BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Michigan Institute for Computational Discovery and Engineering - ECPv6.15.20//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:Michigan Institute for Computational Discovery and Engineering
X-ORIGINAL-URL:https://micde.umich.edu
X-WR-CALDESC:Events for Michigan Institute for Computational Discovery and Engineering
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/Detroit
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20190310T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20191103T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20200308T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20201101T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20210314T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20211107T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20220313T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20221106T060000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210218T160000
DTEND;TZID=America/Detroit:20210218T170000
DTSTAMP:20260603T235413
CREATED:20230905T171258Z
LAST-MODIFIED:20230905T171258Z
UID:10000452-1613664000-1613667600@micde.umich.edu
SUMMARY:Ph.D Seminar: Matthew Duschenes & Yi Zhu
DESCRIPTION:MATTHEW DUSCHENES\, GRADUATE STUDENT\, APPLIED PHYSICS & SCIENTIFIC COMPUTING \nBio: I am in my third year of the Applied Physics & Scientific Computing Ph.D. programs\, after completing a master’s in theoretical physics in my home country of Canada. As a member of Dr. Krishna Garikipati’s Computational Physics group\, I am currently working on data driven modelling and am collaborating with several groups on applying these graph theoretic approaches to various systems of interest. \nGRAPH THEORETIC APPROACHES FOR PHYSICAL SYSTEMS: Numerical analyses of physical systems are conventionally performed using direct numerical simulations\, that have proven highly successful\, yielding high fidelity solutions to very high dimensional problems\, such as boundary value problems with upwards of tens of millions of degrees of freedom. However\, there is always a balance to be met between the desire for higher accuracy and additional physics to be modeled\, and the complexity\, interpret-ability and ease of representation of such solutions. To aid in this dilemma\, I will be introducing a novel graph theoretic approach\, allowing for lower dimensional\, reduced order models to be produced\, given small amounts of high fidelity data. In this talk I will explain how such an approach allows for an intuitive representation of the states of a systems\, and how it is possible to use a non-local calculus\, allowing for rigorous operators and equations to be defined on the graph. I will then be discussing some implementation details\, and convey the generality\, validity\, and future applications of this framework through some example results from collaborations. \nYI ZHU\, GRADUATE STUDENT\, CIVIL AND ENVIRONMENTAL ENGINEERING & SCIENTIFIC COMPUTING \n \nBio: Yi is a 3rd year PhD candidate in Civil and Environmental Engineering & Scientific Computation. His research focuses on simulation\, design\, and fabrication of active origami systems for engineering devices\, and is particularly focused on micro-scale shape morphing systems inspired by origami. \nSIMULATION AND DESIGN OF MICRO-ORIGAMI SYSTEMS: In this talk\, we will introduce some recent advancement in the simulation and the design of micro-origami systems. We will discuss the micro-origami structures we fabricated and the rapid simulation framework we developed to capture the behaviors of these active origami. We will focus on the simulation framework and demonstrate how we can capture the thermo-mechanically coupled folding behavior and contacts between origami panels effectively and rapidly. Finally\, we will introduce some ongoing work on extracting origami design principle with interpretable machine learning\, which demonstrates how we can use the simulation framework to create better origami design. \n  \n  \n\nThis event is part of MICDE’s Winter 2021 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
URL:https://micde.umich.edu/event/ph-d-seminar-matthew-duschenes-yi-zhu/
LOCATION:Zoom Event\, MI\, United States
CATEGORIES:Featured Events,MICDE PhD Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210216T150000
DTEND;TZID=America/Detroit:20210216T160000
DTSTAMP:20260603T235413
CREATED:20230905T171258Z
LAST-MODIFIED:20230905T171258Z
UID:10000428-1613487600-1613491200@micde.umich.edu
SUMMARY:MICDE Seminar: Emma Lejeune\, Assistant Professor\, Mechanical Engineering\, Boston University
DESCRIPTION:Bio: Emma Lejeune is an Assistant Professor in the Mechanical Engineering Department at Boston University. She received her PhD from Stanford University in September 2018\, and was a Peter O’Donnell\, Jr. postdoctoral research fellow at the Oden Institute at the University of Texas at Austin until 2020 when she joined the faculty at BU. At BU\, Emma has received the David R. Dalton Career Development Professorship\, a Computational Science and Engineering Junior Faculty Fellowship\, and the Haythornthwaite Research Initiation Grant from the ASME Applied Mechanics Division. Current areas of research involve integrating data-driven and physics based computational models\, and characterizing and predicting the mechanical behavior of heterogeneous materials and biological systems. \nMODELING HETEROGENEOUS MATERIALS: BENCHMARK DATASETS\, METAMODELS\, AND EXPERIMENTAL CHARACTERIZATION: \nBiological systems are spatially heterogeneous across scales. To effectively model biological materials we need new tools to quantify and capture this heterogeneity. In this talk\, we will first discuss our recent work on simulating spatially heterogeneous materials. Specifically\, we will discuss our recent work in developing and exploring benchmark datasets of spatially heterogeneous materials simulated with the finite element method. These datasets are useful primarily for constructing metamodels\, or computationally cheap models of models\, that map defined model inputs to defined model outputs. By nature\, a given metamodel will be tailored to a specific dataset. However\, the most pragmatic metamodel type and structure will often be general to larger classes of problems. At present\, the most pragmatic metamodel selection for predicting the mechanical behavior of spatially heterogeneous materials — specifically simulations of heterogenous materials — has not been thoroughly explored. Drawing inspiration from the benchmark datasets available to the computer vision research community\, we introduce a benchmark data set (Mechanical MNIST https://open.bu.edu/handle/2144/39371) for constructing metamodels of heterogeneous material undergoing large deformation. We then show a few examples of problems that we have explored thus far with this dataset. Looking forward\, we anticipate that disseminating benchmark datasets will enable the broader community of researchers to develop improved metamodeling techniques for capturing the behavior of spatially heterogeneous materials that will surpass the baseline performance that we show here. Finally\, to conclude the talk\, we will change gears and briefly discuss some of our recent work on creating new tools for characterizing cell behavior using concepts from kinematics and spatial statistics. Looking forward\, we are interested in the natural synergy between advances in methods for both simulating and characterizing heterogeneous materials. \n\nThe MICDE Winter 2021 Seminar Series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nDr. Lejeune will be hosted by Professor Krishna Garikipati\, MICDE Director. \nWatch the full webinar. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-emma-lejeune-assistant-professor-mechanical-engineering-boston-university/
LOCATION:Zoom Event
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2020/11/Emma-Lejeune.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210211T160000
DTEND;TZID=America/Detroit:20210211T163000
DTSTAMP:20260603T235413
CREATED:20230905T171258Z
LAST-MODIFIED:20230905T171258Z
UID:10000451-1613059200-1613061000@micde.umich.edu
SUMMARY:Ph.D Seminar: Saibal De\, Applied and Interdisciplinary Mathematics & Scientific Computing
