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DTSTART;TZID=America/Detroit:20221116T153000
DTEND;TZID=America/Detroit:20221116T163000
DTSTAMP:20230713T163322Z
CREATED:20220825T193358Z
LAST-MODIFIED:20230713T163322Z
UID:10000579-1668612600-1668616200@micde.umich.edu
SUMMARY:MICDE Seminar: Miguel Bessa Associate Professor of Engineering\, Brown University
DESCRIPTION:Miguel Bessa is an Associate Professor in the School of Engineering at Brown University. His research interests include computational mechanics and materials science\, development of numerical methods\, machine learning and optimization\, multi-scale modeling of materials and structures. Miguel Bessa and his research group envision a new era for the design of materials and structures using artificial intelligence. Miguel received a PhD in Mechanical Engineering from Northwestern University in 2016 as a Fulbright scholar. After a short postdoctoral position at Caltech (2017) and a quick leap from Assistant to Associate Professor (2021) at Delft University of Technology\, he joined the Solid Mechanics Group at Brown University in the Summer of 2022. \nCOOPERATIVE DATA-DRIVEN MODELING \nThe human brain is capable of learning tasks mostly without forgetting. However\, deep neural networks suffer from catastrophic forgetting when learning tasks one after the other. We address this challenge considering a class-incremental learning scenario where the network sees test data without knowing its origin. We show the best results to date for the ImageNet dataset\, outperforming by more than 20% the state of the art. The proposed method is also applied to learn material laws\, illustrating its versatility. This strategy is believed to open new avenues for cooperation among different researchers and practitioners. \n  \n\nThe MICDE Fall 2022 Seminar Series is open to all. \nThis seminar is hosted by the Michigan Institute for Computational Discovery & Engineering (MICDE). Prof. Bessa will be hosted by Prof. Krishna Garikipati\, Professor of Mechanical Engineering and Mathematics and Director of MICDE. \nThis is an in-person event\, Zoom link will only be provided upon request. \nGraduate Certificate in Computational Discovery and Engineering\, and MICDE fellows\, please use this form to record your attendance. \nQuestions? Email MICDE-events@umich.edu \nWATCH THE RECORDING HERE.
URL:https://micde.umich.edu/event/micde-seminar-miguel-bessa-associate-professor-of-engineering-brown-university/
LOCATION:1303 EECS\, 1301 Beal Ave\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20221117T160000
DTEND;TZID=America/Detroit:20221117T163000
DTSTAMP:20230809T191957Z
CREATED:20211021T140003Z
LAST-MODIFIED:20230809T191957Z
UID:10000548-1668700800-1668702600@micde.umich.edu
SUMMARY:PhD Seminar: Khoi Dang
DESCRIPTION:The Ph.D. in Scientific Computing program is intended for students who will make extensive use of large-scale computation\, computational methods\, or algorithms for advanced computer architectures in their doctoral studies. This seminar series showcases the breadth of research covered by the program.  \nFeatured Speaker:\nKhoi Dang\, PhD Candidate\, Chemistry and Scientific Computing\nKhoi is a 5th year graduate student in the Chemistry Department currently developing electronic structure theory methods in the Zimmerman Group. \nParallel Heat-bath Configuration Interaction\nThe heat-bath configuration interaction (HBCI) method is a deterministic wave function method that approaches the full CI limit at greatly reduced cost. HBCI consists of two parts: the generation of a variational wave function\, followed by a perturbative correction. This work introduces a parallel implementation that is highly scalable and overcomes the memory bottleneck of perturbation theory. The implementation demonstrates 83% parallel efficiency for the perturbative step on 32 nodes. \n\n  \nThis event is part of MICDE’s seminar series featuring Ph.D. students in the Scientific Computing program. This series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nQuestions? Email MICDE-events@umich.edu \n 
URL:https://micde.umich.edu/event/phd-seminar-khoi-dang/
LOCATION:Weiser Hall\, 6th Floor\, 619\, 500 Church Street\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE PhD Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/02/2022-Fall-Dang.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20221201T160000
DTEND;TZID=America/Detroit:20221201T170000
DTSTAMP:20260522T141801Z
CREATED:20211021T140003Z
LAST-MODIFIED:20260522T141801Z
UID:10000549-1669910400-1669914000@micde.umich.edu
SUMMARY:PhD Seminar: Meichen Liu
DESCRIPTION:The Ph.D. in Scientific Computing program is intended for students who will make extensive use of large-scale computation\, computational methods\, or algorithms for advanced computer architectures in their doctoral studies. This seminar series showcases the breadth of research covered by the program.  \nFeatured Speakers:\nMeichen Liu\, PhD Candidate\, Earth and Environmental Science and Scientific Computing\nShe works with Professor Jeroen Ritsema in the department of Earth and Environmental Sciences. Her research involves characterizing earthquake sources as well as imaging structures in deep Earth. \nInfluence of shear wave velocity heterogeneity on SH-wave reverberation imaging of the mantle transition zone\nWe use the top-side shear wave reflection Ssds as a probe for mapping the depths of the mantle transition zone (MTZ) beneath the contiguous US. Using a common-reflection point (CRP) mapping approach\, we observe that the MTZ are about 40–50 km deeper beneath the western United States than the central-eastern United States if based on the 1-D Earth wave velocity model (Preliminary Reference Earth Model). However\, the east-to-west deepening of the MTZ disappears in the CRP image if we account for 3-D shear wave velocity variations in the mantle according to global tomography. In addition\, from spectral-element method synthetics\, we find that ray theory overpredicts the traveltime delays of the reverberations. Undulations of the MTZ are underestimated when their wavelengths are smaller than the Fresnel zones of the wave reverberations in the MTZ. Therefore\, modelling of layering in the upper mantle must be based on 3-D reference structures and accurate calculations of reverberation traveltimes. \n\n  \nThis event is part of MICDE’s seminar series featuring Ph.D. students in the Scientific Computing program. This series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nQuestions? Email MICDE-events@umich.edu \n 
URL:https://micde.umich.edu/event/phd-seminar-meichen-liu/
LOCATION:Weiser Hall\, 6th Floor\, 619\, 500 Church Street\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE PhD Seminar Series,Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20230112T160000
DTEND;TZID=America/Detroit:20230112T163000
DTSTAMP:20230809T191524Z
CREATED:20211021T140003Z
LAST-MODIFIED:20230809T191524Z
UID:10000550-1673539200-1673541000@micde.umich.edu
SUMMARY:PhD Seminar: Ismael Mendoza
DESCRIPTION:The Ph.D. in Scientific Computing program is intended for students who will make extensive use of large-scale computation\, computational methods\, or algorithms for advanced computer architectures in their doctoral studies. This seminar series showcases the breadth of research covered by the program.  \nFeatured Speaker:\nIsmael Mendoza\, PhD Candidate\, Physics and Scientific Computing\nIsmael is a 4th year Physics PhD student working in the area of cosmology. His research focuses on developing novel statistical and machine learning methods to analyze astronomical images from state-of-the-art telescopes. \nGitHub \nMachine Learning in Cosmology\nIn the upcoming decades\, we will have the opportunity to solve some of the biggest questions about our universe by taking advantage of the huge amounts of data produced by upcoming state-of-the-art cosmological experiments. In order to harness the full statistical power of this data\, we will need to develop scalable and accurate algorithms that can extract its maximal information. Recent advances in Machine Learning have demonstrated its ability to overcome the computational bottlenecks of traditional statistical techniques and even achieve better performance when analyzing cosmology data. In this talk\, I will give a brief overview of the open problems in cosmology\, motivate how Machine Learning (ML) could help us answer these by enabling novel analyses of upcoming cosmological surveys\, and give a specific application of ML enabling probabilistic detection and measurement of galaxy images. \n\n  \nThis event is part of MICDE’s seminar series featuring Ph.D. students in the Scientific Computing program. This series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nQuestions? Email MICDE-events@umich.edu \n 
URL:https://micde.umich.edu/event/phd-seminar-ismael-mendoza-2/
LOCATION:Weiser Hall\, 6th Floor\, 619\, 500 Church Street\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE PhD Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/02/Mendoza.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20230117T140000
DTEND;TZID=America/Detroit:20230117T150000
DTSTAMP:20230714T152222Z
CREATED:20221222T184418Z
LAST-MODIFIED:20230714T152222Z
UID:10000590-1673964000-1673967600@micde.umich.edu
SUMMARY:MICDE Seminar: Mark Vogelsberger Associate Professor of Physics\, Massachusetts Institute of Technology
