUMMARY:Ph.D. in Scientific Computing Seminar Series
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. Lunch will be served. These events are open to the public\, but we request that all who plan to attend register in advance. Planned sessions will be canceled if no one signs up to present\, and registered attendees will be notified. \nIf you have any questions\, please email micde-phd@umich.edu. \nRegister to attend \n\nEmbodying mechano-intelligence in mechanical metastructures for in-memory phononic learning\nMechano-intelligence (MI)—intelligence embodied within the mechanical domain of materials and structures—promises autonomous systems with higher effectiveness\, efficiency\, and resilience. Rather than outsourcing information processing entirely to electronics\, MI envisions materials that store\, process\, and adapt to environmental inputs through intrinsic mechanical responses\, reducing latency and energy while improving robustness in extreme and cyber-contested conditions. Realizing MI requires three elements: a memory module to retain knowledge from inputs\, a computing module to interpret and act on information\, and a physical communication interface linking storage and computation. In this talk\, I will introduce a new approach to realizing MI in and through a reconfigurable phononic metastructures via the concept of in-memory phononic learning\, where mechanical states are programmed to encode and store information and the elastic-wave physics is harnessed to carry out computation and decision—a framework that unifies the full information chain in the mechanical domain and provides efficient\, physically interpretable processing by using elastic waves as the natural communication and processing medium.  \nYuning Zhang (Mechanical Engineering and Scientific Computing)\nYuning is a Ph.D. candidate in Mechanical Engineering under Prof. Kon-Well Wang. His research focuses on wave propagation in phononic metastructures\, and the development of physical computing and mechanical intelligence.  \n\nGlobal Probabilistic Geomagnetic Perturbation Forecasting \nAccurately predicting the horizontal component of the ground magnetic field perturbation (dBH)\, as a proxy for Geomagnetically Induced Currents (GICs)\, is crucial for estimating the impact of geomagnetic storms and remains a topic under active investigation. The current operational Geospace model is computationally expensive for fine-grid global simulations\, while existing machine learning methods consistently tend to underestimate dBH. Additionally\, these models either lack uncertainty quantification (UQ)\, which is either overlooked or treated as secondary. In this work\, as part of the NextGen SWMF project funded by NSF\, we develop a data-driven\, grid-free global model using deep Gaussian process (DGP)\, a Bayesian non-parametric approach that forecasts the dBH for the full surface of Earth with calibrated uncertainty. The model uses solar wind measurements and the Dst index as input\, and it is trained based on ground magnetometer station data provided by SuperMAG over the period 1995-2022. The model’s predictions are evaluated based on the Heidke skill score (HSS) for a total of 23 storms in 2015. We further test the model on the 2024 Gannon superstorm. The results demonstrate that our model outperforms the state-of-the-art model\, with predictions exhibiting high accuracy in mid-latitudes and high-latitude regions in the northern hemisphere. \nHongfan Chen (Mechanical Engineering and Scientific Computing)\nHongfan Chen is a fourth-year PhD student in Mechanical Engineering and the Michigan Institute for Computational Discovery and Engineering (MICDE) Scientific Computing program. His research develops computational methods for uncertainty quantification (UQ) and machine learning (ML) in complex scientific and engineering systems\, with emphases on data assimilation (DA)\, knowledge-guided machine learning\, and optimal experimental design (OED).  \n\n 
URL:https://micde.umich.edu/event/workshop-seminarph-d-in-scientific-computing-seminar-series-4/
LOCATION:North Quad – 2185
CATEGORIES:Astronomy,Chemical Engineering,Chemistry,College Of Engineering,Computational Science,computing,Electrical And Computer Engineering,Electrical Engineering and Computer Science,Engineering,Free,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,In Person,Interdisciplinary,Mechanical Engineering,Micde,Michigan Engineering,Networking,Phd Seminar,Political Science,Prospective Graduate Students,Rackham,Research,Science,Scientific Computing,Seminar,Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20251111T114500
DTEND;TZID=America/Detroit:20251111T124500
DTSTAMP:20260605T164012
CREATED:20250926T143952Z
LAST-MODIFIED:20251105T194338Z
UID:10000839-1762861500-1762865100@micde.umich.edu
SUMMARY:Ph.D. in Scientific Computing Seminar Series
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. Lunch will be served. These events are open to the public\, but we request that all who plan to attend register in advance. Planned sessions will be canceled if no one signs up to present\, and registered attendees will be notified. \nIf you have any questions\, please email micde-phd@umich.edu. \nRegister to attend \n\nPy-Conformational-Sampling: Towards Predicting Stereoselectivity\nStereoselective reactions are an integral part of organic synthesis due to the abundance of chiral centers in natural products and drug molecules. The design of these reactions remains challenging due to specific substrate requirements\, delicate reaction conditions and more importantly\, multiple competing product-forming transition states (TSs). These TSs often arise from a range of conformers present within the reactant complex. Thus\, predicting stereoselectivity requires detailed insights into favorable interactions amidst the conformational ensemble. This work introduces Py-Conformational-Sampling (PyCoSa) as a methodical approach to sample transition-metal-catalyzed stereoselective reactions. This technique\, when devoted to atroposelective Suzuki-Miyaura coupling to generate axially chiral biaryl products\, shows a variety of mechanistic possibilities through which C(sp2)–C(sp2) bond formation takes place. \nSoumik Das (Chemistry and Scientific Computing)\nSoumik is currently pursuing Ph.D. in Chemistry and Scientific Computing under the supervision of Dr. Paul Zimmerman. His research interests involve developing and applying automated and predictive computational tools using quantum chemistry for reaction design and discovery. Among other things\, he’s also a recipient of MICDE Graduate Fellowship for the academic year 2023-2024 and presented his research in MICDE conference SciFM ’24. \n\nDensity Functional Theory Simulations of Icosahedral Quasicrystals\nQuasicrystals (QCs) are fascinating materials with their long-range aperiodicity and forbidden rotational symmetry\, which opened a new type of classification in crystallography and attracted much attention to its potential applications to condensed matter\, statistical and solid-state physics. The characterization and identification of QCs after the first discovery is widely undertaken\, but thermodynamic stability and kinetics of nucleation are ongoing questions to answer the synthesizability and design novel structures. The quantum mechanical simulation including the density functional theory (DFT) is a widely used method for atomic-scale simulation\, however\, aperiodicity of QC structure makes it challenging to apply a computational model for periodic