DESCRIPTION:Bio: Saibal De is a 5th year PhD candidate in Applied and Interdisciplinary Mathematics. His research involves using high-performance computing and novel algorithms for accelerating physics-based simulation frameworks\, and developing faithful reduced-order models of black-box high-fidelity simulations. \nTENSOR METHODS FOR DATA COMPRESSION: With the advancement of computing software and hardware\, physics-based simulations have gained notoriety in many scientific and industrial applications due to their highly accurate prediction capabilities. However\, in addition to being computationally expensive\, even a single of these high-fidelity simulations produce massive amounts of data. Storing and processing all these data thus requires novel approaches. In this talk\, I will present how we can use tensor factorization methods for compressing scientific data\, leading to dramatic savings in disk-space usage. Towards the end of the talk\, I’ll also touch upon how we can potentially construct reduced-order models out of these compressed datasets. \n\nThis event is part of MICDE’s Winter 2021 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
URL:https://micde.umich.edu/event/ph-d-seminar-saibal-de-applied-and-interdisciplinary-mathematics-scientific-computing/
LOCATION:Zoom Event\, MI\, United States
CATEGORIES:Featured Events,MICDE PhD Seminar Series
ATTACH;FMTTYPE=image/jpeg:https://micde.umich.edu/wp-content/uploads/2023/02/Headshot-Saibal-De.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210209T160000
DTEND;TZID=America/Detroit:20210209T170000
DTSTAMP:20260603T235413
CREATED:20230905T171258Z
LAST-MODIFIED:20230905T171258Z
UID:10000408-1612886400-1612890000@micde.umich.edu
SUMMARY:MICDE / Mechanical Engineering Seminar: Ceila Reina\, Assistant Professor\, Mechanical Engineering and Applied Mechanics\, University of Pennsylvania
DESCRIPTION:Bio:  Celia Reina is the William K. Gemmill Term Assistant Professor in Mechanical Engineering and Applied Mechanics at the University of Pennsylvania. She joined in 2014 after holding the Lawrence Postdoctoral Fellowship at Lawrence Livermore National Laboratory and the HCM postdoctoral Fellowship at the Hausdorff Center of Mathematics in Bonn\, Germany. Dr. Reina received her PhD from the California Institute of Technology in Aerospace Engineering in 2011\, under the supervision of Prof. Michael Ortiz\, following a B.S. in Mechanical Engineering from the University of Seville in Spain\, and a Master in Structural Dynamics from Ecole Centrale Paris in France. She is the 2017 recipient of the Eshelby Mechanics Award for Young Faculty\, she is a member of the TTA on Nanotechnology and Lower Scale Phenomena at the USACM\, and she currently serves as the recording secretary for the Applied Mechanics Division of the ASME. \nCONTINUUM MECHANICS OF NON-EQUILIBRIUM PHENOMENA: A JOURNEY THROUGH SPACE AND TIME SCALES:  The fascinating diversity of material behavior at the macroscopic scale can only emerge from the underlying atomistic or particle behavior. Yet\, the direct connection between these two scales remains an extremely challenging quest\, particularly in the context of non-equilibrium phenomena. In this talk\, we will discuss several advances in this direction\, in the context of plasticity\, thermoelasticity\, diffusion and viscous dissipation. In all these cases\, the importance of fluctuations in the effective response will become apparent. More precisely\, these will provide crucial information for the material description and evolution at the continuum scale\, where the behavior is modeled as deterministic and free of fluctuations. \n\nThe MICDE Winter 2021 Seminar Series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nThis event will be a joint seminar with the University of Michigan College of Engineering’s Mechanical Engineering department. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-mechanical-engineering-seminar-ceila-reina-assistant-professor-mechanical-engineering-and-applied-mechanics-university-of-pennsylvania/
LOCATION:Zoom Event
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2020/09/Celia-Reina.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210204T110000
DTEND;TZID=America/Detroit:20210204T120000
DTSTAMP:20260603T235413
CREATED:20230905T171258Z
LAST-MODIFIED:20230905T171258Z
UID:10000407-1612436400-1612440000@micde.umich.edu
SUMMARY:MICDE / MIDAS Seminar: Ivo Dinov\, Professor\, Nursing\, Computational Medicine & Bioinformatics
DESCRIPTION:Bio: Dr. Ivo D. Dinov directs the Statistics Online Computational Resource (SOCR)\, co-directs the multi-institutional Probability Distributome Project\, and is an associate director for education of the Michigan Institute for Data Science (MIDAS). \nDr. Dinov is an expert in mathematical modeling\, statistical analysis\, computational processing and visualization of Big Data. He is involved in longitudinal morphometric studies of human development (e.g.\, Autism\, Schizophrenia)\, maturation (e.g.\, depression\, pain) and aging (e.g.\, Alzheimer’s and Parkinson’s diseases). Dr. Dinov is developing\, validating and disseminating novel technology-enhanced pedagogical approaches for scientific education and active learning. \nDATA SCIENCE\, TIME COMPLEXITY\, AND SPACEKIME ANALYTICS \nMany observable processes demand managing\, harmonizing\, modeling\, analyzing\, interpreting\, and visualizing of large and complex information. There is a substantial need to develop\, validate\, productize\, and support novel mathematical techniques\, advanced statistical computing algorithms\, transdisciplinary tools\, and effective artificial intelligence applications. Spacekime analytics is a new technique for modeling high-dimensional longitudinal data. This approach relies on extending the notions of time\, events\, particles\, and wavefunctions to complex-time (kime)\, complex-events (kevents)\, data\, and inference-functions. We will illustrate how the kime-magnitude (longitudinal time order) and kime-direction (phase) affect the subsequent predictive analytics and the induced scientific inference. \nThe mathematical foundation of spacekime calculus reveal various statistical implications including inferential uncertainty and a Bayesian formulation of spacekime analytics. Complexifying time allows the lifting of all commonly observed processes from the classical 4D Minkowski spacetime to a 5D spacekime manifold\, where a number of interesting mathematical problems arise. Direct data science applications of spacekime analytics will be demonstrated using simulated data and clinical observations (e.g.\, structural and functional MRI). \n\nThe MICDE Fall 2020 and Winter 2021 Seminar Series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nWatch the recorded webinar. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-ivo-dinov-professor-nursing-and-computational-medicine-bioinformatics-university-of-michigan/
LOCATION:Zoom Event
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2020/09/Ivo-Dinov.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210127T140000
DTEND;TZID=America/Detroit:20210127T170000
DTSTAMP:20260603T235413
CREATED:20230905T171256Z
LAST-MODIFIED:20230905T171256Z
UID:10000423-1611756000-1611766800@micde.umich.edu
SUMMARY:Using GPUs with Python
DESCRIPTION:To view registration information for the February 24\, 2021 session of this workshop\, visit the event page. \n \nPython is the Lingua Franca of Data today and is being increasingly used in scientific computations. This workshop introduces Python GPU tools for porting and writing code that runs on GPUs. The primary tools\, Numba and CuPy\, are presented with examples. Back by popular demand\, this workshop is presented by Kristopher Keipert of NVIDIA. \nThis event is open to students\, faculty\, and staff within the University of Michigan community. A Jupyter notebook is used along with a set of lecture slides. The workshop will use online tools\, so there is no need to install any software ahead of time. \nThis event is brought to you by the Michigan Institute for Computational Discovery and Engineering\, and Consulting for Statistics\, Computing & Analytics Research at the University of Michigan in partnership with NVIDIA. \nSpace is limited\, register today!