DESCRIPTION:WATCH THE RECORDING HERE \nProfessor Vogelsberger grew up in Germany\, and received his undergraduate degree in physics from the University of Mainz and his Ph.D from the University of Munich and the Max Planck Institute for Astrophysics in 2010\, advised by Prof. Simon D.M. White. In 2009 he won the Rudolf Kippenhahn Prize for his thesis work. He was an ITC postdoctoral fellow at the Harvard-Smithsonian Center for Astrophysics from 2009-2012\, and a Hubble fellow from 2012-2013. In 2014\, Dr. Vogelsberger joined the MIT physics faculty as Assistant Professor. In 2016 he won an Alfred P. Sloan Fellowship in Physics. Professor Vogelsberger was promoted to Associate Professor in 2018. Professor Vogelsberger is a theoretical astrophysicist whose research interests broadly cover structure and galaxy formation\, dark matter physics and large-scale hydrodynamical simulations. He makes extensive use of numerical simulations using state-of-the-art high-performance supercomputers around the world. \n  \nSIMULATING EARLY STRUCTURE AND GALAXY FORMATION – THE THESAN PROJECT \nCosmological simulations of galaxy formation have evolved significantly over the last decade. In my talk I will describe recent efforts to model the\nlarge-scale distribution of galaxies with cosmological hydrodynamical simulations. The focus of the talk will be a discussion of our new simulation\ncampaign\, the THESAN project\, to study the epoch of re-ionization and the early Universe. \n  \n\nThe MICDE Winter 2023 Seminar Series is open to all. University of Michigan faculty and students interested in cosmology are encouraged to attend. \nThis seminar is hosted by the Michigan Institute for Computational Discovery & Engineering (MICDE). Prof. Vogelsberger will be hosted by Prof. Monica Valluri\, Research Professor of Astronomy. \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/mark-vogelsberger-associate-professor-of-physics-massachusetts-institute-of-technology-2/
LOCATION:MI
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2022/12/Mark-Vogelsberger.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20230123T150000
DTEND;TZID=America/Detroit:20230123T160000
DTSTAMP:20230810T200557Z
CREATED:20221222T184418Z
LAST-MODIFIED:20230810T200557Z
UID:10000589-1674486000-1674489600@micde.umich.edu
SUMMARY:MICDE Seminar: Albert Berahas Assistant Professor of Industrial and Operations Engineering at the University of Michigan
DESCRIPTION:Albert S. Berahas is an Assistant Professor in the Industrial and Operations Engineering department at the University of Michigan. Before joining the University of Michigan\, he was a Postdoctoral Research Fellow in the Industrial and Systems Engineering department at Lehigh University working with Professors Katya Scheinberg\, Frank Curtis and Martin Takáč. Prior to that appointment\, he was a Postdoctoral Research Fellow in the Industrial Engineering and Management Sciences department at Northwestern University working with Professor Jorge Nocedal. Berahas completed his PhD studies in the Engineering Sciences and Applied Mathematics (ESAM) department at Northwestern University in 2018\, advised by Professor Jorge Nocedal. He received his undergraduate degree in Operations Research and Industrial Engineering (ORIE) from Cornell University in 2009\, and in 2012 obtained an MS degree in Applied Mathematics from Northwestern University. Berahas’ research broadly focuses on designing\, developing and analyzing algorithms for solving large scale nonlinear optimization problems. Specifically\, he is interested in and has explored several sub-fields of nonlinear optimization such as: (i) general nonlinear optimization algorithms\, (ii) optimization algorithms for machine learning\, (iii) constrained optimization\, (iv) stochastic optimization\, (v) derivative-free optimization\, and (vi) distributed optimization. \n  \nALGORITHMS FOR DETERMINISTICALLY CONSTRAINED STOCHASTIC OPTIMIZATION \nStochastic gradient and related methods for solving stochastic optimization problems have been studied extensively in recent years. It has been shown that such algorithms and much of their convergence and complexity guarantees extend in straightforward ways when one considers problems involving simple constraints\, such as when one can perform projections onto the feasible region of the problem. However\, settings with general nonlinear constraints have received less attention\, and many of the approaches that have been proposed for solving such problems resort to using penalty or (augmented) Lagrangian methods\, which are often not the most effective strategies. In this work\, we propose and analyze stochastic optimization algorithms for deterministically constrained problems based on the sequential quadratic optimization (commonly known as SQP) methodology. We discuss the rationale behind our proposed techniques\, convergence in expectation and complexity guarantees for our algorithms\, and the results of preliminary numerical experiments that we have performed. This is joint work with Raghu Bollapragada\, Frank E. Curtis\, Michael O’Neill\, Daniel P. Robinson\, Jiahao Shi and Baoyu Zhou. \n  \n\nThe MICDE Winter 2023 Seminar Series is open to all. \nThis seminar is hosted by the Michigan Institute for Computational Discovery & Engineering (MICDE). Prof. Berahas will be hosted by Prof. Siqian Shen\, Associate Professor of Industrial and Operations Engineering and Associate Professor of Civil and Environmental Engineering. \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/albert-berahas-assistant-professor-of-industrial-and-operations-engineering-university-of-michigan/
LOCATION:Johnson Rooms\, Lurie Engineering Center\, 3rd Floor LEC 3213ABC\, 1221 Beal Ave.\, Ann Arbor\, MI\, United States
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2022/12/Albert-Berahas.png
GEO:42.2914823;-83.7138452
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20230126T160000
DTEND;TZID=America/Detroit:20230126T163000
DTSTAMP:20230809T191357Z
CREATED:20230104T090003Z
LAST-MODIFIED:20230809T191357Z
UID:10000588-1674748800-1674750600@micde.umich.edu
SUMMARY:PhD Seminar: Alex Hrabski
DESCRIPTION:The Ph.D. in Scientific Computing program is intended for students who will make extensive use of large-scale computation\, computational methods\, or algorithms for advanced computer architectures in their doctoral studies. This seminar series showcases the breadth of research covered by the program.  \nFeatured Speaker:\nAlex Hrabski\, PhD Candidate\, Naval Architecture & Marine Engineering and Scientific Computing\nAlex is a PhD candidate in the department of Naval Architecture and Marine Engineering\, working in Yulin Pan’s Flow Physics and Engineering Lab to study nonlinear waves. His research seeks to leverage modern computational capabilities to explore wave turbulence theory and the physics that it seeks to describe. \nInvestigations of Wave Turbulence in Bounded Domains\nNonlinear wave systems are ubiquitous in nature\, and when many incoherent dispersive waves interact\, there is the potential for wave turbulence. Just as in hydrodynamic turbulence (HDT)\, systems in wave turbulence exhibit inter-scale energy cascades\, power-law inertial-range spectra\, and even intermittency. Unlike in HDT\, however\, a natural analytical closure for field statistics has been developed: spectral evolution in wave turbulence can be expressed as a Boltzmann-like kinetic equation. In this talk\, we will numerically probe the interplay of nonlinear strength and domain size (critical quantities to the analytical closure) in determining the behaviors of wave turbulence in a model system. Our numerical experiments demonstrate that (a) domain aspect ratio plays a key role in spectral evolution when nonlinearity is weak\, (b) that near-resonant interactions are important for the observation of kinetic behavior\, and (c) evaluations of the energy cascade can be used to investigate the wave turbulence closure. \n\n  \nThis event is part of MICDE’s seminar series featuring Ph.D. students in the Scientific Computing program. This series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nQuestions? Email MICDE-events@umich.edu \n 
URL:https://micde.umich.edu/event/phd-seminar-alex-hrabski/
LOCATION:Weiser Hall\, 6th Floor\, 619\, 500 Church Street\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE PhD Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/02/2023-Winter-Hrabski.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20230126T163000
DTEND;TZID=America/Detroit:20230126T170000
DTSTAMP:20230809T191218Z
CREATED:20230104T090003Z
LAST-MODIFIED:20230809T191218Z
UID:10000595-1674750600-1674752400@micde.umich.edu
SUMMARY:PhD Seminar: Gurmeet Singh