boundary frameworks. In this present work\, atomistic simulation of Tsai-type ScZn and YbCd icosahedral quasicrystals (iQCs)\, which is one of recently discovered iQCs types\, were performed using density functional theory – finite element (DFT-FE) method to study the thermodynamic stability\, role of surface energy to the stability\, and driving force of QC formation. The size-dependent and mixed-thermodynamic-and-kinetic phase diagram from quantitative theoretical calculations can provide fundamental insights into the origin of QC formation. \nWoohyeon Baek (Materials Science and Engineering and Scientific Computing)\nWoohyeon Baek is a PhD student in Materials Science and Engineering and Scientific Computing under the supervision of Dr. Wenhao Sun. He is working on the thermodynamics and kinetics of non-traditional materials formation from computational simulations including quasicrystals\, minerals\, functional materials\, and organic crystals. \n\nData-Driven Development of Constitutive Equations for Thixotropic Waxy Oil Rheology for Flow Assurance Using Symbolic Regression and PINNs\nWaxy crude oils crystallize below the wax appearance temperature\, forming networks that make rheology strongly dependent on temperature and prior shear history\, complicating pipeline restart operations. We develop a compact\, predictive modeling framework that combines data-driven and mechanistic approaches\, with all methods using differential scanning calorimetry crystallinity measurements to encode temperature effects. Symbolic regression (PySR) trained on two temperatures accurately predicts steady-state flow curves at remaining temperatures. A Fractal Isotropic-Kinematic Hardening (FIKH) model\, fitted at two temperatures for steady response\, predicts steady behavior at other temperatures; for transients\, parameters identified at 5°C reproduce rejuvenation and recovery dynamics at additional temperatures. We introduce LFP-IKH (Liquid Free-Path IKH)\, a novel approach that defines the structural state as liquid-network connectivity bounded by crystallinity. When calibrated only on steady-state data\, LFP-IKH predicts both steady and transient responses across all temperatures without refitting. This yields a mechanism-based framework that requires no parameter adjustment across temperature ranges\, making it suitable for flow-assurance prediction and restart design applications. \nSamuel Ogunwale (Chemical Engineering and Scientific Computing)\nSamuel Ogunwale is a sixth-year PhD student in Chemical Engineering working in the Larson group. His research focuses on developing predictive models for complex fluid systems\, combining mechanistic understanding with experimental validation to address industrial flow assurance challenges.
URL:https://micde.umich.edu/event/workshop-seminarph-d-in-scientific-computing-seminar-series-5/
LOCATION:North Quad – 2185
CATEGORIES:Astronomy,Chemical Engineering,Chemistry,College Of Engineering,Computational Science,computing,Electrical And Computer Engineering,Electrical Engineering and Computer Science,Engineering,Free,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,In Person,Interdisciplinary,Mechanical Engineering,Micde,Michigan Engineering,Networking,Phd Seminar,Political Science,Prospective Graduate Students,Rackham,Research,Science,Scientific Computing,Seminar,Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20251118T114500
DTEND;TZID=America/Detroit:20251118T124500
DTSTAMP:20260605T164012
CREATED:20250926T143953Z
LAST-MODIFIED:20251023T021817Z
UID:10000840-1763466300-1763469900@micde.umich.edu
SUMMARY:Ph.D. in Scientific Computing Seminar Series
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. Lunch will be served. These events are open to the public\, but we request that all who plan to attend register in advance. Planned sessions will be canceled if no one signs up to present\, and registered attendees will be notified. \nIf you have any questions\, please email micde-phd@umich.edu. \nRegister to attend \n\nTailored Ultrashort Pulse Bursts in a Gain-Managed Nonlinear Fiber Amplifier for Coherent 50fs Pulse Stacking at mJ Energies\nWe show a method of scaling gain-managed nonlinear amplifiers (GMNA) to mJ energies using feedback-driven scaling of pulse bursts that can be time-combined into a single 50fs output pulse using coherent pulse stacking.  \nLauren Cooper (Electrical Engineering and Scientific Computing)\nLauren Cooper is working on coherent pulse stacking of gain-managed nonlinear amplified pulse bursts for high power applications. She is being advised by Professor Almantas Galvanauskas in the Electrical Engineering department at the University of Michigan. \n\nLeveraging multipole models to measure rotation in time-dependent potentials\nMultipole expansion models are efficient and flexible methods by which to encode aspherical and time-dependent fluctuations in 3D functions of galactic densities and potentials. Historically these techniques have been used primary to perform orbit integration and N-body simulations. However\, it is becoming increasingly clear that the expansion series coefficients encode useful physical information that may be used to discover novel dynamics. In this talk\, I will outline my recent work using multipole expansion coefficient series\, including methods I have developed for measuring rotation in the quadrupole component and the discoveries multipole expansion has facilitated. \nNeil Ash (Astronomy and Scientific Computing)\nNeil is a 5th year graduate student in the Astronomy Department working with Professor Monica Valluri. His research interests include hydrodynamical simulations of cosmic structure formation and galactic dynamics\, with a special focus on the dark matter haloes and their interactions with the baryonic (stellar) galactic component. \n\nTracing Refractory Material in the Inner 10 AU of Protoplanetary Disks\nPlanets form in protoplanetary disks by building their cores from rocky/refractory material that drifts inward toward the central star\, establishing this material as the fundamental building blocks of all planets. Identifying the physical processes that regulate rocky material within the inner 10 AU during disk evolution is essential for understanding the formation of the observed diversity of planetary systems\, particularly for all rocky planets. In my PhD dissertation\, I study the content of rocky material in the inner regions of protoplanetary disks. I utilize spectroscopic observations across the entire electromagnetic spectrum\, using both ground-based and space telescopes\, to disclose how much rocky material reaches the inner disk and what its composition is. I have found (1) evidence for refractory depletion in the inner gas disk\, 2) connections between age and dust-trapping/planet-forming mechanisms with higher depletion values\, and 3) estimates of the impact of sublimation temperature and dust drifts on the composition of rocky material in the inner disk. Overall\, my work probes dust trapping and dust drift theories. \nMarbely Micolta (Astronomy and Scientific Computing)\nI’m a fifth-year Ph.D. student in Astronomy\, working with Prof. Nuria Calvet. I’m from Venezuela. My research aims to constrain the physical and chemical processes that regulate rocky (refractory) material\, the building blocks of planets\, in the inner 10AU of protoplanetary disks. I have developed a broad expertise in disk characterization\, using observations across the electromagnetic spectrum\, both from the ground and space telescopes.