URL:https://micde.umich.edu/event/using-gpus-with-python-3/
CATEGORIES:Featured Events
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210126T150000
DTEND;TZID=America/Detroit:20210126T160000
DTSTAMP:20260603T235413
CREATED:20230905T171256Z
LAST-MODIFIED:20230905T171256Z
UID:10000406-1611673200-1611676800@micde.umich.edu
SUMMARY:MICDE Seminar: Tianle Yuan\, Associate Research Scientist\, University of Maryland\, Baltimore County\, JCET\, NASA Goddard Space Flight Center
DESCRIPTION:About Dr. Tianle Yuan: Dr. Yuan received his B.S. in Geophysics and Computer Science from Peking University\, his Ph.D. from the University of Maryland\, College Park in 2008. After graduation\, he became affiliated with the Joint Center for Earth Systems Technologies (JCET) at the University of Maryland Baltimore County (UMBC) and NASA Goddard Space Flight Center (GSFC) as an Associate Research Scientist. His research interests include cloud and aerosol climate feedback\, aerosol-cloud interactions\, remote sensing\, cloud physics\, and application of ML/Deep Learning in Earth science. In deep learning applications\, Dr. Yuan published a few papers in modeling sub-grid clouds\, global scale clouds\, hurricane prediction\, finding ship-tracks\, and supervised and unsupervised cloud morphology classifications. \nARTIFICIAL INTELLIGENCE-BASED CLOUD DISTRIBUTOR (AI-CD): MODELING CLOUDS AT DIFFERENT SCALES\nHere we introduce the artificial intelligence-based cloud distributor (AI-CD) approach to generate cloud fields across different scales and cloud types. We show that generative adversarial nets (GANs) can not only generate realistic cloud fields with corresponding meteorological variables\, but also capture known physical relationship between cloud fields and meteorological variables such as sea surface temperature\, atmospheric stability\, and relative humidity etc. We demonstrate that this approach works across a large range of spatial scales: from individual grid points (sub-grid process modeling)\, multiple grids\, to global scale. In addition\, the AI-CD approach is stochastic in nature. We suggest the AI-CD approach can be used as a data-drive framework for stochastic cloud parameterization. \n\nThe MICDE Winter 2021 Seminar Series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nRegister to immediately receive Zoom details. Note: you may register after the event has started. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-tianle-yuan-research-associate-nasa-goddard-space-flight-center/
LOCATION:Zoom Event
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2020/09/Tianle-Yuan.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210119T160000
DTEND;TZID=America/Detroit:20210119T170000
DTSTAMP:20260603T235413
CREATED:20230905T171257Z
LAST-MODIFIED:20230905T171257Z
UID:10000427-1611072000-1611075600@micde.umich.edu
SUMMARY:MICDE Seminar: Yang Liu\, Research Scientist\, Scalable Solvers Group of the Computational Research Division at the Lawrence Berkeley National Laboratory
DESCRIPTION:About Dr. Liu: Yang Liu is a research scientist in the Scalable Solvers Group of the Computational Research Division at the Lawrence Berkeley National Laboratory\, in Berkeley\, California. Dr. Liu received the Ph.D. degree in electrical engineering from the University of Michigan in 2015. From 2015 to 2017\, he worked as a postdoctoral fellow at the Radiation Laboratory\, University of Michigan. From 2017 to 2019\, he worked as a postdoctoral fellow at the Lawrence Berkeley National Laboratory. His main research interest is in numerical linear and multi-linear algebras (including sparse solvers\, randomized low-rank\, butterfly and tensor algebras)\, computational electromagnetics (including fast iterative time-domain integral equation solvers\, fast direct integral and differential equation solvers\, and multi-physics\nmodeling)\, scalable machine learning algorithms\, and high-performance scientific computing. Dr. Liu authored and co-authored the Sergei A. Schelkunoff Transactions Prize Paper\, APS 2018\, second place student paper\, ACES 2012\, and the first place student paper\, FEM 2014. \nFAST\, DIRECT INTEGRAL DIFFERENTIAL EQUATION SOLVERS FOR ELECTROMAGNETIC ACOUSTIC\, AND ELASTIC APPLICATIONS AT ALL FREQUENCY RANGES: Large-scale and full-wave modeling for acoustic and elastic inversion applications\, analysis and synthesis of electromagnetic systems for traditional and emerging RF\, microwave\, terahertz applications rely on efficient numerical tools. Integral equation (i.e.\, method of moment) and differential equation (e.g.\, finite-difference\, finite-element\, and finite-volume) formulations lead to dense and sparse linear systems\, respectively. These linear systems can be solved by either iterative or direct solvers. Iterative solvers\, despite their success in constructing well-conditioned formulations and fast multipole-type algorithms\, remain inefficient for systems that are inherently ill-conditioned and/or require multiple right-hand sides. This is particularly true for design automation\, inverse scattering\, and other coupled systems where iterative solvers often require forbiddingly high iteration time. Direct solvers\, in stark contrast\, can attain reliable solutions in a predictable time. However\, exact direct solvers typically require O(N 3 ) and O(N 2 ) computational costs for dense and sparse systems of size N\, respectively. Fast direct solvers\, on the other hand\, rely on the fact that off-diagonal blocks of the well-ordered linear systems can be compressed by numerical linear algebra tools including low-rank and butterfly decompositions. When further embedded in hierarchical matrix frameworks\, such as H-matrix\, hierarchically off-diagonal low-rank (HODLR)\, and hierarchically semi-separable (HSS) formats\, these direct solvers and preconditioners can achieve quasi-linear complexities for construction\, factorization and solution for the discretized systems across all frequency ranges. We will review the development of these solvers in the past two decades\, with an emphasis on their butterfly-based variants and distributed-memory parallelization for high-frequency problems. An open source package integrating most techniques reviewed\, called ButterflyPACK\, will also be introduced. \n\nWatch the full webinar. \nNote: You can register after the webinar has started.
URL:https://micde.umich.edu/event/micde-aim-seminar-yang-liu-research-scientist-scalable-solvers-group-of-the-computational-research-division-at-the-lawrence-berkeley-national-laboratory/
LOCATION:Zoom Event\, MI\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2020/11/Yang-Liu.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20201203T150000
DTEND;TZID=America/Detroit:20201203T160000
DTSTAMP:20260603T235413
CREATED:20230905T171255Z
LAST-MODIFIED:20230905T171255Z
UID:10000401-1607007600-1607011200@micde.umich.edu
SUMMARY:MICDE / IOE Seminar: Salar Fattahi\, Assistant Professor\, Industrial & Operations Engineering\, University of Michigan
DESCRIPTION:About Salar Fattahi: Dr. Salar Fattahi is an Assistant Professor in the Department of Industrial and Operations Engineering at the University of Michigan. He received his M.S. and Ph.D. degrees in Industrial Engineering and Operations Research from UC Berkeley. He received a M.S. degree from Columbia University\, and a B.S. degree from Sharif University of Technology\, Iran\, both in Electrical Engineering. Salar’s research lies at the intersection of optimization\, data analytics\, and control theory. He was the recipient of several awards\, including the 2020 INFORMS ENRE Best Student Paper Award\, 2018 INFORMS Data Mining Best Paper Award and 2020 Power & Energy Society General Meeting Best-of-the-Best Paper Award. He was also a finalist for the 2018 American Control Conference Best Paper Award. \nWebinar: LARGE-SCALE INFERENCE OF TIME-VARYING MARKOV RANDOM FIELDS: BRIDGING THE GAP BETWEEN STATISTICAL AND COMPUTATIONAL EFFICIENCIES \nContemporary systems are comprised of a massive number of interconnected components that interact according to a hierarchy of complex\, dynamic\, and unknown topologies. For example\, with billions of neurons and hundreds of thousands of voxels\, the human brain is considered as one of the most complex physiological networks\, whose structure remains as a long-standing mystery. As another example\, the emergence of self-driving cars has only accentuated the need for the development of real-time and reliable methods for detecting moving objects\, whose temporal locations are captured through a dynamically-evolving 3D