DESCRIPTION:The Ph.D. in Scientific Computing program is intended for students who will make extensive use of large-scale computation\, computational methods\, or algorithms for advanced computer architectures in their doctoral studies. This seminar series showcases the breadth of research covered by the program.  \nFeatured Speaker:\nGurmeet Singh\, PhD Candidate\, Aerospace Engineering and Scientific Computing\nGurmeet is a Ph.D. candidate in the Department of Aerospace Engineering. His research interests lie in the field of computational solid mechanics focusing on constitutive behavior of materials. He works in Prof. Veera Sundararaghavan’s research group\, and his PhD dissertation focuses on the multiscale modeling of vitrimers and semi-crystalline polymers. \nUnderstanding thermomechanical behavior of vitrimers using molecular dynamics simulations\nVitrimers are a special class of polymers that undergo dynamic cross-linking under thermal stimuli. Their ability to exchange covalent bonds can be harnessed to mitigate damage in a composite or to achieve recyclable composites. This work addresses the primary challenge of modeling dynamic cross-linking reactions in vitrimers during thermomechanical loading. Dynamic bond exchange reaction probability change during heating and its effect on dilatometric and mechanical response are simulated in large scale molecular dynamics (MD) simulations. Healing of damage under thermal cycling is computed with mechanical properties predicted before and after self–healing. \nSubsequently\, the model is used to simulate the creep response of the vitrimer. The results show that the vitrimers demonstrate a secondary creep response on contrary to pure epoxy. The MD simulations are able to probe the interplay between chemical reactions and the loading that results in the healing of the vitrimer under creep. The important feature that explains the difference between epoxies and vitrimers is the orientation of the crosslink bonds with respect to the loading direction. Furthermore\, it is found that the free volume that arises from tensile loads is reduced in vitrimers through dynamic bond rearrangement. The bond orientation\, however\, is preferentially chosen to be normal to the loading axis which ends up decreasing the stiffness along the loading axis\, leading to higher strain as compared to epoxies. Over longer timescales\, the increased strain leads to faster damage localization in tertiary creep where the largest void grows to a critical volume beyond which healing is no longer possible. Thus\, chemistry changes or additives that can prevent the initial realignment of dynamic bonds can be an effective strategy to mitigate creep in vitrimers. \n\n  \nThis event is part of MICDE’s seminar series featuring Ph.D. students in the Scientific Computing program. This series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nQuestions? Email MICDE-events@umich.edu \n 
URL:https://micde.umich.edu/event/phd-seminar-gurmeet-singh-2/
LOCATION:Weiser Hall\, 6th Floor\, 619\, 500 Church Street\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE PhD Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/02/2023-Winter-Singh.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20230216T120000
DTEND;TZID=America/Detroit:20230216T130000
DTSTAMP:20230714T152013Z
CREATED:20230127T161137Z
LAST-MODIFIED:20230714T152013Z
UID:10000598-1676548800-1676552400@micde.umich.edu
SUMMARY:MICDE Seminar: Mark Pauly Professor of Computer Science\, École Polytechnique Fédérale de Lausanne
DESCRIPTION:WATCH THE RECORDING HERE. \nMark Pauly is a full professor at EPFL\, where he directs the Geometric Computing Laboratory (GCM). Prior to joining EPFL\, he was assistant professor at ETH Zurich\, postdoctoral scholar at Stanford University\, and doctoral student at ETH Zurich. He received the ETH medal for outstanding dissertation in 2003\, was awarded the Eurographics Young Researcher Award in 2006\, an ERC Starting Grant in 2010\, and the Eurographics Outstanding Technical Contributions Award in 2016. He is the co-founder of two EPFL spin-offs\, Faceshift AG and Rayform SA. \n  \nCOMPUTATIONAL INVERSE DESIGN OF DEPLOYABLE STRUCTURES \nResearch at the EPFL Geometric Computing Laboratory (GCM) aims at empowering creators. We develop efficient simulation and optimization algorithms to build computational design methodologies for advanced material systems and digital fabrication technology. Mathematical reasoning\, geometric abstractions\, and powerful numerical methods are key ingredients in our work.\nIn this talk I will show how these tools can be used to solve challenging inverse problems for deployable structures that can transition between multiple geometric states. Several design studies will highlight how the interplay of geometry\, computation\, and digital fabrication technologies facilitates the discovery of new material systems with superior functional performance. Such systems offer a wide variety of potential applications\, for example in industrial and consumer products\, soft robotics\, medical devices\, or architecture. \n\n  \nThe MICDE Winter 2023 Seminar Series is open to all. University of Michigan faculty and students interested in computationally designed advanced material systems and digital fabrication technology are encouraged to attend. \nThis seminar is hosted by the Michigan Institute for Computational Discovery & Engineering (MICDE). Prof. Pauly will be hosted by Prof. Evgueni Filipov\, Assistant Professor of Civil and Environmental Engineering. \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/mark-pauly-professor-at-the-school-of-computer-and-communication-sciences-ecole-polytechnique-federale-de-lausanne/
LOCATION:MI
CATEGORIES:Education,Featured Events,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/01/Mark-Pauly.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20230223T160000
DTEND;TZID=America/Detroit:20230223T163000
DTSTAMP:20230809T191036Z
CREATED:20230123T090003Z
LAST-MODIFIED:20230809T191036Z
UID:10000599-1677168000-1677169800@micde.umich.edu
SUMMARY:PhD Seminar: Pei-Hsun Huang
DESCRIPTION:The Ph.D. in Scientific Computing program is intended for students who will make extensive use of large-scale computation\, computational methods\, or algorithms for advanced computer architectures in their doctoral studies. This seminar series showcases the breadth of research covered by the program.  \nFeatured Speaker:\nPei-Hsun Huang\, PhD Candidate\, Nuclear Engineering & Radiological Sciences and Scientific Computing\nPei-Hsun is a PhD student in Nuclear Engineering & Radiological Sciences working with Professor Annalisa Manera in the Experimental and Computational Multiphase Flow Laboratory. His project involves high-temperature two-phase heat pipe technologies. \nSimulation for the Design of Sodium Heat Pipes Bundle Test Facility for the Application of Microreactors\nThe 20 MW Special Purpose Reactor (SPR) is a heat pipe cooled microreactor that designed for electricity production in remote locations where reliable power grids are not always available. The key to SPR is the alkali metal heat pipes\, which offer entirely passive operation capacity with high mobility. Prior to deployment\, safety analysis with postulated accident scenarios is required for the licensing of SPR. To this regard\, a sufficiently accurate model is crucial to predict the behavior of heat pipes\, and high-resolution data is needed for the safety analysis of SPR. However\, the current existing heat pipe models are either oversimplified or unpractical expensive in view of the difficulty of the simulation with the wick structure and two-phase flow in the heat pipe. Therefore\, high fidelity experimental data is required for model verification in the high temperature heat pipe bundle system. The Michigan Sodium Heat Pipe bundle test facility which serves as a scale-down test facility using ten sodium heat pipes with a triangular array\, was utilized to verify the model for the licensing of SPR. In the talk\, the feasibility analysis using Computer Aided Engineering and Computational Fluid Dynamics for the design of the test facility was addressed. \n\n  \nThis event is part of MICDE’s seminar series featuring Ph.D. students in the Scientific Computing program. This series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nQuestions? Email MICDE-events@umich.edu \n 
URL:https://micde.umich.edu/event/phd-seminar-pei-hsun-huang-2/
LOCATION:Rackham Building\, Earl Lewis Room\, 3rd Floor East\, 915 E. Washington St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE PhD Seminar Series,Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20230223T163000
DTEND;TZID=America/Detroit:20230223T170000
DTSTAMP:20230809T190922Z
CREATED:20230123T090003Z
LAST-MODIFIED:20230809T190922Z
UID:10000591-1677169800-1677171600@micde.umich.edu
SUMMARY:PhD Seminar: Shirlyn Wang
DESCRIPTION:The Ph.D. in Scientific Computing program is intended for students who will make extensive use of large-scale computation\, computational methods\, or algorithms for advanced computer architectures in their doctoral studies. This seminar series showcases the breadth of research covered by the program.  \nFeatured Speaker:\nShirlyn Wang\, PhD Candidate\, Applied & Interdisciplinary Mathematics and Scientific Computing\nShirlyn Wang is a Ph.D candidate in Applied and Interdisciplinary Mathematics. Her research interest is in mathematical oncology\, the study of cancer initiation\, progression\, and therapy through data-driven mathematical models and simulations.  \nModeling CTL-mediated Tumor Cell Death Mechanisms and the Activity of Immune Checkpoints in Immunotherapy\nImmunotherapy has dramatically transformed the cancer treatment landscape. Of the variety of types of immunotherapies available\, immune checkpoint inhibitors (ICIs)\, which block inhibitory signals from tumor cells and reinvigorate killing activities of immune cells\, have gained the spotlight. Although ICIs have shown promising results for some patients\, the low response rates in many cancers highlight the challenges of using immune checkpoint blockade as an effective treatment. Cytotoxic T lymphocytes (CTLs) execute their cell-killing function via two distinct mechanisms. The first process is fast-acting and perforin/granzyme-mediated\, and the second is a slower\, Fas ligand (FasL)-driven killing mechanism. There is also evidence suggesting that the preferred killing mechanism by CTLs depends on the antigenicity of tumor cells. To determine the key factors affecting responses to checkpoint blockade therapy\, we constructed an ordinary differential equation model describing in vivo tumor-immune dynamics in the presence of active or blocked PD-1/PDL1 immune checkpoint. Specifically\, we analyzed which aspects of the tumor-immune landscape affect the response to ICIs with endpoints of tumor size and composition in the short and long term. By generating a virtual cohort with heterogeneous tumor and immune attributes\, we also simulated the therapeutic outcomes of immune checkpoint blockade in a largely diverse population. In this way\, we identified key tumor and immune characteristics that are associated with tumor elimination\, dormancy and escape. This talk will also shed light on which fraction of a population potentially responds well to ICIs and ways to enhance therapeutic outcomes with combination therapy. \n\n  \nThis event is part of MICDE’s seminar series featuring Ph.D. students in the Scientific Computing program. This series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nQuestions? Email MICDE-events@umich.edu \n 
