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DTSTART;TZID=America/Detroit:20260811T120000
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UID:10000863-1786449600-1786453200@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 \nImprove influenza burden estimation through multiplier prediction and true case estimation\nInfluenza infection burden estimation in the US currently relies on multipliers that are not timely updated. This study aims to utilize Michigan Medicine patient records and local longitudinal cohorts to describe and predict next season values for influenza case-to-hospitalization ratios and percent of cases seeking outpatient care using machine learning classification models. We also estimated true number of inpatient and outpatient influenza cases in the capture population of five Michigan Medicine sites\, which was validated through scenario simulations using an agent-based model. \nTroy Zirui Zhou (Epidemiology and Scientific Computing)\nZhou research involves influenza burden estimation\, phylodynamics\, and modeling. \n\nFluttering and Tumbling in Falling Plates\nFalling thin bodies are ubiquitous in nature: gliding birds and falling leaves are familiar examples. In this talk\, we discuss how fast\, low order numerical models can help explain the fundamental physics behind such motions. \nYu Jun Loo (Mathematics and Scientific Computing)\nLoo Yu Jun is a PhD candidate in pure mathematics and scientific computing. He works with Professor Silas Alben on developing fast computational methods for bio-locomotion. \n\nFrom the Method of Averaging to a Numerical Method to Simulate Neuronal Populations\nWe present a novel numerical algorithm that incorporates phase reduction techniques into Lagrangian particle methods to study population-level behaviors of noisy coupled oscillators. We use elliptical Gaussian basis functions to solve the Fokker-Planck equation that describes the evolution of the probability density function using a score-based approach. We propose the shrinkage of particles based on phase reduction\, which takes advantage of the traditional approach that simplifies periodic dynamical systems. At the same time\, we preserve the structure of the possibly high-dimensional state space and effectively avoid oversimplification. Our method reduces the number of particles and accelerates the particle updating process\, thereby achieving higher computational efficiency. \nAlexandra Du (Applied and Interdisciplinary Mathematics and Scientific Computing)\nAlexandra obtained her bachelor’s degree from Oberlin College. She works with Professor Daniel Forger in the math department. Her research focuses on applied dynamical systems and computational neuroscience.
URL:https://micde.umich.edu/event/ph-d-in-scientific-computing-student-seminar-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
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2026/06/4-29-Fang-Lee-Chen.png
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DTSTART;TZID=America/Detroit:20260818T120000
DTEND;TZID=America/Detroit:20260818T130000
DTSTAMP:20260811T222310Z
CREATED:20260617T195355Z
LAST-MODIFIED:20260811T222310Z
UID:10000864-1787054400-1787058000@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 \nAccelerating Molecular Simulations with Multilayer Machine-Learned Interatomic Potentials\nMachine-learned interatomic potentials (ML-IAPs) enable near-quantum-accurate molecular simulations at significantly lower computational cost than first-principles methods. However\, accurately modeling covalently bonded systems requires resolving both highly featured short-range interactions and smoother long-range interactions\, creating a trade-off between model complexity and computational efficiency. We address this challenge with a multilayer representation that decomposes the potential energy surface into separate short-range and long-range models\, implemented within the ChIMES ML-IAP framework. Evaluated on propane\, water\, and reactive C/O systems spanning diverse thermodynamic conditions\, the multilayer approach matches the accuracy of conventional single-layer models while reducing computational cost by more than an order of magnitude. A hyperparameter sensitivity analysis further provides practical guidelines for model design. These results establish multilayer ChIMES as a general framework for substantially improving ML-IAP efficiency without compromising predictive accuracy. \nAwwal Oladipupo (Chemical Engineering and Scientific Computing)\nAwwal Oladipupo is a Ph.D. candidate in Chemical Engineering and Scientific Computing at the University of Michigan. His research focuses on developing machine learning-enabled atomistic simulation methods\, multiscale modeling frameworks\, and scientific software to accelerate the discovery and design of materials for energy\, environmental\, and chemical applications\, with an emphasis on improving the accuracy\, scalability\, and computational efficiency of molecular simulations.
URL:https://micde.umich.edu/event/ph-d-in-scientific-computing-student-seminar-4/
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
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2026/06/4-29-Fang-Lee-Chen-1.png
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