network. Nonetheless\, the vast amounts of parameters to be estimated\, caused both by the large number of components and the time-varying nature of the systems\, are currently the major bottlenecks in our ability to successfully solve such inference problems. \nThe temporal behavior of today’s interconnected systems can be captured via time-varying Markov random fields (MRF). A popular approach to achieve this goal is based on the so-called maximum-likelihood estimation (MLE): to find a probabilistic graphical model\, based on which the observed data is most probable to occur. The MLE-based methods suffer from several fundamental drawbacks which render them impractical in realistic settings. First\, they often suffer from notoriously high computational cost in the massive problems\, where the number of variables to be inferred is in the order of millions\, or more. Second\, they fail to efficiently incorporate prior structural information into their estimation procedure. With the goal of bridging this knowledge gap\, the aim of this work is to revisit the standard MLE as the “Holy Grail” of the inference methods for graphical models\, and precisely pinpoint and remedy the scenarios where it fails. A recurring theme in our proposed approach is a class of efficiently-solvable mixed-integer optimization problems that is used in lieu of the regularized MLE for the inference of time-varying MRFs. Our proposed optimization problems enjoy strong statistical and computational guarantees\, while being amenable to a wide class of graphical models with different side information\, such as sparsity\, smoothness\, etc. \n\nThe MICDE Fall 2020 and Winter 2021 Seminar Series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nThis event will be a joint seminar with the University of Michigan College of Engineering’s Industrial Operations & Engineering department. \nQuestions? Email MICDE-events@umich.edu \nConnect via this Zoom link: https://umich.zoom.us/j/96516676892#success
URL:https://micde.umich.edu/event/micde-ioe-seminar-salar-fattahi-assistant-professor-industrial-operations-engineering-university-of-michigan/
LOCATION:Zoom Event
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2020/09/Salar-Fattahi.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20201120T150000
DTEND;TZID=America/Detroit:20201120T160000
DTSTAMP:20260603T235413
CREATED:20230905T171255Z
LAST-MODIFIED:20230905T171255Z
UID:10000404-1605884400-1605888000@micde.umich.edu
SUMMARY:MICDE / AIM Seminar: Baole Wen\, Assistant Professor\, Mathematics\, University of Michigan
DESCRIPTION:About Baole Wen: Dr. Wen obtained a B.S. degree in Engineering Mechanics and a M.S. degree in Fluid Mechanics\, respectively\, from the Beijing University of Aeronautics and Astronautics.  He was awarded a CEPS Graduate Fellowship \& a Dissertation Year Fellowship and earned a Ph.D. in Applied Mathematics from University of New Hampshire in 2015.  His Ph.D. research was focused on understanding the underlying flow and transport mechanisms governing the spatiotemporally-chaotic system of porous medium convection at large Rayleigh numbers.  Upon graduation\, he was awarded a Peter O’Donnell\, Jr. Postdoctoral Fellowship through the Oden Institute for Computational Engineering and Sciences in the University of Texas at Austin.  His primary research interests are fluid dynamics\, mathematical modeling\, scientific computing and dynamical systems theory.  Recently\, he is working with Dr. Charles Doering as a Postdoctoral Assistant Professor at University of Michigan on extreme behavior in fundamental models of fluid mechanics. \nSTEADY COHERENT STATES IN RAYLEIGH–B\'{E}NARD CONVECTION: Buoyancy-driven flows are central to engineering heat transport\, atmosphere and ocean dynamics\, climate science\, geodynamics\, and stellar physics.   Rayleigh–B\’enard convection—the buoyancy driven flow in a fluid layer heated from below and cooled from above—is recognized as the simplest scenario in which to study such phenomena\, and beyond its importance for applications this problem has served for a century as one of the primary paradigms of nonlinear physics\, complex dynamics\, pattern formation and turbulence.   A central question about Rayleigh–B\’enard convection is how the Nusselt number $Nu$ depends on the Rayleigh number $Ra$ and the Prandtl number $Pr$—i.e.\, how heat flux depends on imposed temperature gradient and the ratio of the fluid’s kinematic viscosity to its thermal diffusivity—as $Ra\rightarrow\infty$.  Experiments and simulations have yet to rule out either `classical’ $Nu \sim Ra^{1/3}$ or `ultimate’ $Nu \sim Ra^{1/2}$ asymptotic scaling.  Here we provide clear quantitative evidence suggesting that the ultimate regime might not exist.  Our tactic is to study relatively simple time-independent states called rolls and compare heat transport by these rolls with that of turbulent convection.  These steady rolls are not typically seen in large-$Ra$ simulations or experiments because they are dynamically unstable.  Nonetheless\, they are part of the global attractor for the infinite-dimensional dynamical system defined by Rayleigh’s model\, and recent results suggest that steady rolls may be one of the key coherent states comprising the `backbone’ of turbulent convection.  By developing novel numerical methods\, we compute steady rolls between no-slip boundaries for $Ra\le 10^{14}$ with $Pr=1$ and various horizontal periods.  We find that rolls of the periods that maximize $Nu$ at each $Ra$ have classical $Nu\sim Ra^{1/3}$ scaling asymptotically\, and they transport more heat than turbulent experiments or simulations at similar parameters.  If turbulent heat transport continues to be dominated by steady transport asymptotically\, it cannot achieve ultimate scaling. \n\nThe MICDE Fall 2020 and Winter 2021 Seminar Series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nThis event will be a joint seminar with the University of Michigan Applied Interdisciplinary Mathematics. \nQuestions? Email MICDE-events@umich.edu \nJoin the webinar via the Zoom details below:\nhttps://umich.zoom.us/j/96450383843 \nMeeting ID: 964 5038 3843\nPasscode: 010182
URL:https://micde.umich.edu/event/micde-aim-seminar-baole-wen-assistant-professor-mathematics-university-of-michigan/
LOCATION:Zoom Event
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2020/09/Baole-Wen.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20201112T110000
DTEND;TZID=America/Detroit:20201112T120000
DTSTAMP:20260603T235413
CREATED:20230905T171255Z
LAST-MODIFIED:20230905T171255Z
UID:10000403-1605178800-1605182400@micde.umich.edu
SUMMARY:MICDE Seminar: Denise Kirschner\, Professor\, Microbiology and Immunology\, University of Michigan Medical School
DESCRIPTION:About Denise Kirschner: Dr. Kirschner received her Bachelors\, Masters and PhD in applied mathematics from Tulane University. She did graduate work also at Los Alamos National Labs and a postdoctoral fellowship at Vanderbilt University joint with the departments of Mathematics and Infectious Diseases. Over the past 25 years Dr. Kirschner has focused on questions related to models of host-pathogen interactions in infectious diseases. Her main focus has been to build models of persistent infections (e.g. Helicobacter pylori and Mycobacterium tuberculosis and HIV-1). Her goal is to understand the complex dynamics involved\, together with how perturbations to this interaction (via treatment with chemotherapies or immunotherapies) can lead to prolonged or permanent health. For the past 20 years\, her research focus has been on building multi-scale models to describe the host immune response to M. tuberculosis at multiple spatial and time scales and in multiple physiological compartments including lung\, lymph nodes and blood. \nTo date\, she have worked and collaborated with experimentalists generating data on TB with mouse\, non-human primate and human studies. Denise has over 150 publications in top journals describing this work that spans topics from methodological to biological advancement. Dr. Kirschner currently serves (and has for the past 17 years) as Editor-in-Chief of the Journal of Theoretical Biology. She serves as the founding co-director of The Center for Systems Biology at the University of Michigan\, an interdisciplinary center at the University of Michigan aimed to facilitate research and training between wet-lab and theoretical scientists. In 2016 she was elected as President-elect of the Society for Mathematical Biology and has served as its president from 2017-2020. Denise’s passion for mentoring students\, postdoctoral fellows and junior faculty has been a major focus of her career\, and her key mission is to promote both mathematics and family values in the scientific community.