URL:https://micde.umich.edu/event/phd-seminar-shirlyn-wang/
LOCATION:Rackham Building\, Earl Lewis Room\, 3rd Floor East\, 915 E. Washington St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE PhD Seminar Series,Seminar
GEO:42.2807892;-83.7381556
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Rackham Building Earl Lewis Room 3rd Floor East 915 E. Washington St. Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=915 E. Washington St.:geo:-83.7381556,42.2807892
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20230302T153000
DTEND;TZID=America/Detroit:20230302T163000
DTSTAMP:20230905T171445Z
CREATED:20230905T171445Z
LAST-MODIFIED:20230905T171445Z
UID:10000017-1677771000-1677774600@micde.umich.edu
SUMMARY:MICDE Seminar: Daniele Schiavazzi\, Associate Professor of Applied and Computational Mathematics and Statistics\, University of Notre Dame
DESCRIPTION:Daniele Schiavazzi is an Associate Professor in the Department of Applied and Computational Mathematics and Statistics at the University of Notre Dame. He graduated with honors and received a Ph.D. in Applied Mathematics from Universita’ degli Studi di Padova in Italy. He held postdoctoral appointments at the University of California\, San Diego and Stanford University. He is the recipient of a CAREER Award from the National Science Foundation\, a Young Faculty Award from DARPA and a Postdoctoral Fellowship from the American Heart Association. His research interests include uncertainty quantification\, cardiovascular simulation\, multi-resolution and multi-fidelity approximation\, model-based inference and inverse problems in medical imaging. \nTalk Title: NEW PARADIGMS FOR ENSEMBLE MODELING\, UNCERTAINTY QUANTIFICATION AND INFERENCE IN CARDIOVASCULAR SIMULATION \nAbstract: \nComputer simulations are increasingly used to complement clinical decision making in the diagnosis and treatment of cardiovascular disease. High-fidelity cardiovascular models are traditionally deterministic and solved using implicit time integration\, without directly accounting for uncertainty and variability in the underlying input processes\, for example boundary conditions\, material properties or segmented model anatomy. I will discuss an alternative simulation paradigm based on the explicit integration in time of an ensemble of model realizations\, running on multiple GPUs. Additionally\, I will present some results on the acceleration of traditional numerical solvers through data-driven methods based on deep neural networks\, focusing on synchronization-avoiding algorithms for distributed finite element solvers. I will finally discuss recently proposed approaches for multi-fidelity uncertainty propagation and variational inference\, combining high-fidelity cardiovascular models with their low-fidelity approximation or neural network surrogate. \n  \n\n  \nThe MICDE Fall 2022 Seminar Series is open to all. \nThis seminar is hosted by the Michigan Institute for Computational Discovery & Engineering (MICDE). Prof. Schiavazzi will be hosted by Prof. Alex Gorodetsky\, Assistant Professor of Aerospace Engineering. \nThis is an in-person event\, Zoom link will only be provided upon request. This seminar will not be recorded! \nGraduate Certificate in Computational Discovery and Engineering\, and MICDE fellows\, please use this form to record your attendance. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-daniele-schiavazzi-associate-professor-of-applied-and-computational-mathematics-and-statistics-university-of-notre-dame/
LOCATION:1014 H. H. Dow\, 2300 Hayward St\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20230309T160000
DTEND;TZID=America/Detroit:20230309T163000
DTSTAMP:20260417T164122Z
CREATED:20230209T090003Z
LAST-MODIFIED:20260417T164122Z
UID:10000596-1678377600-1678379400@micde.umich.edu
SUMMARY:PhD Seminar: Kashvi Srivastava
DESCRIPTION:The Ph.D. in Scientific Computing program is intended for students who will make extensive use of large-scale computation\, computational methods\, or algorithms for advanced computer architectures in their doctoral studies. This seminar series showcases the breadth of research covered by the program.  \nFeatured Speaker:\nKashvi Srivastava\, PhD Candidate\, Applied and Interdisciplinary Mathematics and Scientific Computing\nKashvi Srivastava is a PhD candidate in Applied and Interdisciplinary Mathematics. Her research interests lie in the applications of nonlinear dynamics in chemical kinetics. She works on analytical and computational modeling of chemical reactions using tools from perturbation theory and bifurcation theory. \nDeterministic and Stochastic Modeling of Dynamical Systems in Chemical Kinetics\nChemical reactions are ubiquitous in nature in the form of biological and physical processes. We use nonlinear ordinary differential equations to mathematically model these processes in the deterministic regime. If a given process occurs at disparate time-scales\, we can further reduce the number of equations to obtain a quasi-steady-state approximation of the system. In this talk\, we consider a significant mechanism in chemical kinetics called the Michaelis–Menten reaction and its different quasi-steady-state reductions. We focus on the challenges faced in applying classical reduction theory on the system and the conditions under which its reductions are valid in the stochastic regime. We make use of a stochastic simulation algorithm called the Gillespie algorithm to demonstrate the accuracy of the reduced systems and to disprove a commonly-accepted qualifier for the validity of the stochastic approximation.  \n\n  \nThis event is part of MICDE’s seminar series featuring Ph.D. students in the Scientific Computing program. This series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nQuestions? Email MICDE-events@umich.edu \n 
URL:https://micde.umich.edu/event/phd-seminar-kashvi-srivastava/
LOCATION:3530 Rackham\, 915 E. Washington St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE PhD Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/02/2023-Winter-Srivastava.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20230309T163000
DTEND;TZID=America/Detroit:20230309T170000
DTSTAMP:20230809T184654Z
CREATED:20230209T090003Z
LAST-MODIFIED:20230809T184654Z
UID:10000600-1678379400-1678381200@micde.umich.edu
SUMMARY:PhD Seminar: Jiahao Shi
DESCRIPTION:The Ph.D. in Scientific Computing program is intended for students who will make extensive use of large-scale computation\, computational methods\, or algorithms for advanced computer architectures in their doctoral studies. This seminar series showcases the breadth of research covered by the program.  \nFeatured Speaker:\nJiahao Shi\, PhD Candidate\, Industrial and Operations Engineering and Scientific Computing\nHe is from industrial and Operations Engineering department and is working on constrained stochastic optimization. \nAccelerating Stochastic Sequential Quadratic Programming for Equality Constrained Optimization using Predictive Variance Reduction\nWe propose a stochastic method for solving equality constrained optimization problems that utilizes predictive variance reduction. Specifically\, we develop a method based on the sequential quadratic programming paradigm that employs variance reduction in the gradient approximations. Under reasonable assumptions\, we prove that a measure of first-order stationarity evaluated at the iterates generated by our proposed algorithm converges to zero in expectation from arbitrary starting points\, for both constant and adaptive step size strategies. Finally\, we demonstrate the practical performance of our proposed algorithm on constrained binary classification problems that arise in machine learning. \n\n  \nThis event is part of MICDE’s seminar series featuring Ph.D. students in the Scientific Computing program. This series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nQuestions? Email MICDE-events@umich.edu \n 
URL:https://micde.umich.edu/event/phd-seminar-jiahao-shi/
LOCATION:Venue TBA\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE PhD Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/02/2023-Winter-Shi.png
GEO:42.3053253;-83.6694169
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20230316T160000
DTEND;TZID=America/Detroit:20230316T163000
DTSTAMP:20230809T182009Z
CREATED:20230123T090003Z
LAST-MODIFIED:20230809T182009Z
