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DTSTART;TZID=America/Detroit:20260225T120000
DTEND;TZID=America/Detroit:20260225T130000
DTSTAMP:20260604T024940
CREATED:20260116T194936Z
LAST-MODIFIED:20260130T183451Z
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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:20260317T160000
DTEND;TZID=America/Detroit:20260317T170000
DTSTAMP:20260604T024940
CREATED:20260306T144640Z
LAST-MODIFIED:20260306T144640Z
UID:10000859-1773763200-1773766800@micde.umich.edu
SUMMARY:Mathematics - MICDE - MCAIM joint colloquium: Peter Bosler\, Sandia National Laboratories
DESCRIPTION:Bio:  Dr. Bosler received his B.S. degree with Honors in Oceanography from the U.S. Naval Academy in 2002. In 2002-2007\, he served as an officer in the U.S. Navy with active duty service that included both surface warfare and meteorology/oceanography operational support. Upon completing his service\, he started graduate studies at the University of Michigan and received a Ph.D. degree in Applied and Interdisciplinary Mathematics in 2013. In 2014\, he received the John von Neumann Postdoctoral Fellowship at Sandia National Laboratories\, and thereafter\, he became a staff member in the Center for Computing Research at Sandia. His projects involve close coupling between numerical methods development\, data collection\, application science\, and high-performance computing. Recent projects focus on climate modeling and plasma physics. Dr. Bosler received the Department of Energy Early Career Award for Advanced Scientific Computing in 2022 and the Presidential Early Career Award for Science and Engineering in 2025. \nAccelerating Earth System Simulation\nAbstract: Providing high-quality “actionable information” for strategic risk analysis is amongst the primary goals of the U.S. Department of Energy’s Exascale Earth System Model (E3SM). The simulation speed required to generate high-quality localized predictions at seasonal-to-decadal time scales is very high. In this talk\, we highlight some algorithmic design decisions that combine new research with classical numerical methods to enable E3SM’s ultra-high resolution configuration to achieve exascale performance and win the inaugural Gordon Bell Prize for Climate in 2023. Our design strategies tailor mathematical methods to both the unique features of the application space and to the heterogeneous computing architectures of exascale supercomputers. Ultimately\, these efforts doubled the speed of the most computationally demanding component of E3SM\, its atmosphere model. We will also discuss new and ongoing research associated with opportunities afforded by these performance gains. \n  \n\n  \nThe MICDE 2025-26 Seminar Series is open to all. \nGraduate Certificate in Computational Discovery and Engineering\, and MICDE fellows\, please use this form to record your attendance. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/math-micde-mcaim-peter-bosler-sandia/
LOCATION:1360 East Hall\, 530 Church St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Climate and Space Sciences and Engineering,College Of Engineering,Featured Events,Mathematics,Mechanical Engineering,Micde,Micde Seminar,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2026/03/Peter-Bosler.png
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X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=1360 East Hall 530 Church St. Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=530 Church St.:geo:-83.7351764,42.2757302
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20260325T120000
DTEND;TZID=America/Detroit:20260325T130000
DTSTAMP:20260604T024940
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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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20260408T120000
DTEND;TZID=America/Detroit:20260408T130000
DTSTAMP:20260604T024940
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:20260604T024940
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:20260604T024940
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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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20260529T110000
DTEND;TZID=America/Detroit:20260529T120000
DTSTAMP:20260604T024940
CREATED:20260514T175620Z
LAST-MODIFIED:20260601T195905Z
UID:10000862-1780052400-1780056000@micde.umich.edu
SUMMARY:MICDE - Mechanical Engineering seminar: Phani Motamarri\, Indian Institute of Science\, Bangalore
DESCRIPTION:Bio: Phani Motamarri is an Assistant Professor in the Department of Computational and Data Sciences at the Indian Institute of Science\, Bengaluru\, where he leads the MATRIX Lab. He is an alumnus of the University of Michigan–Ann Arbor\, where he earned his PhD in Mechanical Engineering.\nHis research lies at the intersection of computational mechanics\, materials science\, numerical analysis\, and high-performance computing. His work focuses on developing mathematical techniques and hardware-aware algorithms for quantum modeling of materials\, with applications to structural and functional materials and multiscale modeling methodologies. He is also interested in machine learning frameworks for accelerating materials discovery and quantum computing\, particularly in the context of quantum-centric supercomputing. \nProf. Motamarri’s research contributions include advances in finite-element methods\, numerical analysis\, and large-scale scientific software development. He is one of the lead developers of DFT-FE\, an open-source\, massively parallel finite-element code for density functional theory calculations. He received the ACM Gordon Bell Prize in 2023 and was a finalist for the ACM Gordon Bell Prize in 2019. \nInexact yet Accurate: Unlocking Quantum Modeling of Materials at Scale through Approximation-Tolerant Algorithms\nAbstract:  Modern computing architectures increasingly rely on iterative solvers that employ reduced-precision computation and communication-reduction techniques to lower time-to-solution and improve scalability. However\, eigensolvers in scientific simulations have struggled to exploit such approximations without compromising accuracy. We present an eigensolver R-ChFSI\, a residual-based reformulation of Chebyshev Filtered Subspace Iteration (ChFSI) provably tolerant to inexact matrix–vector products. By expressing the Chebyshev recurrence in terms of residuals rather than eigenvector estimates\, R-ChFSI naturally accommodates multiple sources of approximation\, including reduced-precision arithmetic (FP32 and TF32) in the filtering step\, lossy compression with compression ratios exceeding 4x for inter-process communication\, and approximate inverses for generalized eigenproblems\, while preserving eigensolver robustness. Large-scale experiments on GPU accelerators are conducted using finite-element discretized generalized eigenproblems arising in Kohn–Sham density functional theory for quantum modeling of materials. The results demonstrate that R-ChFSI achieves eigen-residual norms orders of magnitude smaller than standard ChFSI under comparable inexactness\, while delivering substantial performance gains. This work provides a practical pathway toward approximation-tolerant eigensolvers enabling accurate and scalable simulations on modern computing architectures. \n\nThe MICDE 2025-26 Seminar Series is open to all. \nGraduate Certificate in Computational Discovery and Engineering\, and MICDE fellows\, please use this form to record your attendance. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-me-seminar-phani-motamarri-iisc/
LOCATION:1311 EECS\, 1301 Beal Ave.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:College Of Engineering,Computational Science,Featured Events,Graduate Students,Mechanical Engineering,Micde,Micde Seminar,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2026/05/Phani-Motamarri.png
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X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=1311 EECS 1301 Beal Ave. Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=1301 Beal Ave.:geo:-83.713272,42.292322
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20260603T120000
DTEND;TZID=America/Detroit:20260603T130000
DTSTAMP:20260604T024940
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
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2026/05/4-29-Fang-Lee-Chen-4.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20260625T120000
DTEND;TZID=America/Detroit:20260625T130000
DTSTAMP:20260604T024940
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
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2026/05/4-29-Fang-Lee-Chen-3.png
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