URL:https://micde.umich.edu/event/workshop-seminarph-d-in-scientific-computing-seminar-series-6/
LOCATION:North Quad – 2185
CATEGORIES:Astronomy,Chemical Engineering,Chemistry,College Of Engineering,Computational Science,computing,Electrical And Computer Engineering,Electrical Engineering and Computer Science,Engineering,Free,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,In Person,Interdisciplinary,Mechanical Engineering,Micde,Michigan Engineering,Networking,Phd Seminar,Political Science,Prospective Graduate Students,Rackham,Research,Science,Scientific Computing,Seminar,Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20251209T114500
DTEND;TZID=America/Detroit:20251209T124500
DTSTAMP:20260605T164012
CREATED:20250926T143954Z
LAST-MODIFIED:20251208T171351Z
UID:10000841-1765280700-1765284300@micde.umich.edu
SUMMARY:Ph.D. in Scientific Computing Seminar Series
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. Lunch will be served. These events are open to the public\, but we request that all who plan to attend register in advance. Planned sessions will be canceled if no one signs up to present\, and registered attendees will be notified. \nIf you have any questions\, please email micde-phd@umich.edu. \nRegister to attend \n  \n\nImproving Slater Orbital Integration Accuracy through Prolate Spheroidal Coordinates\nThe core of electronic structure calculations is the integration of forces exerted on and by\nelectrons and nuclei in a system. Some of these interactions have forms which manifest in such a way that makes integration challenging depending on the choice of basis (specifically Slater Type Orbitals (STOs)). This difficulty lies in the fact that not all integrals have a known analytically integrable form when Slater functions are used as a basis. The Prolate Spheroidal coordinate system has only been applied to diatomic systems\, but offers an advantage in numerical integration accuracy over more generally applicable schemes. A third center is added in the PS coordinate grid in this work\, where we will note the challenges and steps taken to handle a third center. It is important to note that the addition of a third center is sufficient to solve all integrals required by the Hamiltonian under the Resolution of the Identity(RI) approximation. Analysis was performed using metrics which test the scheme directly (error values for integral matrix elements) and indirectly(applying integrals to Hartree-Fock(HF) and post-HF methods to get observables). The methods ability to accurately calculate 2-center properties allows for the use of larger basis sets which were previously unserviceable. \nAlexander Stark (Chemistry and Scientific Computing)\nThis is Alexander Stark\, he is in the Zimmerman group in the chemistry department\, his research involves refining different levels of wave-function theory as to improve the accuracy of predictions. \n\nMultiscale Modeling of Radical and Vibrational Pathways in Plasma-Assisted Ammonia Synthesis on Fe(110) and Ni(111)\nLow-temperature plasma (LTP)-assisted ammonia synthesis is a promising alternative to the Haber-Bosch process for decentralized\, renewable energy-driven production. Progress has been limited by an incomplete mechanistic understanding\, particularly the debated roles of vibrationally excited N2(g)\,ν and plasma-generated N · /H · radicals\, which may explain the unexpected insensitivity of catalyst performance across metals. We apply first-principles multiscale modeling—combining density functional theory (DFT) calculations and a packed-bed reactor microkinetic model—to disentangle these contributions to LTP-assisted NH3(g) synthesis over Fe(110) and Ni(111) catalysts. The model incorporates an experimentally derived vibrationally excited N2(g)\,ν distribution from a radiofrequency (RF) plasma source and accounts for their vibrational surface quenching. The model predicts that vibrational excitation enhances the dissociation of N2(g)\,ν on Ni but its impact on Fe is limited. Quenching of vibrationally excited N2(g)\,ν\ndue to collisions with the reactor walls and the catalyst surface does not significantly affect ammonia yields on either catalyst\, with less an an order of magnitude increase. In contrast\, Eley-Rideal reactions involving N · and H · radicals dominate ammonia formation\, bypassing the conventional rate-controlling steps of thermal catalysis on Fe and Ni materials. This mechanistic picture explains the experimentally observed insensitivity of ammonia production rates to metal catalyst identity and highlights the central role of radical chemistry in plasma-assisted ammonia synthesis. \nOluwatosin Ohiro (Chemical Engineering and Scientific Computing)\nOluwatosin earned his primary degree in petroleum and gas engineering and worked for several years as a reservoir engineer and oil asset planner. He is currently pursuing his PhD in the Chemical Engineering Department under the supervision of Prof. Bryan Goldsmith. His research focuses on the interface of computational materials science and heterogeneous catalysis. \n\nQuantifying the state of inflammation in invasive lobular breast cancer using a one-class logistic regression algorithm\nAfter invasive ductal cancer (IDC)\, invasive lobular cancer (ILC) is the second most diagnosed type of breast cancer. Given complexities with detection\, patients with ILC may be diagnosed at an advanced stage of disease\, presenting larger tumors and a higher metastasis incidence when compared to IDC. It is increasingly appreciated that the immune system plays a crucial role in both primary tumor and metastatic progression and is a complex balance of both innate and adaptive immune interactions. Critically\, the success of modern immunotherapies\, such as immune checkpoint blockade\, depends not only on the T cells on which they directly act\, but also the complicated and often contradictory influence of innate myeloid cells on the lymphoid compartment. Innate myeloid cells in the tumor microenvironment (TME) have the potential to be both pro- and anti-cancer and often present in a spectrum within the TME. The dynamic nature of these immune components makes understanding and interpreting the state of the immune system in the TME very difficult. Simple methods\, like quantifying tumor infiltrating lymphocytes (TILs) or tumor-associated macrophages (TAMs) do not account for the function of these cells\, which may be pro- or anti-tumor. We investigated the role of the immune system in the tumor microenvironment (TME) of ILC by developing a machine learning-based inflammation score (IS) that can quantify the complex state of the immune system within a primary tumor on a numerical scale from pro- to anti-inflammatory. We correlate the IS with overall survival and disease-free survival to set prognostic thresholds for immune dysregulation. \nKate Griffin (Biomedical Engineering and Scientific Computing)\nKate is a PhD Candidate in Biomedical Engineering in the Shea Lab. Her research involves engineering nanoparticles to reverse immunosuppression in metastatic breast cancer\, and using computational methods to understand immune dysregulation in the metastatic niche.