\n \nAPPROACHES FOR STUDYING MULTISCALE COMPUTATIONAL MODELS:  \nMycobacterium tuberculosis is a bacterium that infects 1/3 of the world today. While only 10% of infected individuals experience active tuberculosis disease\, if left untreated infection results in death. The remainder of individuals harbor the bacteria in a clinically latent infection\, and those individuals can experience reactivation of infection up to 10% per year. Our goal in a number of studies is to understand the role of the bacteria in initiating\, sustaining and inhibiting the immune response during infection. Granulomas are a hallmark of tuberculosis infection arising within lungs of infected humans. Understanding the immune response that leads to formation of granulomas can help us better design therapies to control or clear infection. We use a hybrid multi-scale approach that is fine grained for spatial details to help uncover these dynamics paired with a coarse grained spatial model that allows us to capture the entire host dynamics. We use a combination of statistic and mathematical and engineering approaches to predict optimal treatments. \n\nThe MICDE Fall 2020 and Winter 2021 Seminar Series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nWatch the full webinar here. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-denise-kirschner-professor-microbiology-and-immunology-university-of-michigan-medical-school/
LOCATION:Zoom Event
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2020/09/Denise-Kirschner.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20201020T150000
DTEND;TZID=America/Detroit:20201020T160000
DTSTAMP:20260603T235413
CREATED:20230905T171253Z
LAST-MODIFIED:20230905T171253Z
UID:10000402-1603206000-1603209600@micde.umich.edu
SUMMARY:MICDE Seminar: Grace Gu\, Assistant Professor\, Mechanical Engineering\, University of California- Berkeley
DESCRIPTION:About Grace Gu: Grace X. Gu is an Assistant Professor of Mechanical Engineering at the University of California\, Berkeley. She received her Ph.D. and MS in Mechanical Engineering from the Massachusetts Institute of Technology and her BS in Mechanical Engineering from the University of Michigan\, Ann Arbor. Her current research focuses on creating new materials with superior properties for mechanical\, biological\, and energy applications using multiphysics modeling\, artificial intelligence\, and high-throughput computing\, as well as developing intelligent additive manufacturing technologies to realize complex material designs previously impossible. Gu is the recipient of several awards\, including the 3M Non-Tenured Faculty Award\, MIT Tech Review Innovators Under 35\, Johnson & Johnson Women in STEM2D Scholars Award\, Royal Society of Chemistry Materials Horizons Outstanding Paper Prize\, and SME Outstanding Young Manufacturing Engineer Award. \n  \n\nMETAMATERIALS DESIGN AND MANUFACTURING: LEARNING FROM BIOLOGY AND ARTIFICIAL INTELLIGENCE\nAfter billions of years of evolution\, it is no surprise that biological materials are treated as an invaluable source of inspiration in the search for new materials. Additionally\, developments in computation spurred the fourth paradigm of materials discovery and design using artificial intelligence. Our research aims to advance design and manufacturing processes to create the next generation of high-performance engineering and biological materials by harnessing techniques integrating artificial intelligence\, multiphysics modeling\, and multiscale experimental characterization. This work combines computational methods and algorithms to investigate design principles and mechanisms embedded in materials with superior properties\, including bioinspired materials. Additionally\, we develop and implement deep learning algorithms to detect and resolve problems in current additive manufacturing technologies\, allowing for automated quality assessment and the creation of functional and reliable structural materials. These advances will find applications in robotic devices\, energy storage technologies\, orthopedic implants\, among many others. In the future\, this algorithmically driven approach will enable materials-by-design of complex architectures\, opening up new avenues of research on advanced materials with specific functions and desired properties. \n\nThe MICDE Fall 2020 and Winter 2021 Seminar Series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nTo view the recording for this event\, please complete this form and a link will be sent to you. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-grace-gu-assistant-professor-mechanical-engineering-university-of-california-berkeley/
LOCATION:Zoom Event
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2020/09/Grace-Gu.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20201020T113000
DTEND;TZID=America/Detroit:20201020T130000
DTSTAMP:20260603T235413
CREATED:20230905T171253Z
LAST-MODIFIED:20230905T171253Z
UID:10000405-1603193400-1603198800@micde.umich.edu
SUMMARY:LSA Complex Systems / MICDE / MIDAS Seminar: Marissa Renardy\, Research Fellow\, Microbiology & Immunology\, University of Michigan
DESCRIPTION:Predicting the second wave of COVID-19 in Washtenaw County\, MI\nAbstract: In this work\, we study and predict the spread of COVID-19 in Washtenaw County\, MI through applying a discrete and stochastic network-based modeling framework. In this framework\, we construct contact networks based on synthetic population datasets specific for Washtenaw County that are derived from US Census datasets. We assign individuals to households\, workplaces\, schools\, and group quarters (such as prisons or long term care facilities). In addition\, we assign casual contacts to each individual at random. Using this framework\, we explicitly simulate Michigan-specific government-mandated workplace and school closures as well as social distancing measures. We perform sensitivity analyses to identify key model parameters and mechanisms contributing to the observed disease burden in the three months following the first observed cases of COVID-19 in Michigan. We then consider several scenarios for relaxing restrictions and reopening workplaces to predict what actions would be most prudent. In particular\, we consider the effects of 1) different timings for reopening\, and 2) different levels of workplace vs. casual contact re-engagement. Through simulations and sensitivity analyses\, we explore mechanisms driving the magnitude and timing of a second wave of infections upon re-opening. \nThis work is based on Dr. Renardy’s paper in press in the Journal of Theoretical Biology with coauthors:\nMarisa Eisenberg\, UM Complex Systems & Math (LSA) and Epidemiology (Public Health)\nDenise Kirschner\, UM Department of Microbiology & Immunology (Medical School) \nRegistration is not required for this event\, you may join the seminar via this link. \nThe recording of this webinar will be available for viewing soon! \nThis seminar is hosted by the LSA Center for the Study of Complex Systems\, and co-sponsored by the Michigan Institute for Computational Discovery & Engineering (MICDE) and the Michigan Institute for Data Science (MIDAS).
URL:https://micde.umich.edu/event/lsa-complex-systems-micde-midas-seminar-marissa-renardy-research-fellow-microbiology-immunology-university-of-michigan/
LOCATION:Zoom Event
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2020/09/Marissa-Renardy.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20201009T093000
DTEND;TZID=America/Detroit:20201009T160000
DTSTAMP:20260603T235413
CREATED:20230905T171254Z
LAST-MODIFIED:20230905T171254Z
UID:10000357-1602235800-1602259200@micde.umich.edu
SUMMARY:Workshop on Resilient Cities through Computation
DESCRIPTION:On October 9\, 2020 the Michigan Institute for Computational Discovery and Engineering will host the Workshop on Resilient Cities through Computation. In addition to talks by experts who are driving new fronts in computing and natural hazards\, it will include hands-on workshop’s goal is to introduce the Simple Run-Time Infrastructure software toolkit (SRTI). \nKeynote Speaker:\n\nTerri McAllister\nCommunity Resilience Group Leader and Program Manager\nNational Institute of Standards and Technology \nMore information at micde.umich.edu/workshop-resilient-cities-2020. \nThis event is organized by MICDE’s Center for Scientific Software Infrastructure and with support from the department of Civil and Environmental Engineering.