UID:10000597-1678982400-1678984200@micde.umich.edu
SUMMARY:PhD Seminar: Xingmin Wang
DESCRIPTION:The Ph.D. in Scientific Computing program is intended for students who will make extensive use of large-scale computation\, computational methods\, or algorithms for advanced computer architectures in their doctoral studies. This seminar series showcases the breadth of research covered by the program.  \nFeatured Speaker:\nXingmin Wang\, PhD Candidate\, Civil and Environmental Engineering and Scientific Computing\nXingmin Wang is currently a Ph.D. candidate in the Department of Civil and Environmental Engineering at the University of Michigan\, Ann Arbor\, advised by Professor Henry Liu. He obtained his bachelor’s degree in the school of vehicle and mobility from Tsinghua University\, in 2018. His research interests include traffic state estimation and traffic network optimization with connected and automated vehicles.  \nTraffic signal optimization with connected vehicle trajectories\nTraffic signal retiming is one of the most cost-effective methods for reducing congestion and energy consumption in urban areas based on the existing road infrastructure. However\, high installation and maintenance costs of vehicle detectors have prevented the widespread implementation of adaptive traffic control systems (ATSC). Therefore\, most intersections are still controlled by fixed-time traffic signals which are not updated regularly due to the lack of traffic monitoring capabilities. In the past few years\, vehicle trajectory data has become increasingly available and offers many advantages over detectors and other infrastructure-based sensors for traffic monitoring; but using such data for automatic traffic signal diagnosis and optimization at scalable implementable levels is relatively unexplored. To fill this gap\, this work proposes Optimizing Traffic Signals as a Service (OSaaS)\, an integrated traffic signal re-timing system that uses vehicle trajectories as the main input. OSaaS addresses many of the current challenges relating to signal retiming with trajectory data such as incomplete observation due to limited penetration rates. The system builds a queueing model that reconstructs the overall average traffic state\, calibrated from performance measurements directly obtained from vehicle trajectories. The calibrated queueing model then predicts and evaluates network performance under different traffic signal parameters to provide diagnostics and direct traffic signal retiming guidance. In April 2022\, a citywide field test of OSaaS was conducted in Birmingham\, Michigan\, with 34 signalized intersections. This resulted in decreases in both the delay and number of stops by up to 20% and 30%\, respectively. OSaaS provides a more scalable\, sustainable\, resilient\, and efficient solution to traffic signal retiming without requiring any additional infrastructure through the exclusive utilization of currently available trajectory data. As a result\, it presents the possibility of upgrading all existing fixed-time traffic signals to dynamic systems with periodical parameter updates\, something that is not currently possible without significant investments in infrastructure-based traffic flow sensors. \n\n  \nThis event is part of MICDE’s seminar series featuring Ph.D. students in the Scientific Computing program. This series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nQuestions? Email MICDE-events@umich.edu \n 
URL:https://micde.umich.edu/event/phd-seminar-xingmin-wang/
LOCATION:Venue TBA\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE PhD Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/02/2023-Winter-Wang-1.png
GEO:42.3053253;-83.6694169
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20230316T163000
DTEND;TZID=America/Detroit:20230316T170000
DTSTAMP:20230809T181913Z
CREATED:20230123T090003Z
LAST-MODIFIED:20230809T181913Z
UID:10000601-1678984200-1678986000@micde.umich.edu
SUMMARY:PhD Seminar: Xintao Yan
DESCRIPTION:The Ph.D. in Scientific Computing program is intended for students who will make extensive use of large-scale computation\, computational methods\, or algorithms for advanced computer architectures in their doctoral studies. This seminar series showcases the breadth of research covered by the program.  \nFeatured Speaker:\nXintao Yan\, PhD Candidate\, Civil and Environmental Engineering and Scientific Computing\nXintao Yan is currently a Ph.D. candidate in the Department of Civil and Environmental Engineering at the University of Michigan\, Ann Arbor\, advised by Professor Henry Liu. He received his bachelor’s degree from the Department of Automotive Engineering at Tsinghua University\, China in 2018. His research interests are mainly about the safety of connected and automated vehicles\, including naturalistic driving behavior modeling and automated driving system evaluation. \nSimulating Naturalistic Driving Environment for Autonomous Vehicles\nSimulation provides a controllable\, efficient\, and low-cost venue for both developing and testing autonomous vehicles (AV). But for simulation to be an effective tool\, statistical realism of the simulated driving environment is a must. In this talk\, we will introduce methods to simulate naturalistic driving environment for AV testing purposes. \n\n  \nThis event is part of MICDE’s seminar series featuring Ph.D. students in the Scientific Computing program. This series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nQuestions? Email MICDE-events@umich.edu \n 
URL:https://micde.umich.edu/event/phd-seminar-xintao-yan/
LOCATION:Venue TBA\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE PhD Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/02/2023-Winter-Yan.png
GEO:42.3053253;-83.6694169
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20230412T160000
DTEND;TZID=America/Detroit:20230412T170000
DTSTAMP:20260522T152717Z
CREATED:20230714T151826Z
LAST-MODIFIED:20260522T152717Z
UID:10000602-1681315200-1681318800@micde.umich.edu
SUMMARY:MICDE Seminar: Paul Kent\, PhD\, Distinguished Research Scientist at Oak Ridge National Laboratory
DESCRIPTION:Dr Kent`s research is focusing on predicting and explaining the properties of materials using computer simulation. Over the last two decades\, advances in simulation techniques coupled with increasing computer power have led to several methods that are able to predict physical properties of real materials to a useful accuracy. Moreover\, these methods use little or no experimental data\, making them especially valuable for the study of new materials and devices. Dr. Kent specializes in the application and development of these so-called “first principles” methods. \nHis research interests are broadly focused on atomistic materials simulation. His ongoing research projects include: \n\nQuantum Monte Carlo for real materials\nLarge length and timescale quantum molecular dynamics calculations\nCharacterization\, optimization\, and design of nanoscale systems with desired properties\nCombined density functional and many-body calculations of correlated electron systems such as the copper-oxide superconductors\nReactive classical molecular dynamics\nSimulation methods for exploitation of Exascale supercomputers and emergent architectures\n\n\n\n\n\n\nDr. Kent is the director of  the Center for Predictive Simulation of Functional Materials. He also leads the  development of the QMCPACK application for exascale computing as part of the Exascale Computing Project. QMCPACK is a high-performance Quantum Monte Carlo code for computing the electronic structure of atoms\, molecules and solids\, including metals. QMCPACK is open source and available on GitHub. \nDr Kent is a member of the Nanotheory Institute at the Center for Nanophase Materials Sciences (CNMS) and the Computational Chemical and Materials Science group in the Computational Science and Engineering Division. He spent three years at NREL with Alex Zunger after completing his PhD with Richard Needs at the University of Cambridge. For several years he worked with Mark Jarrell at the University of Cincinnati on high-temperature cuprate superconductors. In 2009 he transitioned from JICS/UT Knoxville to ORNL. \nAwards: \n\nORNL Director’s Award for Outstanding Individual Accomplishment in Science and Technology\, 2020.\nAPS Fellowship\, nominated by the Division of Computational Physics\, 2017.\nACM Gordon Bell Prize\, 2008.\n\nProfessional Service: \n\nGrant reviewer for US DOE and NSF\nReviewer for APS\, ACS\, IOP\, Elsevier\, Springer Nature etc.\n\nAccurate Quantum Materials  Predictions on the Largest Supercomputers\nAdvances in the field of computational materials science have helped to predict\, understand\, and optimize the properties of many classes of materials. These include new battery electrodes\, catalysts\, and arguably even higher-temperature superconductors. However\, we still lack a widely usable method where all the key uncertainties and approximations in the predictions can be assessed and systematically reduced. This is critical where the approximations in established methods fail\, such as in quantum materials\, or simply where greater accuracy is desired. In this talk I will first describe our recent advances in Quantum Monte Carlo methods that promise to meet this challenge. Second\, I will describe the new algorithms and performance portable software design and development strategies we have adopted to run efficiently on the largest supercomputers powered by GPU accelerators from NVIDIA\, AMD and Intel. The lessons learned can be applied in any area of scientific software development. \n\nThe MICDE Winter 2023 Seminar Series is open to all. University of Michigan faculty and students interested in predicting and explaining the properties of materials using computer simulation are encouraged to attend. \nThis seminar is cohosted by the Michigan Institute for Computational Discovery & Engineering (MICDE) and the Department of Physics. Dr. Kent will be hosted by Dr. Emanuel Gull\, Associate Professor of Theoretical Condensed Matter Physics. \nThis is an in-person event. \nGraduate Certificate in Computational Discovery and Engineering\, and MICDE fellows\, please use this form to record your attendance. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-paul-kent-phd-distinguished-research-scientist-at-oak-ridge-national-laboratory/