URL:https://micde.umich.edu/event/workshop-seminarph-d-in-scientific-computing-seminar-series-7/
LOCATION:North Quad – 2185
CATEGORIES:Astronomy,Chemical Engineering,Chemistry,College Of Engineering,Computational Science,computing,Electrical And Computer Engineering,Electrical Engineering and Computer Science,Engineering,Free,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,In Person,Interdisciplinary,Mechanical Engineering,Micde,Michigan Engineering,Networking,Phd Seminar,Political Science,Prospective Graduate Students,Rackham,Research,Science,Scientific Computing,Seminar,Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20260218T120000
DTEND;TZID=America/Detroit:20260218T130000
DTSTAMP:20260605T164012
CREATED:20260116T194934Z
LAST-MODIFIED:20260128T220234Z
UID:10000847-1771416000-1771419600@micde.umich.edu
SUMMARY:Ph.D. in Scientific Computing Student Seminars
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. Lunch will be served. These events are open to the public\, but we request that all who plan to attend register in advance. Planned sessions will be canceled if no one signs up to present\, and registered attendees will be notified. \nIf you have any questions\, please email micde-phd@umich.edu. \nRegister to attend \n\nHidden Relics: The Past and Present Lives of Satellites Around MW-Mass Galaxies\nMergers are one of the most important drivers of galaxy evolution\, as present-day galaxies have been built up over time through hierarchical evolution. The main bodies of galaxies have a diversity of structural properties that can be highly influenced by mergers; unfortunately\, the response of a galaxy to a merger largely erases observational markers that allow us to infer the characteristics of the merger. But simulations have shown that material deposited into a galaxy through merger is retained by its stellar halo\, thereby leaving a “fossil record” we can trace. My PhD thesis takes a multi-faceted approach to uncover this historical record and learn what processes govern how galaxies form and evolve\, from massive Milky Way-like galaxies to their small\, ultra-faint companions. I have harnessed the power of resolved-star photometry and spectroscopy to 1) create the deepest stellar halo map of the nearby galaxy M94\, revealing that it underwent one of the quietest merger histories among galaxies of similar stellar mass\, 2) illuminate the structural diversity of faint satellite galaxies around M81\, improving ground-based characterizations and finding one of the most concentrated satellites we know of\, and 3) make the first-ever measurement of the kinematics of NGC 253’s stellar halo\, finding that it has slight prograde bulk motion and pioneering fiber-fed spectroscopy in a low S/N regime. With the techniques I have developed\, I am laying the foundation for doing resolved stellar population science with next-generation observing facilities such as the Rubin Observatory\, Roman Space Telescope\, and the ELT. \nKatya Gozman (Astronomy and Scientific Computing)\nKatya is a 6th year PhD student in the Astronomy Department working with Prof. Eric Bell. She uses ground- and space-based observations of resolved stars in the outskirts of nearby galaxies to understand their merger histories and satellite populations. \n\nFracture Criterion for Ultra-Low Cycle Fatigue Based on Measured Void Characteristics\nCommonly used ultra-low cycle fatigue (ULCF) fracture models rely on idealized void shapes and sizes. However\, the void shapes generated by real fracture processes are irregular\, forming non-uniform half-dimples and voids on the fracture surface. Therefore\, a gap remains in validating the link between simulated void behavior and fracture initiation with actual fracture surface data. To address this\, monotonic tensile and ULCF tests were performed on axisymmetric circumferential tensile (CNT) specimens with medium to high stress triaxiality\, and dimple-voids were examined using scanning electron microscope (SEM) fractographs. For the first time\, a correlation between simulated and actual void formation under ULCF was established\, leading to a new fracture criterion based on measured void features. \nMin-Chun Han (Civil and Environmental Engineering and Scientific Computing)\nMin-Chun is a Ph.D. candidate in Civil and Environmental Engineering. Her research focuses on the behavior of structures and structural materials under extreme loading and environmental conditions. \n\nA Holistic Performance-Based Framework for Assessing Coupled Building Envelope–Structural System Performance under Extreme Winds\nHigh-rise building envelopes are vulnerable to extreme winds\, requiring robust performance assessment to ensure safety. Existing models often assume linear or simplified post-elastic structural behavior\, overlooking strong nonlinearities that can arise near collapse. This study presents a performance-based computational framework combining high-fidelity nonlinear structural modeling with a progressive damage model for envelope assessment. Localized damage mechanisms\, including yielding\, buckling\, low-cycle fatigue\, and fracture\, are simulated\, and envelope vulnerability is quantified via component-level sequential fragility functions. Dynamic wind pressures are captured using wind tunnel-informed stochastic models\, while internal pressures at damage-induced openings are estimated via Bernoulli’s equation and mass conservation. A case study of a 45-story reinforced concrete building in New York City providing insights into the global probabilistic performance and the local coupled progression of envelope and structural damage under extreme wind events. \nJieling Jiang (Civil and Environmental Engineering and Scientific Computing)\nShe is currently a phd candidate in the civil engineering department\, working on developing next-generation probabilistic modeling frameworks for high-rise building systems under extreme natural hazards. Her research involves high fidelity simulation and stochastic simulation methods.  \n\n  \nRegister to attend