URL:https://micde.umich.edu/event/2020-micde-symposium/
LOCATION:Zoom Event\, MI\, United States
CATEGORIES:Conference,Featured Events
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200929T140000
DTEND;TZID=America/Detroit:20200929T150000
DTSTAMP:20260603T235413
CREATED:20230905T171252Z
LAST-MODIFIED:20230905T171252Z
UID:10000409-1601388000-1601391600@micde.umich.edu
SUMMARY:MICDE / Mechanical Engineering Seminar: Sophia Haussener\, Associate Professor\, Laboratory of Renewable Energy Science and Engineering\, EPFL\, Lausanne\, Switzerland
DESCRIPTION:View webinar recording. \nBio: Sophia Haussener is an Associate Professor heading the Laboratory of Renewable Energy Science and Engineering at the Ecole Polytechnique Fédérale de Lausanne (EPFL). Her current research is focused on providing design guidelines for thermal\, thermochemical\, and photoelectrochemical energy conversion reactors through multi-physics modelling. Her research interests include: thermal sciences\, fluid dynamics\, charge transfer\, electro-magnetism\, and thermo/electro/photochemistry in complex multi-phase media on multiple scales. She received her MSc (2007) and PhD (2010) in Mechanical Engineering from ETH Zurich. Between 2011 and 2012\, she was a postdoctoral researcher at the Joint Center of Artificial Photosynthesis (JCAP) and the Energy Environmental Technology Division of the Lawrence Berkeley National Laboratory (LBNL). She has published over 70 articles in peer-reviewed journals and conference proceedings\, and 2 books. She has been awarded the ETH medal (2011)\, the Dimitris N. Chorafas Foundation award (2011)\, the ABB Forschungspreis (2012)\, the Prix Zonta (2015)\, the Global Change Award (2017)\, and the Viskanta Award (2019)\, and is a recipient of a Starting Grant of the Swiss National Science Foundation (2014). She is a deputy leader in the Swiss Competence Center for Energy Research (SCCER) on energy storage and acts as a Member of the Scientific Advisory Council of the Helmholtz Zentrum. \nModelling\, experimentation and scaling of photo-electrochemical fuel processing devices\nThe development of a sustainable energy economy based on renewable\, carbon-neutral energy is a necessary and urgent task. Photo-electrochemical approaches for solar fuels and materials are interesting\, provided they can be efficiently\, stably\, scalably\, and sustainably implemented. The functionality of such devices relies on complicated and coupled multi-physics processes\, occurring at multiple temporal and spatial scales. Device modelling can actively and efficiently support the choice of the most promising – in terms of efficiency\, cost\, robustness\, scalability\, and practicability – conceptual design pathways\, material choices\, and operating approaches. \nFirst\, I focus on cost competitive photo-electrochemical (PEC) devices identified through quasi-transient techno-economic modelling [1]. I will describe the conceptual idea of thermal integration in the context of PEC [2]\, provide results of maximum theoretical efficiency calculations to quantify the benefits\, and review the modelling framework that enabled the design of a feasible device [3]. I will illustrate how we have used our models to design and implement a PEC device with a solar-to-fuel efficiency of 17%\, and discuss ongoing approaches to scale up by our lab in order to bridge the gap between research and practical applications. \nSecond\, I will discuss detailed multi-dimensional mesoscale models that allow to assess the transport in complex (photo)electrodes. Specifically\, we use direct pore-level simulations for the coupled transport characterization of mesostructured (photo)electrodes utilizing nano-tomography techniques to obtain the exact mesostructure that is utilized in direct numerical simulations [4]. I will extend these investigations to ordered structures for the assessment of the transport in mesostructured electrodes for the electorchemical reduction of CO2 and discuss the effect of the mass transport on selectivity and activity [5]. I will then present possibilities to simplify these involved multi-dimensional numerical models into rapid screening models based on semi-analytical correlations. I will discuss analysis results for a large range of semiconductor materials [6\,7]. I will end with an outlook on research challenges and gaps in the field of (photo)electrochemical water and CO2 splitting. \n\nThis seminar is co-hosted by the Michigan Institute for Computational Discovery & Engineering\, and the Mechanical Engineering department within the University of Michigan College of Engineering. Dr. Haussener will be hosted by Rohini Bala Chandran\, Assistant Professor of Mechanical Engineering. \nThe MICDE Fall 2020 and Winter 2021 Seminar Series is open to the general public. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend.  \nQuestions? Email MICDE-events@umich.edu \n\nReferences: \n[1] M. Dumortier\, S. Tembhurne\, S. Haussener\, Energy Environ. Sci. \, 8:3614–3628\, 2015\n[2] S. Tembhurne\, F. Nandjou\, S. Haussener\, Nature Energy\, 10.1038/s41560-019-0373-7\, 2019\n[3] S. Tembhurne\, S. Haussener\, Journal of The Electrochemical Society \, 163:H1008-H1018\, 2016\n[4] S. Suter\, M. Catoni\, Y. Gaudy\, S. Pokrant\, S. Haussener\, Linking Morphology and Multi-Physical Transport in\nStructured Photoelectrodes\, Sustainable Energy & Fuels \, doi: 10.1039/C8SE00215K\, 2018.\n[5] S. Suter\, S. Haussener\, Energy Environmental Science \, doi: 10.1039/C9EE00656G\, 2019.\n[6] Y. Gaudy\, S. Haussener\, Rapid Performance Optimization Method for Photoelectrodes\, Journal of Physical Chemistry\nC\, doi: 10.1021/acs.jpcc.9b04102\, 2019.\n[7] Y. Gaudy\, Z. Gacevic\, Haussener\, Theoretical maximum photogeneration efficiency and performance characterization\nof InxGa1-xN/Si tandem water-splitting photoelectrodes\, APL Materials\, accepted\, 2020.
URL:https://micde.umich.edu/event/micde-mechanical-engineering-seminar-sophia-haussener-associate-professor-laboratory-of-renewable-energy-science-and-engineering-swiss-federal-institute-of-technology-lausanne/
LOCATION:Zoom Event
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2020/09/Sophia-Haussener.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200929T080000
DTEND;TZID=America/Detroit:20200929T170000
DTSTAMP:20260603T235413
CREATED:20230905T171252Z
LAST-MODIFIED:20230905T171252Z
UID:10000010-1601366400-1601398800@micde.umich.edu
SUMMARY:The 2020 MICDE Annual Symposium
DESCRIPTION:On September 29\, 2020 the Michigan Institute for Computational Discovery and Engineering will host its 2020 Annual Symposium. In addition to talks by external experts who are driving new fronts in computing\, the Symposium will showcase some of the game-changing research supported by our Catalyst Grants program\, and the workshop on Resilient Cities through Computation organized by MICDE’s Center for Scientific Software Infrastructure and with support from the department of Civil and Environmental Engineering. \nKeynote Speakers\n\nEwa Deelman\nResearch Professor and Research Director\nInformation Sciences Institute\nUniversity of Southern California \n\nIan Foster \nProfessor\, Computer Science\nUniversity of Chicago\nDirector\, Data Science and Learning Division\nArgonne National Laboratory \nA poster competition will be held\, open to post-docs and graduate students. \nMore information will be posted here as it becomes available. Also see https://live-umor-micde.pantheonsite.io/symposium20/
URL:https://micde.umich.edu/event/2020-micde-annual-symposium/
CATEGORIES:Conference,Featured Events
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200928T170000
DTEND;TZID=America/Detroit:20200928T210000
DTSTAMP:20260603T235413
CREATED:20230905T171252Z
LAST-MODIFIED:20230905T171252Z
UID:10000011-1601312400-1601326800@micde.umich.edu
SUMMARY:Student Hackathon: creating a hybrid simulation system using the Simple Run Time Infrastructure Software
DESCRIPTION:The hackathon’s goal is to introduce the Simple Run-Time Infrastructure software toolkit (SRTI) to the participants\, and provide a template project consisting of multiple simulators\, each with a specialized purpose\, relating to a natural-disaster scenario. \nThis is a free event and all students from any school/institution are welcome. You need basic coding skills to participate. \nThe first\, second and third place winners will received monetary prizes of $1000\, $600 and $400. \nThe hacakthon is part of the 2020 MICDE Symposium and is sponsored by MICDE and the Civil and Environmental Engineering department. \nFor more information https://live-umor-micde.pantheonsite.io/symposium20/
URL:https://micde.umich.edu/event/student-hackathon-creating-a-hybrid-simulation-system-using-the-simple-run-time-infrastructure-software/
CATEGORIES:Featured Events,Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200909T130000
DTEND;TZID=America/Detroit:20200909T140000
DTSTAMP:20260603T235413
CREATED:20230905T171250Z
LAST-MODIFIED:20260401T200546Z
UID:10000397-1599656400-1599660000@micde.umich.edu
SUMMARY:Testing and Code Review Practices in Research Software Development Webinar
DESCRIPTION: MICDE’s Center for Scientific Software Infrastructure encourages you to check out this webinar! \nThis webinar is part of the HPC Best Practices webinar series. This series address issues faced by developers of computational science and engineering (CSE) software on high-performance computers  (HPC). \nSoftware quality in a research context is essential because research software is used in mission-critical situations\, decision making\, and computation of evidence for research publications. This webinar will cover the use of two software quality practices in the development of research software: software testing and peer code review. These practices in software development can lead to both improved scientific results through higher quality software in the short term and more maintainable software in the long term. While these practices are essential for any type of software\, developers of research software typically do not use peer code review and software testing as frequently as they could for maximum impact. \nThe presenter\, California Polytechnic State University Assistant Professor Nasir Eisty\, will discuss the motivation\, challenges\, barriers\, and necessary improvements to make the practices effective for research software development\, based on studies of the research software community conducted via interviews\, surveys\, workshops\, and tutorials. \nParticipation is free and open to the public\, however registration is required for each event. This series is designed for HPC software developers who are seeking help in increasing their team’s productivity\, as well as facility staff who interact extensively with users. \nThese webinars have been organized by the IDEAS project in collaboration with the DOE/ASCR computing facilities (ALCF\, NERSC\, and OLCF)\, and the Exascale Computing Project (ECP).
