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DTSTART;TZID=America/Detroit:20251118T114500
DTEND;TZID=America/Detroit:20251118T124500
DTSTAMP:20260604T081139
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
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2025/09/2025-11-18-Cooper-Ash-Micolta.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20251209T114500
DTEND;TZID=America/Detroit:20251209T124500
DTSTAMP:20260604T081139
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
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2025/09/2025-12-09-Fang-Ohiro-Griffin.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20260218T120000
DTEND;TZID=America/Detroit:20260218T130000
DTSTAMP:20260604T081139
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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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20260225T120000
DTEND;TZID=America/Detroit:20260225T130000
DTSTAMP:20260604T081139
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
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2026/01/2-25-Mathanker-Liu-Komaiha-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20260325T120000
DTEND;TZID=America/Detroit:20260325T130000
DTSTAMP:20260604T081139
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:20260604T081139
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
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2026/01/4-8-Wang-Karagulle.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20260414T080000
DTEND;TZID=America/Detroit:20260414T170000
DTSTAMP:20260604T081139
CREATED:20260116T194942Z
LAST-MODIFIED:20260127T161000Z
UID:10000853-1776153600-1776186000@micde.umich.edu
SUMMARY:2026 MICDE Predictive Science Conference
DESCRIPTION:This conference will center around predictive science. Fueled by advances in artificial intelligence and high-performance computing\, predictive science is poised to evolve dramatically over the next few years. Featuring presentations and panel discussions from leading voices across academia\, national laboratories\, industry\, and the government\, the conference will bring together researchers in high-performance computing\, verification and validation\, uncertainty quantification\, and artificial intelligence to discuss the state of the field of predictive science and its future outlook.
URL:https://micde.umich.edu/event/conference-symposium2026-micde-predictive-science-conference/
LOCATION:Palmer Commons – Forum Hall
CATEGORIES:Computation,Computational Science,Engineering,Faculty,Graduate and Professional Students,Graduate School,Graduate Students,High Performance Computing,In Person,Machine Learning,Micde,Science,Scientific Computing,symposium
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2026/01/For-web.png
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20260415T080000
DTEND;TZID=America/Detroit:20260415T170000
DTSTAMP:20260604T081139
CREATED:20260116T194943Z
LAST-MODIFIED:20260127T161037Z
UID:10000854-1776240000-1776272400@micde.umich.edu
SUMMARY:2026 MICDE Predictive Science Conference
DESCRIPTION:This conference will center around predictive science. Fueled by advances in artificial intelligence and high-performance computing\, predictive science is poised to evolve dramatically over the next few years. Featuring presentations and panel discussions from leading voices across academia\, national laboratories\, industry\, and the government\, the conference will bring together researchers in high-performance computing\, verification and validation\, uncertainty quantification\, and artificial intelligence to discuss the state of the field of predictive science and its future outlook.
URL:https://micde.umich.edu/event/conference-symposium2026-micde-predictive-science-conference-2/
LOCATION:Palmer Commons – Forum Hall
CATEGORIES:Computation,Computational Science,Engineering,Faculty,Graduate and Professional Students,Graduate School,Graduate Students,High Performance Computing,In Person,Machine Learning,Micde,Science,Scientific Computing,symposium
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2026/01/For-web.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20260422T120000
DTEND;TZID=America/Detroit:20260422T130000
DTSTAMP:20260604T081139
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:20260604T081139
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
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2026/01/4-29-Fang-Lee-Chen.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20260603T120000
DTEND;TZID=America/Detroit:20260603T130000
DTSTAMP:20260604T081139
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:20260604T081139
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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