URL:https://micde.umich.edu/event/phd-seminar-20260218/
LOCATION:Room 4425\, Green Court Building
CATEGORIES:Aerospace Engineering,Chemical Engineering,Chemistry,Civil and Environmental Engineering,College Of Engineering,Computation,Computational Medicine,Computational Modeling,Computational Science,Computational Social Science,Data Science,Engineering,Free,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,Health Behavior & Health Equity,In Person,Interdisciplinary,Machine Learning,Materials Science,Micde,Phd Seminar,Political Science,Prospective Graduate Students,Public Health,Research,Science,Scientific Computing,Sessions
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20260225T120000
DTEND;TZID=America/Detroit:20260225T130000
DTSTAMP:20260605T164012
CREATED:20260116T194936Z
LAST-MODIFIED:20260130T183451Z
UID:10000848-1772020800-1772024400@micde.umich.edu
SUMMARY:Ph.D. in Scientific Computing Student Seminars
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. Lunch will be served. These events are open to the public\, but we request that all who plan to attend register in advance. Planned sessions will be canceled if no one signs up to present\, and registered attendees will be notified. \nIf you have any questions\, please email micde-phd@umich.edu. \nRegister to attend \n\nEstimating potential-dependent physicochemical properties at metal–electrolyte interfaces using machine learning interatomic potentials\nMetal–electrolyte interfaces play a central role in electrocatalysis\, energy storage\, and environmental remediation. Understanding the structure and properties of these interfaces is therefore essential to designing efficient electrochemical systems. Density functional theory (DFT)-based molecular dynamics (MD) can accurately capture interfacial structure but is restricted to short timescales and small system sizes. To overcome these limitations\, we develop machine learning interatomic potentials (MLIPs) using the MACE architecture within an active learning workflow to model aqueous NaCl electrolytes in contact with Au\, Cu\, and Rh (111) electrodes. The resulting committee of MLIPs achieves DFT-level accuracy across 21 electrolyte–metal systems spanning a wide range of surface charge densities. MACE–MD simulations reproduce key interfacial properties obtained from ab initio MD\, including water density profiles\, water orientation\, and chemisorbed water coverage. \nOur simulations reveal a universal trend across all metals: the total coverage of water and ions decreases with increasing surface charge density or potential\, reaches a minimum at or slightly below the pzc\, and increases thereafter. Overall\, this work demonstrates that MLIPs based on the MACE architecture enable long-timescale\, first-principles-accurate simulations of metal electrolyte interfaces and provide detailed mechanistic insight into their potential-dependent physicochemical properties. \nAnkit Mathanker (Chemical Engineering and Scientific Computing)\nAnkit Mathanker is a Ph.D. researcher in Chemical Engineering in the Goldsmith Lab. His work leverages DFT\, AIMD\, and machine-learning interatomic potentials to understand and predict electrochemical interfacial phenomena relevant to catalysis and energy conversion. \n\nPredictive Modeling and Inverse Design of High-Entropy Semiconductor Alloys\nThe vast compositional space of high-entropy semiconductors offers unprecedented tunability but presents a significant challenge for traditional screening methods. This talk outlines a multi-tiered computational strategy designed to navigate this complexity\, applied specifically to ferroelectric high-entropy III-nitrides (AlGaInScY-N). We detail a comprehensive workflow that begins with high-throughput first-principles calculations to generate accurate stability and property datasets. We then demonstrate how this data fuels a dual-pronged AI approach\, which uses generative machine learning (symbolic regression) to discover interpretable governing equations for phase stability\, and black-box machine learning models to rapidly predict structural properties and band gaps beyond the training set. This synergistic framework not only accelerates materials discovery but also reveals the physical descriptors driving entropy stabilization and ferroelectric performance. \nYujie Liu (Materials Science and Engineering and Scientific Computing)\nYujie is a Ph.D. student from materials science and engineering. He is working on semiconductor materials design\, combineing high-throughput first-principles workflows with surrogate machine-learning models. \n\nRapid 3D Localization of Cavitation Events for Histotripsy Monitoring\nHistotripsy is a noninvasive ultrasound therapy that relies on controlled cavitation to mechanically fractionate tissue\, but accurately localizing cavitation events in real time remains a challenge\, particularly in the presence of acoustic aberrations and attenutation. This talk presents computational and experimental methods for rapid three-dimensional localization of inertial cavitation events using a large-aperture\, receive-capable focused ultrasound array. By combining narrowband signal processing with passive acoustic mapping techniques\, these methods enable high-accuracy cavitation localization at clinically relevant treatment rates. Experimental validation using optical imaging and rib-mimicking phantoms demonstrates the potential of these approaches for treatment monitoring and feedback control in therapeutic ultrasound. \nMikey Komaiha (Biomedical Engineering and Scientific Computing)\nMikey is a Ph.D. candidate in the Department of Biomedical Engineering at the University of Michigan and a member of the Histosonics research group. His research focuses on computational signal processing and experimental methods for cavitation localization and monitoring in therapeutic ultrasound applications. \n\nRegister to attend