URL:https://micde.umich.edu/event/testing-and-code-review-practices-in-research-software-development-webinar/
LOCATION:Zoom Event
CATEGORIES:Featured Events,Workshops
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/02/Testing-and-Code-Review-Practices-in-Research-Software-Development-Webinar.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200602T150000
DTEND;TZID=America/Detroit:20200602T160000
DTSTAMP:20260603T235413
CREATED:20230905T171345Z
LAST-MODIFIED:20230905T171345Z
UID:10000605-1591110000-1591113600@micde.umich.edu
SUMMARY:MICDE Webinar Series: Gabriel Ehrlich\, Director\, Research Seminar in Quantitative Economics\, University of Michigan
DESCRIPTION:Bio: Dr. Gabriel Ehrlich is the Director of the Research Seminar in Quantitative Economics (RSQE)\, and an Assistant Research Scientist in the department of Economics at the University of Michigan. Prior to joining RSQE\, he worked in the Financial Analysis Division at the Congressional Budget Office (CBO)\, where he forecast interest rates and conducted analysis on monetary policy and the mortgage finance system. His academic research focuses on several areas of housing and land economics as well as the effects of wage rigidity on labor market outcomes. \nMODELING THE ECONOMIC OUTLOOK IN THE TIME OF COVID-19\nWe will present the Research Seminar in Quantitative Economics’ (RSQE’s) forecast for the national and Michigan economies from 2020 to 2022. We will discuss the incoming data during the COVID-19 pandemic\, the near-term economic damage\, and the prospects for economic recovery. RSQE is the world’s oldest continuously operating economic forecasting unit and is home to the “Michigan Model” of the U.S. economy.
URL:https://micde.umich.edu/event/micde-webinar-series-gabriel-ehrlich-director-research-seminar-in-quantitative-economics-university-of-michigan/
LOCATION:Zoom Event\, MI\, United States
CATEGORIES:Education,Featured Events,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/07/Gabriel-Ehrlich.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200602T150000
DTEND;TZID=America/Detroit:20200602T160000
DTSTAMP:20260603T235413
CREATED:20230905T171345Z
LAST-MODIFIED:20230905T171345Z
UID:10000375-1591110000-1591113600@micde.umich.edu
SUMMARY:MICDE Webinar Series: Gabriel Ehrlich\, Director\, Research Seminar in Quantitative Economics\, University of Michigan
DESCRIPTION:Bio: Dr. Gabriel Ehrlich is the Director of the Research Seminar in Quantitative Economics (RSQE)\, and an Assistant Research Scientist in the department of Economics at the University of Michigan. Prior to joining RSQE\, he worked in the Financial Analysis Division at the Congressional Budget Office (CBO)\, where he forecast interest rates and conducted analysis on monetary policy and the mortgage finance system. His academic research focuses on several areas of housing and land economics as well as the effects of wage rigidity on labor market outcomes. \nMODELING THE ECONOMIC OUTLOOK IN THE TIME OF COVID-19\nWe will present the Research Seminar in Quantitative Economics’ (RSQE’s) forecast for the national and Michigan economies from 2020 to 2022. We will discuss the incoming data during the COVID-19 pandemic\, the near-term economic damage\, and the prospects for economic recovery. RSQE is the world’s oldest continuously operating economic forecasting unit and is home to the “Michigan Model” of the U.S. economy. \nWatch the full seminar.
URL:https://micde.umich.edu/event/webinar-gabriel-ehrlich-2020/
CATEGORIES:Featured Events,Webinar
ATTACH;FMTTYPE=image/jpeg:https://micde.umich.edu/wp-content/uploads/2023/02/Ehrlich.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200512T130000
DTEND;TZID=America/Detroit:20200512T140000
DTSTAMP:20260603T235413
CREATED:20230905T171344Z
LAST-MODIFIED:20260522T153619Z
UID:10000364-1589288400-1589292000@micde.umich.edu
SUMMARY:CAsToR Webinar: Modeling in Tobacco Control in the U.S. - the good\, the bad\, the ugly
DESCRIPTION:Center for the Assessment of Tobacco Regulations [CAsToR] leads Drs. Levy\, Mendez\, and Meza will provide an overview of modeling applications in tobacco control research\, discuss the types of models used in this field and their purpose\, as well as future directions for modeling in tobacco regulatory science. A Q&A session will follow. \nPlease contact Katie Zarins (kmrents@umich.edu) with questions \nDr. David Levy\nProfessor\nGeorgetown University\n  \n  \n  \n \nDr. David Mendez\nAssociate Professor\nUM School of Public Health\n  \n  \n  \n \nRafael Meza\nAssociate Professor\nUM School Public Health\n  \n  \n  \n 
URL:https://micde.umich.edu/event/castor-webinar-modeling-in-tobacco-control-in-the-u-s-the-good-the-bad-the-ugly/
LOCATION:Zoom Event
CATEGORIES:Featured Events,Webinar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200417T150000
DTEND;TZID=America/Detroit:20200417T163000
DTSTAMP:20260603T235413
CREATED:20230905T171344Z
LAST-MODIFIED:20230905T171344Z
UID:10000606-1587135600-1587141000@micde.umich.edu
SUMMARY:Webinar: Transmission modeling of infectious diseases and the COVID-19 outbreak
DESCRIPTION:This seminar will focus on differential equation transmission modeling approaches to analyze the spread of infections diseases\, and how Prof. Eisenberg and her colleagues are using them to model the current COVID-19 outbreak in the State of Michigan.Their current model is helping to forecast the numbers of laboratory-confirmed cases\, fatalities\, hospitalized patients\, and hospital capacity issues (such as ICU beds needed)\, and examining how social distancing can impact the spread of the epidemic.