LOCATION:411 West Hall (1085 S. University)\, 1085 S. University Ave\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Education,Featured Events,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/07/Paul-Kent.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20230926T123000
DTEND;TZID=America/Detroit:20230926T130000
DTSTAMP:20230921T195259Z
CREATED:20230913T145952Z
LAST-MODIFIED:20230921T195259Z
UID:10000631-1695731400-1695733200@micde.umich.edu
SUMMARY:MICDE Ph.D. Student Seminar: Haowei Sun
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public\, but we ask that you register to attend the seminar. If you have any questions\, please email micde-events@umich.edu. \nRegister to attend this seminar \nTera City: Accurate and Efficient AV Safety Performance Evaluation\nThis talk is aiming at mitigating current simulation-based AV safety performance evaluation approaches. Tera City is composed of naturalistic driving environment construction and intelligent testing environment construction\, which provided accuracy and efficiency\, respectively. \nHaowei Sun\, Ph.D. candidate in Civil and Environmental Engineering and Scientific Computing \nHaowei Sun is a Ph.D. candidate at Civil Engineering\, Next Generation Transportation System Program. His research focus is mainly on the safety validation and verification of autonomous vehicles. \nRegister to attend this seminar
URL:https://micde.umich.edu/event/phd-seminar-haowei-sun/
LOCATION:2022 South Thayer Building
CATEGORIES:Civil and Environmental Engineering,Computation,Computational Science,Engineering,Free,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,In Person,Interdisciplinary,Michigan Engineering,Phd Seminar,Prospective Graduate Students,Rackham,Science,Scientific Computing,Seminar,Talk
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/09/Haowei-Sun.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20231107T120000
DTEND;TZID=America/Detroit:20231107T130000
DTSTAMP:20231019T200916Z
CREATED:20230914T150100Z
LAST-MODIFIED:20231019T200916Z
UID:10000639-1699358400-1699362000@micde.umich.edu
SUMMARY:MICDE Ph.D. Student Seminars: Bernardo Pacini & Srinivasan Arunachalam
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public\, but we ask that you register to attend the seminar. If you have any questions\, please email micde-events@umich.edu. \nRegister to attend this seminar \nGradient-Based Multidisciplinary Design Optimization for Propeller Design\nUrban air mobility (UAM) vehicles have taken form as advanced rotorcraft with sets of wings\, rotors\, canards\, and other appendages. Noise generation is an important technical barrier that must be addressed to prevent these vehicles from causing excessive disturbance to the communities they are intended to service. To understand the noise these vehicles generate\, and to develop designs that can minimize disturbance\, there is a need for analysis and optimization tools specifically for the conceptual design and sizing phase of urban air mobility vehicle development. Such tools must be computationally efficient to allow for the repeated analyses needed for design optimization. This presentation will review the work being carried out at the University of Michigan\, coupling aerodynamic\, structural\, and aeroacoustic disciplines within the multidisciplinary gradient-based design optimization framework OpenMDAO. While aerostructural optimization has been performed previously\, coupling with aeroacoustics is challenging given the requirement for time accurate simulations and the associated computational cost of such analyses. By leveraging multiple model fidelities and utilizing efficient gradient calculation techniques\, such as the adjoint method and algorithmic differentiation\, these disciplines can be formulated into an optimization framework that can be applied to UAM vehicle designs. This presentation will review the work completed to date\, including preliminary results\, and expand on the future goals of the project\, working towards a broader optimization framework for rotorcraft vehicle design optimization. \nBernardo Pacini\, Ph.D. candidate in Mechanical Engineering and Scientific Computing \nBernardo Pacini is a Ph.D. Candidate at the University of Michigan focusing his research on aerodynamic\, structural\, and aeroacoustic modeling for multidisciplinary design optimization of urban air mobility vehicles. He is a member of the Multidisciplinary Design Optimization Laboratory led by Professor Joaquim R. R. A. Martins and of the Computational Aerosciences Laboratory led by Professor Karthik Duraisamy. Bernardo’s work to date is on developing an aero-structural-acoustic analysis framework that can be implemented within the multidisciplinary design optimization process for rotorcraft and urban air mobility vehicle design. \nRegister to attend this seminar \nValidation of a multivariate non-Gaussian\, non-stationary wind pressure simulation model for performance-based wind engineering\nWith a growing interest in probabilistic performance assessments of building systems subjected to wind loads\, there is a demand for accurately representing building-specific wind loads\, considering their non-Gaussian and non-stationary features. While typical wind tunnel data collected for a set of discrete wind directions provide a single realization of stationary pressures\, there is currently no experimentally validated model for the stochastic simulation of non-Gaussian and non-stationary wind pressures that can be calibrated to wind tunnel datasets. Such a model is essential for simulating building aerodynamics\, especially the stochastic\, path-dependent responses associated with time-varying wind speed and direction experienced by a building during hurricane wind events. This talk will review a recently developed theoretical formulation for generating these stochastic pressures. Through carefully designed tests conducted at the University of Florida wind tunnel facility\, the formulation was extensively validated with respect to its ability to capture trends over time\, occurrences of peaks\, and time-varying frequency content. \nSrinivasan Arunachalam\, Ph.D. candidate in Civil and Environmental Engineering and Scientific Computing \nSrinivasan Arunachalam is a PhD candidate in Civil and Environmental Engineering. His research interests lie in uncertainty quantification and understanding the inelastic behavior of wind-excited structures. He is excited about the algorithmic developments that enable efficient reliability assessments\, as well as the evolving insights into the physics of extreme responses and their implications for structural design. \nRegister to attend this seminar
URL:https://micde.umich.edu/event/phd-seminar-bernardo-pacini-srinivasan-arunachalam/
LOCATION:2022 South Thayer Building
CATEGORIES:Computation,Computational Modeling,Computational Science,Engineering,Free,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,In Person,Interdisciplinary,Michigan Engineering,Phd Seminar,Prospective Graduate Students,Rackham,Science,Scientific Computing,Seminar,Sessions,Talk
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/09/2023117-Bernardo-Pacini-and-SrinivasanArunachalam-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20231114T123000
DTEND;TZID=America/Detroit:20231114T130000
DTSTAMP:20231103T200940Z
CREATED:20230914T150100Z
LAST-MODIFIED:20231103T200940Z
UID:10000640-1699965000-1699966800@micde.umich.edu
SUMMARY:MICDE Ph.D. Student Seminars: Jamie Holber
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public\, but we ask that you register to attend the seminar. If you have any questions\, please email micde-events@umich.edu. \nActive Learning for Physics Informed Data Sampling and Construction of Free Energy Representations\nUsing automation technology to gather and disseminate information to the public is commonly viewed as a government-led effort to enhance oversight and address the principal-agent problem in bureaucracy. However\, focusing on the expansion of China’s automatic ambient air quality monitoring network in the last decade (2012-2022)\, I argue that technology is being utilized as a tool to emphasize optics but overlook the substantive problems. I illustrate the idea with multiple original georeferenced data sets on the automatic monitoring network\, pollution sources\, and satellite-derived vegetation density across time and space. I show that\, while the automation initiative has improved the data quality in some ways\, the undersupply of automatic monitoring stations\, over-represented clean locations\, and non-random missing pollution records continue to contribute to inaccurate air pollution information. As long as political incentives to manipulate information persist\, actors can mold technology that operates without human intervention to serve their own interests. \nJamie Holber\, Ph.D. candidate in Applied Physics and Scientific Computing \nJamie Holber is a PhD Candidate in Applied Physics and Scientific Computing working in the Computational Physics Group in the Mechanical Engineering Department. \nAdvisor: Krishna Garikipati \nRegister to attend this seminar