URL:https://micde.umich.edu/event/workshop-seminar2025-2026-micde-ph-d-in-scientific-computing-student-seminars-3/
LOCATION:Room 4425\, Green Court Building
CATEGORIES:Aerospace Engineering,Chemical Engineering,Chemistry,Civil and Environmental Engineering,College Of Engineering,Computation,Computational Medicine,Computational Modeling,Computational Science,Computational Social Science,Data Science,Engineering,Free,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,Health Behavior & Health Equity,In Person,Interdisciplinary,Machine Learning,Materials Science,Micde,Phd Seminar,Political Science,Prospective Graduate Students,Public Health,Research,Science,Scientific Computing,Sessions
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20260325T120000
DTEND;TZID=America/Detroit:20260325T130000
DTSTAMP:20260605T164012
CREATED:20260116T194939Z
LAST-MODIFIED:20260318T200653Z
UID:10000851-1774440000-1774443600@micde.umich.edu
SUMMARY:Ph.D. in Scientific Computing Student Seminars
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. Lunch will be served. These events are open to the public\, but we request that all who plan to attend register in advance. Planned sessions will be canceled if no one signs up to present\, and registered attendees will be notified. \nIf you have any questions\, please email micde-phd@umich.edu. \nRegister to attend \n\nA Parametric Approach for Solving Convex Quadratic Optimization with Indicators Over Trees\nThis talk investigates convex quadratic optimization problems involving n indicator variables\, each associated with a continuous variable\, particularly focusing on scenarios where the matrix Q defining the quadratic term is positive definite and its sparsity pattern corresponds to the adjacency matrix of a tree graph. We introduce a graph-based dynamic programming algorithm that solves this problem in time and memory complexity of O(n2). Central to our algorithm is a precise parametric characterization of the cost function across various nodes of the graph corresponding to distinct variables. Our computational experiments conducted on both synthetic and real-world datasets demonstrate the superior performance of our proposed algorithm compared to existing algorithms and state-of-the-art mixed-integer optimization solvers. \nAaresh Bhathena (Industrial and Operational Engineering and Scientific Computing)\nAaresh Bhathena is a PhD student in Industrial and Operations Engineering at the University of Michigan\, advised by Professor Salar Fattahi. His research focuses on solving optimization problems that arise in machine learning and operations research. \n\nReconstruction of 3D Bacterial Genome Structures from Hi-C Data Using Diffusion Model\nIn this talk\, I will present a generative framework for reconstructing three-dimensional bacterial genome structures from Hi-C data. Existing methods predominantly yield a single deterministic structure\, overlooking the inherent heterogeneity and dynamic nature of chromosome organization. To address this limitation\, I applied a conditional latent diffusion model that generates ensembles of genome conformations conditioned on contact frequencies. This project aims to deliver a diffusion-based reconstruction method that provides uncertainty-aware\, population-level representations of bacterial genome organization. \nXiaofeng Dai (Chemistry and Scientific Computing)\nXiaofeng’s research focuses on bacterial genome organization. His work integrates quantitative microscopy and data-driven analysis to understand how chromosomes are structured and regulated in bacteria cells. \n\nIncorporating Logic in Online Preference Learning for Safe Personalization of Autonomous Vehicles\nCustomizing autonomous vehicles to align with user preferences while ensuring safety may significantly impact their adoption. Collecting user preference data by asking a large number of comparison questions can be demanding. In this work\, we use active learning along with temporal logic descriptions of constraints to enable safe learning of preferences with a reduced number of questions. We take a Bayesian inference approach combined with Weighted Signal Temporal Logic (WSTL)\, resulting in a WSTL formula that can rank signals based on user preferences and be used for correct-and-custom-by-construction control synthesis. Our method is practical for formulas and signals with various complexity since we compute STL-related values offline. We provide an upper bound for the number of answers in disagreement with user answers. We demonstrate the performance of our method both on synthetic data and by human subject experiments in an immersive driving simulator. We consider two driving scenarios\, one involving a vehicle approaching a pedestrian crossing and the other with an overtake maneuver. Our results over synthetic experiments with ground truth weight valuation show that our query selection algorithm converges faster than random query selection. Human subject study results show an average agreement of 94% with user answers during training\, and 79% during validation (which increases to 86% when restricted to high confidence results). \nRuya Karagulle (Electrical and Computer Engineering and Scientific Computing)\nRuya Karagulle is a PhD candidate in the Ozay Group whose research focuses on integrating formal methods and human feedback for safe and personalized control synthesis. Her work has been recognized through multiple fellowship awards\, including Rackham Predoctoral Fellowship. \n\nRegister to attend
URL:https://micde.umich.edu/event/workshop-seminar2025-2026-micde-ph-d-in-scientific-computing-student-seminars-6/
LOCATION:Room 4425\, Green Court Building
CATEGORIES:Aerospace Engineering,Chemical Engineering,Chemistry,Civil and Environmental Engineering,College Of Engineering,Computation,Computational Medicine,Computational Modeling,Computational Science,Computational Social Science,Data Science,Engineering,Free,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,Health Behavior & Health Equity,In Person,Interdisciplinary,Machine Learning,Materials Science,Micde,Phd Seminar,Political Science,Prospective Graduate Students,Public Health,Research,Science,Scientific Computing,Sessions
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20260408T120000
DTEND;TZID=America/Detroit:20260408T130000
DTSTAMP:20260605T164012
CREATED:20260116T194941Z
LAST-MODIFIED:20260522T153839Z
UID:10000852-1775649600-1775653200@micde.umich.edu
SUMMARY:Ph.D. in Scientific Computing Student Seminars
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. Lunch will be served. These events are open to the public\, but we request that all who plan to attend register in advance. Planned sessions will be canceled if no one signs up to present\, and registered attendees will be notified. \nIf you have any questions\, please email micde-phd@umich.edu. \nRegister to attend \n\nPhysics-based Simulation of Solar Energetic Particles Using the Solar Wind with Field Lines and Energetic Particles Model\nSolar energetic particles (SEPs) can pose hazardous radiation risks to both humans and spacecraft electronics in space. In this talk\, we present recent advances in physics-based simulation of solar energetic particles (SEPs) using the Solar Wind with Field Lines and Energetic Particles (SOFIE) model within the Space Weather Modeling Framework. We describe the development of a particle-conserving numerical scheme for particle acceleration and transport\, together with a shock-capturing tool for coronal mass ejection-driven shocks\, and show their application to one of the historical SEP events with multi-spacecraft comparison. We also discuss SOFIE’s recent evaluation unnder a simulated operational condition at NOAA’s Space Weather Prediction Center\, where we demonstrated its ability to deliver SEP forecasts significantly faster than real time\, supporting future space weather forecasting and human space exploration. \nWeihao Liu (Climate and Space Sciences and Engineering and Scientific Computing)\nWeihao Liu is a Ph.D. student in Climate and Space Sciences and Engineering at the University of Michigan. His research focuses on physics-based modeling of solar coronal mass ejections and solar energetic particles\, and space weather forecasting\, with an emphasis on developing and applying numerical models to understand particle acceleration and transport in the heliosphere. \n\nRegister to attend
URL:https://micde.umich.edu/event/workshop-seminar2025-2026-micde-ph-d-in-scientific-computing-student-seminars-7/
LOCATION:Room 4425\, Green Court Building
CATEGORIES:Aerospace Engineering,Chemical Engineering,Chemistry,Civil and Environmental Engineering,College Of Engineering,Computation,Computational Medicine,Computational Modeling,Computational Science,Computational Social Science,Data Science,Engineering,Free,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,Health Behavior & Health Equity,In Person,Interdisciplinary,Machine Learning,Materials Science,Micde,Phd Seminar,Political Science,Prospective Graduate Students,Public Health,Research,Science,Scientific Computing,Sessions
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20260422T120000
DTEND;TZID=America/Detroit:20260422T130000
DTSTAMP:20260605T164012
CREATED:20260116T194944Z
LAST-MODIFIED:20260522T154547Z
UID:10000855-1776859200-1776862800@micde.umich.edu
SUMMARY:Ph.D. in Scientific Computing Student Seminar
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. Lunch will be served. These events are open to the public\, but we request that all who plan to attend register in advance. Planned sessions will be canceled if no one signs up to present\, and registered attendees will be notified. \nIf you have any questions\, please email micde-phd@umich.edu. \nRegister to attend \n\nThomas Coons (Mechanical Engineering and Scientific Computing)\n\nCelia Kelly (Mechanical Engineering and Scientific Computing)\n\nLiliang Wang (Aerospace Engineering and Scientific Computing)\n\nRegister to attend
URL:https://micde.umich.edu/event/phd-seminar-20260422/
LOCATION:Room 4425\, Green Court Building
CATEGORIES:Aerospace Engineering,Chemical Engineering,Chemistry,Civil and Environmental Engineering,College Of Engineering,Computation,Computational Medicine,Computational Modeling,Computational Science,Computational Social Science,Data Science,Engineering,Free,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,Health Behavior & Health Equity,In Person,Interdisciplinary,Machine Learning,Materials Science,Micde,Phd Seminar,Political Science,Prospective Graduate Students,Public Health,Research,Science,Scientific Computing,Sessions
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20260429T120000
DTEND;TZID=America/Detroit:20260429T130000
DTSTAMP:20260605T164012
CREATED:20260126T142044Z
LAST-MODIFIED:20260505T205036Z
UID:10000857-1777464000-1777467600@micde.umich.edu
SUMMARY:Ph.D. in Scientific Computing Student Seminar
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. Lunch will be served. These events are open to the public\, but we request that all who plan to attend register in advance. Planned sessions will be canceled if no one signs up to present\, and registered attendees will be notified. \nIf you have any questions\, please email micde-phd@umich.edu. \nRegister to attend \n  \n\nProfit-Driven Polarization: The Algorithmic Market for Partisan Attention\n[Removed] \nJun Fang (Political Science and Scientific Computing)\nJun Fang is a PhD candidate at the University of Michigan\, where he is pursuing a joint degree in Political Science and Scientific Computing. \n\nGanlin Chen (Materials Science and Engineering and Scientific Computing) \n\nRegister to attend
URL:https://micde.umich.edu/event/phd-seminar-20260429/
LOCATION:Room 4425\, Green Court Building
CATEGORIES:Aerospace Engineering,Chemical Engineering,Chemistry,Civil and Environmental Engineering,College Of Engineering,Computation,Computational Medicine,Computational Modeling,Computational Science,Computational Social Science,Data Science,Engineering,Free,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,Health Behavior & Health Equity,In Person,Interdisciplinary,Machine Learning,Materials Science,Micde,Phd Seminar,Political Science,Prospective Graduate Students,Public Health,Research,Science,Scientific Computing,Sessions
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20260603T120000
DTEND;TZID=America/Detroit:20260603T130000
DTSTAMP:20260605T164012
CREATED:20260511T145029Z
LAST-MODIFIED:20260529T151942Z
UID:10000860-1780488000-1780491600@micde.umich.edu
SUMMARY:Ph.D. in Scientific Computing Student Seminar