URL:https://micde.umich.edu/event/phd-seminar-jamie-holber/
LOCATION:2022 South Thayer Building
CATEGORIES:Computation,Computational Modeling,Computational Science,Engineering,Free,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,In Person,Interdisciplinary,Michigan Engineering,Phd Seminar,Prospective Graduate Students,Rackham,Science,Scientific Computing,Seminar,Sessions,Talk
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/09/20231114-Jamie-Holber.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20231128T120000
DTEND;TZID=America/Detroit:20231128T130000
DTSTAMP:20260522T152930Z
CREATED:20230914T150100Z
LAST-MODIFIED:20260522T152930Z
UID:10000641-1701172800-1701176400@micde.umich.edu
SUMMARY:MICDE Ph.D. Student Seminars 2023-2024: Guoer Liu
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public\, but we ask that you register to attend the seminar. If you have any questions\, please email micde-events@umich.edu. \nRegister to attend this seminar \nWhen Is Big Data Biased?\nUsing automation technology to gather and disseminate information to the public is commonly viewed as a government-led effort to enhance oversight and address the principal-agent problem in bureaucracy. However\, focusing on the expansion of China’s automatic ambient air quality monitoring network in the last decade (2012-2022)\, I argue that technology is being utilized as a tool to emphasize optics but overlook the substantive problems. I illustrate the idea with multiple original georeferenced data sets on the automatic monitoring network\, pollution sources\, and satellite-derived vegetation density across time and space. I show that\, while the automation initiative has improved the data quality in some ways\, the undersupply of automatic monitoring stations\, over-represented clean locations\, and non-random missing pollution records continue to contribute to inaccurate air pollution information. As long as political incentives to manipulate information persist\, actors can mold technology that operates without human intervention to serve their own interests. \nGuoer Liu\, Ph.D. candidate in Political Science and Scientific Computing\nGuoer Liu is a Ph.D. candidate in Political Science. Her dissertation project\, ‘‘From Oversight to Overlook’’ investigates how political determinants distort the technology infrastructure and create seemingly credible but inaccurate information to the public. \nAdvisors: Mary Gallagher\, Charles Shipan \nRegister to attend this seminar
URL:https://micde.umich.edu/event/phd-seminar-guoer-liu/
LOCATION:2022 South Thayer Building
CATEGORIES:Computation,Computational Modeling,Computational Science,Engineering,Free,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,In Person,Interdisciplinary,Michigan Engineering,Phd Seminar,Prospective Graduate Students,Rackham,Science,Scientific Computing,Seminar,Sessions,Talk
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20231205T120000
DTEND;TZID=America/Detroit:20231205T130000
DTSTAMP:20231204T192114Z
CREATED:20230926T191303Z
LAST-MODIFIED:20231204T192114Z
UID:10000654-1701777600-1701781200@micde.umich.edu
SUMMARY:MICDE Ph.D. Student Seminars 2023-2024: Jeffrey Hatch
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public\, but we ask that you register to attend the seminar. If you have any questions\, please email micde-events@umich.edu. \nComputational Methods in Chemistry\nAbstract coming soon… \nJeffrey Hatch\, Ph.D. candidate in Chemistry and Scientific Computing \nBio coming soon… \nRegister to attend this seminar
URL:https://micde.umich.edu/event/phd-seminar-jeffrey-hatch/
LOCATION:2022 South Thayer Building
CATEGORIES:Computation,Computational Modeling,Computational Science,Engineering,Free,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,In Person,Interdisciplinary,Michigan Engineering,Phd Seminar,Prospective Graduate Students,Rackham,Science,Scientific Computing,Seminar,Sessions,Talk
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20240305T120000
DTEND;TZID=America/Detroit:20240305T123000
DTSTAMP:20240223T215755Z
CREATED:20240220T232014Z
LAST-MODIFIED:20240223T215755Z
UID:10000673-1709640000-1709641800@micde.umich.edu
SUMMARY:MICDE Ph.D. Student Seminar: Lingfeng Luo
DESCRIPTION:Please register to attend \nLingfeng Luo will present: Gradient Boosting-Based Discrete Failure Time Model for Selecting Time-Varying Effects and Interactions as a part of the MICDE PhD Student Seminar Series. \nThe MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public\, but we ask that all attendees register in advance so that we can be prepared with lunch for all attendees. \nIf you have any questions\, please email micde-events@umich.edu. \nPlease register to attend
URL:https://micde.umich.edu/event/micde-ph-d-student-seminar-lingfeng-luo/
LOCATION:Duderstadt Center – 1180
CATEGORIES:Biostatistics,Phd Seminar,Scientific Computing,Seminar,Workshops
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20240312T120000
DTEND;TZID=America/Detroit:20240312T130000
DTSTAMP:20240220T232015Z
CREATED:20240220T232015Z
LAST-MODIFIED:20240220T232015Z
UID:10000674-1710244800-1710248400@micde.umich.edu
SUMMARY:Workshop / Seminar:MICDE Ph.D. Student Seminar: Hannah Van Wyk and Musawer Ahmad Saqif
DESCRIPTION:Hannah Van Wyk will present her talk: Using a hidden markov model to pinpoint the date of the primary case in a dengue outbreak in rural Ecuador.\nAn infectious disease outbreak investigation typically consists of retrospectively determining information regarding the outbreak such as the timing of the primary case (the first case of the outbreak\, whether detected or not) and transmission dynamics that occurred prior to the outbreak. However\, information on the primary case is often hard to obtain\, especially in scenarios where the disease has a high asymptomatic ratio. Using a hidden Markov model\, we estimate the most likely date of the primary case of a dengue outbreak in a small community in northern coastal Ecuador.\n*Bio*:\nHannah is a doctoral student in the Department of Epidemiology. Her research involves using mathematical models of infectious diseases to understand transmission dynamics. She has a background in mathematics and computer science at her undergraduate institution and a Master of Public Health in Epidemiology.\nMusawer Ahmad Saqif will present his talk: Fracture and Collapse Simulation of UHPC Structures.\nThis presentation delves into the advanced simulation techniques for understanding the fracture and collapse behaviors of ultra-high performance concrete (UHPC) structures. Leveraging finite element modeling and experimental validation\, the study elucidates the critical mechanical properties and failure mechanisms of UHPC under various conditions. Through a detailed investigation of microstructural characteristics and their impact on macroscopic performance\, the research provides valuable insights into optimizing the design and resilience of UHPC structures against extreme loading scenarios. The findings contribute significantly to the field of civil engineering by enhancing the predictive capabilities for the structural integrity and durability of UHPC infrastructures.\n*Bio*:\nM. A. Saqif is a fifth year PhD student in Civil Engineering and Scientific Computing at the Computational Structural Simulation Lab. His research interest lies in fracture and collapse simulation of concrete structures.\n*The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public.\nIf you have any questions\, please email micde-events@umich.edu.*
URL:https://micde.umich.edu/event/workshop-seminarmicde-ph-d-student-seminar-hannah-van-wyk-and-musawer-ahmad-saqif/
LOCATION:Duderstadt Center – 1180
CATEGORIES:Phd Seminar,Scientific Computing,Seminar,Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20240409T120000
DTEND;TZID=America/Detroit:20240409T130000
DTSTAMP:20240405T124240Z
CREATED:20240220T232015Z
LAST-MODIFIED:20240405T124240Z
UID:10000675-1712664000-1712667600@micde.umich.edu
SUMMARY:MICDE Ph.D. Student Seminar: Jeffrey Hatch and Jiadong Chen