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. Lunch will be served. These events are open to the public\, but we request that all who plan to attend register in advance. Planned sessions will be canceled if no one signs up to present\, and registered attendees will be notified. \nIf you have any questions\, please email micde-phd@umich.edu. \nRegister to attend \n  \n\nPersona-Based Modeling of Human Opinion from Social Media at Population Scale\nWhat does it take to simulate a specific human being rather than a demographic stereotype? While large language models (LLMs) generate plausible human-like text\, existing simulations rely heavily on demographic correlations\, which strip away individual heterogeneity and yield concentrated\, homogenous responses. We introduce SPIRIT (Semi-structured Persona Inference and Reasoning for Individualized Trajectories)\, a framework designed explicitly for simulation rather than prediction. SPIRIT infers psychologically grounded\, semi-structured personas from public social-media traces\, integrating structured attributes (e.g.\, personality traits and world beliefs) with unstructured narrative signals reflecting values and lived experience. These personas condition LLM-based agents to act as specific individuals when answering survey questions or responding to events. Using the Ipsos KnowledgePanel\, a nationally representative probability sample of U.S. adults\, we show that SPIRIT-conditioned simulations recover self-reported responses more faithfully than demographic baselines and reproduce human-like heterogeneity in response patterns. We further demonstrate that persona banks can function as virtual respondent panels for studying both stable attitudes and time-sensitive public opinion. \nMao Li (Survey and Data Science and Scientific Computing)\nMao Li is a Ph.D. candidate in Survey and Data Science and Scientific Computing at the University of Michigan. His research develops and applies large language models and other computational methods to study public opinion\, social media discourse\, and survey-related questions. \n\nNumerical Study of Bidirectional Shallow-Water Wave Kinetics\nThe traditional view is that one-dimensional shallow-water waves do not admit a wave kinetic description\, as their dynamics can be described by integrable systems. We revisit this problem by studying bidirectional shallow-water waves using the integrable Kaup-Boussinesq (KB) equation and a related non-integrable variant. For both systems\, a normal-form transformation yields interaction coefficients with the same general structure\, differing only through the dispersion relation. We numerically confirm that the coefficient vanishes exactly on the resonant manifold for the KB equation\, consistent with integrability\, while the non-integrable model admits a non-zero resonant coefficient and thus a non-trivial wave kinetic equation (WKE). \nThe WKE is derived in the infinite-domain\, weak-nonlinearity limit\, where the dynamics are dominated by exact resonances. In numerical simulations\, we no longer operate in this regime as computations are performed on a discrete grid at finite nonlinearity. Consequently\, exact resonances may be sparse or absent\, allowing for quasi-resonant interactions to play a significant role. We perform a set of numerical experiments demonstrating that these quasi-resonant interactions govern the observed spectral evolution. Despite differing on the exact resonant manifold\, the integrable KB and non-integrable models exhibit nearly identical stationary spectra\, revealing the dominant role of near-resonant interactions and elucidating the wave-kinetic picture in shallow-water and integrable systems. \nAshleigh Simonis (Naval Architecture & Marine Engineering and Scientific Computing)\nAshleigh is a Ph.D. candidate in the Department of Naval Architecture and Marine Engineering\, advised by Dr. Yulin Pan. Her research focuses on theoretical and numerical studies of wave turbulence and coherent structures in dispersive wave systems. \n\n  \nRegister to attend
URL:https://micde.umich.edu/event/ph-d-in-scientific-computing-student-seminar/
LOCATION:Room 4425\, Green Court Building
CATEGORIES:Aerospace Engineering,Chemical Engineering,Chemistry,Civil and Environmental Engineering,College Of Engineering,Computation,Computational Medicine,Computational Modeling,Computational Science,Computational Social Science,Data Science,Engineering,Free,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,Health Behavior & Health Equity,In Person,Interdisciplinary,Machine Learning,Materials Science,Micde,Phd Seminar,Political Science,Prospective Graduate Students,Public Health,Research,Science,Scientific Computing,Sessions
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20260625T120000
DTEND;TZID=America/Detroit:20260625T130000
DTSTAMP:20260605T164012
CREATED:20260511T145137Z
LAST-MODIFIED:20260524T213602Z
UID:10000861-1782388800-1782392400@micde.umich.edu
SUMMARY:Ph.D. in Scientific Computing Student Seminar
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. Lunch will be served. These events are open to the public\, but we request that all who plan to attend register in advance. Planned sessions will be canceled if no one signs up to present\, and registered attendees will be notified. \nIf you have any questions\, please email micde-phd@umich.edu. \nRegister to attend \nHardik Patil (Civil & Environmental Engineering and Scientific Computing)\n\nZiqi Wang (Mechanical Engineering and Scientific Computing)\n\nTopic Modeling of Firearm-Related Social Media Content for Survey Development\nEsther Lee (Health Behavior & Health Equity and Scientific Computing)
URL:https://micde.umich.edu/event/ph-d-in-scientific-computing-student-seminar-2/
LOCATION:Room 4425\, Green Court Building
CATEGORIES:Aerospace Engineering,Chemical Engineering,Chemistry,Civil and Environmental Engineering,College Of Engineering,Computation,Computational Medicine,Computational Modeling,Computational Science,Computational Social Science,Data Science,Engineering,Free,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,Health Behavior & Health Equity,In Person,Interdisciplinary,Machine Learning,Materials Science,Micde,Phd Seminar,Political Science,Prospective Graduate Students,Public Health,Research,Science,Scientific Computing,Sessions
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END:VCALENDAR