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public but we ask that all attendees register so that we can prepare properly. If you have any questions\, please email micde-events@umich.edu. \nRegister to attend this seminar \n  \nJeffrey Hatch: An introduction to the many-body basis set amelioration method\nModeling the interaction of subatomic particles in chemical species has become a routine part of modern chemical research as this analysis can be used to find a system’s energy\, thermodynamic properties and more. The algorithms that can accomplish this vary in their accuracy and computational cost\, with more accurate methods generally incurring more cost. Additionally\, the more subatomic particles present\, the more costly the calculation will be. A computationally intensive family of methods known as select configuration interaction methods are generally thought of as the most accurate and most computationally expensive family of methods. However\, due to their high cost\, it is requisite that we investigate mechanisms of diminishing the cost while maintaining accuracy. The nature of one such method\, incremental full configuration interaction (iFCI) lends itself to accurate extrapolations based on much cheaper levels of theory in smaller basis sets. This is known as the many-body basis set amelioration (MBBSA) method. The MBSSA method has be shown to reduce the cost of a given calculation by as much as 80% without loss in the accuracy of the calculation.\n\nJeffrey Hatch\, Ph.D. candidate in Chemistry and Scientific Computing\nJeffrey is in the Zimmerman group in the chemistry department. He is interested in using HPC methods to improve quantum chemical calculations especially in the configuration interaction realm of electronic structure calculations.\n\n\n\nRegister to attend this seminar\n\n\n\nJiadong Chen: High dimensional phase diagrams: Engineering relative stability in 4-dimensions\nSequential learning algorithms based on Bayesian optimization are routinely being deployed for materials stability optimization in high-parameter spaces. We anticipate these optimization methods would perform better if they were built upon stronger priors\, for example\, as derived from the fundamental thermodynamics underlying the equilibrium behavior of materials. Here\, we present a thermodynamics-based technique to optimize the relative stability of a materials in high-dimensional thermodynamic space\, based on a new derivation of a generalized high-dimensional Clausius Clapeyron relation. Using this thermodynamic infrastructure\, we design several pathways to enhance the relative acid stability of Mn-oxides versus its dissolved states for potential electrochemical catalyst application. We construct a 4-D Pourbaix diagram with pH\, redox potential E\, particle radius 1/R and a chemical potential μK as axis. By exploring the gradients of the high-dimensional phase boundaries\, we derive first-principles insights that nano-sizing (1/R) and certain doping ions (μK) can stabilize some metastable Mn-oxides polymorphs\, where 1/R decreases acid stability and μK increases it. Our high-dimensional thermodynamic framework is a general method to engineer relative stability in parameter spaces that leverage multiple forms of thermodynamic work.\n\nJiadong Chen\, Ph.D. candidate in Materials Science and Engineering and Scientific Computing\nJiadong Chen is a 5th year PhD in materials science and engineering department\, Wenhao Sun group\, focusing on use computational and data-driven methods to predict materials stability and synthesis recipes.\n  \nRegister to attend this seminar
URL:https://micde.umich.edu/event/workshop-seminarmicde-ph-d-student-seminar-jeffrey-hatch-and-jiadong-chen/
LOCATION:Duderstadt Center – 1180
CATEGORIES:Phd Seminar,Scientific Computing,Seminar,Workshops
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20240416T120000
DTEND;TZID=America/Detroit:20240416T130000
DTSTAMP:20240414T192856Z
CREATED:20240220T232015Z
LAST-MODIFIED:20240414T192856Z
UID:10000676-1713268800-1713272400@micde.umich.edu
SUMMARY:Workshop / Seminar:MICDE Ph.D. Student Seminar: Anna Halstenbach and Katie Nissen
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public but we ask that all attendees register so that we can prepare properly. If you have any questions\, please email micde-events@umich.edu. \nRegister to attend this seminar \n  \nAnna Halstenbach: “Uncovering the network of political parties’ event sponsors in Germany”\nGray money in politics – those contributions that don’t fall under transparency regulations but cannot be made completely anonymous either\, for example sponsorships of political parties’ events – could change our understanding of money as a signal. However\, the fact that neither political parties nor firms are obliged to disclose such transactions makes studying them difficult. In the talk\, I will present one approach to measure gray money on the basis of tweets from party conferences.\n\nAnna Halstenbach\, Ph.D. candidate in Political Science and Scientific Computing\nAnna earned her Bachelor’s degree from the University of Mannheim and her Master’s degree from Heinrich Heine University Düsseldorf. Her current research analyzes the distinct incentives within the regulatory frameworks governing political party finances in Germany and the United States. Additionally\, she explores the impact of consumer behavior on firms’ decisions to be vocal about their political donations and take controversial political stances.\n\n\n\nRegister to attend this seminar\n\n\n\nKatie Nissen: “Climate Change Protests and Gender: The Influence of Role Incongruence on Support for Social Movements”\nIn recent years\, we have seen an increase in the incidences of radical protests about climate change in response to lackluster mitigation efforts worldwide. Historically\, the environmental movement as a whole has long been an issue space where women have held prominent leadership positions. However\, role congruity theory posits that women – due to being perceived as more passive and docile than men – may not be regarded as “proper” leaders of social movements\, especially when such movements use radical tactics. How does the interaction of protest tactics and leadership gendering affect support for the current climate movement? In this paper\, we report the results of a pilot survey experiment to address this question. Respondents were exposed to mock news stories about climate protests where they received one of four treatment conditions that varied the protest characteristics between combinations of radical/traditional tactics and women leadership/gender of leadership not specified. Respondents were then asked to report on their level of support for the movement\, level of support for the protest\, and the likelihood of the movement’s success. We also asked respondents to write in their most important reason for supporting the movement or not\, to which we applied basic topic modelling to extract key themes. Ultimately\, our pilot results show support for notion that radical protest tactics harm both support and perceptions of the movement\, but that gender of the protest leadership does not make a significant difference. We believe that the latter result is most likely due to weakness of the gender treatment in the survey experiment\, so future iterations of this work will seek to develop a stronger prime for this component of our analysis.\n\nKatie Nissen\, Ph.D. candidate in Political Science and Scientific Computing\nKatie is a current fourth year Joint PhD Candidate in Political Science and Scientific Computing. Her research is primarily about factors that influence climate change discourse and public opinion\, and her dissertation will focus on the effects of optimism and pessimism on climate attitudes.\n  \nRegister to attend this seminar
URL:https://micde.umich.edu/event/workshop-seminarmicde-ph-d-student-seminar-anna-halstenbach-and-katie-nissen/
LOCATION:Duderstadt Center – 1180
CATEGORIES:Phd Seminar,Scientific Computing,Seminar,Workshops
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20250117T160000
DTEND;TZID=America/Detroit:20250117T170000
DTSTAMP:20260522T182843Z
CREATED:20241224T044635Z
LAST-MODIFIED:20260522T182843Z
UID:10000789-1737129600-1737133200@micde.umich.edu
SUMMARY:MICDE - NERS Seminar: Teresa Bailey\, Lawrence Livermore National Laboratory
DESCRIPTION:Bio: Teresa S. Bailey is the Associate Program Director of Computational Physics in LLNL’s Weapon Simulation and Computing program. She oversees the development of multiple multiphysics simulation tools across a wide range of applications. These codes span a broad range of physics\, chemistry\, and engineering application space. As required\, the codes are production-quality software products that are portable and computationally efficient on DOE’s most advanced HPC systems. \nBailey has been an LLNL employee since 2008. She began her career as a code physicist before moving into technical leadership roles as the Deterministic Transport project leader and the Nuclear Science program group leader. Bailey earned her B.S. in Nuclear Engineering from Oregon State University in 2002. She received the DOE Computational Science Graduate Fellowship to support her graduate work and earn her Ph.D. in Nuclear Engineering from Texas A&M in 2008. \nComputational Science and High-Performance Computing at Lawrence Livermore National Laboratory
URL:https://micde.umich.edu/event/workshop-seminarmicde-ners-seminar-teresa-bailey-lawrence-livermore-national-laboratory/
LOCATION:Johnson Rooms\, Lurie Engineering Center\, 3rd Floor LEC 3213ABC\, 1221 Beal Ave.\, Ann Arbor\, MI\, United States
CATEGORIES:College Of Engineering,Computational Science,Micde,Micde Seminar,Michigan Engineering,Nuclear Engineering and Radiological Sciences,Physics,Seminar
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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
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20251007T114500
DTEND;TZID=America/Detroit:20251007T124500
DTSTAMP:20251008T041229Z
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
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20251028T114500
DTEND;TZID=America/Detroit:20251028T124500
DTSTAMP:20251027T214532Z
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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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20251104T114500
DTEND;TZID=America/Detroit:20251104T124500
DTSTAMP:20251009T184957Z
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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