URL:https://micde.umich.edu/event/webinar-transmission-modeling-of-infectious-diseases-and-the-covid-19-outbreak/
LOCATION:BlueJeans Events
CATEGORIES:Education,Featured Events,MICDE Seminar Series,Webinar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/07/Marisa-Eisenberg.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200409T130000
DTEND;TZID=America/Detroit:20200409T143000
DTSTAMP:20260603T235413
CREATED:20230905T171344Z
LAST-MODIFIED:20260522T183951Z
UID:10000358-1586437200-1586442600@micde.umich.edu
SUMMARY:Webinar: 2020 MICDE Catalyst Grants Showcase - Session II
DESCRIPTION:This webinar will showcase some of the game-changing research supported by our Catalyst Grants program. \nThis event was recorded and will be on the UM Youtube channel shortly. \nSpeakers\n \nStephen Smith\nAssociate Professor of Ecology and Evolutionary Biology\nUniversity of Michigan\nThe Emergence of Biological Complexity and Evolutionary Innovation in Plant Genomes\n\nXun Huan\nAssistant Professor of Mechanical Engineering\nUniversity of Michigan\nTowards Bayesian Uncertainty Quantification in Deep Learning Models for Brain Tumor Segmentation\nWhile the use of deep learning (DL) models in healthcare has grown rapidly in recent years\, the uncertainty/confidence information in their predictions is often unavailable and unreported. A lack of such information can render decision-making dangerous\, and prompt clinicians to hesitate in using and trusting these machine learning technologies. We propose to adopt principles and computational methods of uncertainty quantification for medical artificial intelligence applications\, focusing on a problem of brain tumor segmentation from MRI scans. As a first step\, we assess the robustness and sensitivity of two such DL models\, U-Net and SqueezeU-Net\, with respect to uncertainty in model weights\, which may arise due to sparsity and noise in training data features as well as labels. We achieve this through Monte Carlo uncertainty propagation of noise injected on trained weight values. The resulting uncertainty of segmentation maps can then be presented and visualized through robustness maps and summarizing box-plots of the Dice coefficients\, which can help indicate the regions where our models do not predict well and most susceptible to training noise. In our on-going work\, we seek to compute the Bayesian posterior distributions for the weights directly from training data. However\, performing a full-scale inference for the millions of weights in U-Net and SqueezeU-Net would be prohibitive. Instead\, we develop a procedure to use sensitivity analysis to identify the most important subset of weights (or layers)\, and perform a targeted Bayesian inference on this lower-dimensional parameter space. \n\nMonica Valluri\nResearch Professor of Astronomy\nUniversity of Michigan\nProbing the nature of dark matter by modeling the Milky Way\nDespite nearly four decades of research in astrophysics and particle physics\, the nature of dark matter\, the substance that comprises 85% of the matter in the universe\, is unknown. The shape of the Milky Way’s dark matter distribution and the variation of this shape with radius are important probes of the nature of dark matter. Mapping the detailed formation history of the Milky Way\, especially the number of satellites that were assimilated by our Galaxy and their masses and their time of infall will provide clues to the dark matter distribution in satellites as well as evidence for nearby streams and dark matter satellites. We are developing a multi-pronged approach to understanding the nature of dark matter with new dynamical tools\, new simulations and analysis of large cosmological simuations. I will describe progress on our efforts to enhance the galactic dynamics package AGAMA (Vasiliev\, 2019)by adding GPU acceleration for the potential and action solvers. I will provide an update on how we are using positions and velocities for old stars in the Milky Way’s halo to determine the three dimensional shape of the dark matter distribution and its variation with radius.I will describe new simulations of the evolution of satellites that merge with our Milky Way that can lead to insights into the fundamental nature of dark matter. Finally I will descibe the use of two cluster finding tools (a self organizing mapping and multi-dimensional density estimation)\, that when applied to action-space properties of stars in the Milky Way’s halo\, can yield insights into the accretion history of our Galaxy. This concert of efforts will significantly advance our goal of understanding the fundamental nature of dark matter using the properties of stars in the Milky Way.
URL:https://micde.umich.edu/event/catalyst-grants-webinar-session-2/
CATEGORIES:Featured Events
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200409T100000
DTEND;TZID=America/Detroit:20200409T113000
DTSTAMP:20260603T235413
CREATED:20230905T171344Z
LAST-MODIFIED:20230905T171344Z
UID:10000356-1586426400-1586431800@micde.umich.edu
SUMMARY:Webinar: 2020 MICDE Catalyst Grants Showcase - Session I
DESCRIPTION:This webinar will showcase some of the game-changing research supported by our Catalyst Grants program. \nThis event was recorded and will be on the UM Youtube channel shortly. \nSpeakers\n \nRobert Krasny\nProfessor of Applied Mathematics and Mathematics\nUniversity of Michigan\nINTEGRAL EQUATION BASED METHODS FOR SCIENTIFIC COMPUTING\nThere are several different approaches to the numerical solution of partial differential equations. For example\, finite-difference methods and finite-element methods discretize either the strong form or the weak form of the equation in real space\, while spectral methods discretize the equation in reciprocal space. This project employs an alternative method which converts the differential equation into an integral equation by convolution with the Green’s function\, followed by discretization and linear solution; the hope is that this approach is more amenable to adaptive refinement and parallelization than other methods. In the past\, integral equation based methods were hindered by the difficulty of discretizing singular integrals and the cost of computing dense matrix-vector products\, but these obstacles are being brought under control. We present our recent work in this area including (1) a GPU-accelerated barycentric treecode for long-range particle interactions\, (2) applications in electrostatics\, electronic structure\, and vortex dynamics. \n\nVikram Gavini\nProfessor of Mechanical Engineering\nUniversity of Michigan\nLong time-scale simulations using exponential time-propagators\nHigh-fidelity long-time scale simulations have been a challenge in a wide range of areas\, including time-dependent electronic structure calculations and molecular dynamics. In particular\, time-dependent density functional theory (TDDFT) calculations are limited to time-scales of the order of hundred femtoseconds\, and MD simulations (even those based on interatomic potentials) are routinely limited to time-scales of the order of nanoseconds. However\, there is very rich material phenomena\, both at the quantum and atomistic scale\, that occurs at time-scales that are orders of magnitude larger than the currently accessible range. In this talk\, I will present the ideas we have been exploring as part of the MICDE catalyst grant to enable long time-scale simulations on a class of time-dependent problems. In particular\, we investigate the use of exponential time-propagators as an alternative to the finite-difference based time-discretization of the PDEs. The ideas will be presented for time-dependent density functional theory and elastodynamics—as a prototypical problem for molecular dynamics—along with numerical results demonstrating the viability and computational efficiency of the proposed ideas. \nThis is joint work with Bikash Kanungo and Paavai Pari. \n\n \nYulin Pan\nAssistant Professor of Naval Architecture and Marine Engineering\nUniversity of Michigan\nReal-Time Phase-resolved ocean wave forecast with data assimilation enabled by gpu-accelerated computation\nThe real-time phase-resolved prediction of ocean waves is crucial for the safety of offshore operations. With the development of the remote sensing technology\, it is now possible to reconstruct the phase-resolved ocean surface from radar measurements in real time. Using the reconstructed ocean surface as initial condition\, nonlinear wave models such as the high-order spectral (HOS) method can be applied to predict the evolution of the ocean waves. However\, the computations reply heavily on large CPU clusters which are usually not available in the offshore onboard environment\, and the prediction can deviate quickly from the true wave evolution due to the chaotic nature of the nonlinear wave equations. To address these problems\, we develop a novel GPU-accelerated computational framework\, which features the coupling of HOS and an ensemble Kalman filter (EnKF) to reduce the uncertainties in the prediction. The new framework algorithm is tested and validated using both synthetic and real wave data\, and is shown promising in fundamentally improving the real-time prediction capability of ocean waves.
URL:https://micde.umich.edu/event/catalyst-grants-webinar-session-1/
CATEGORIES:Featured Events,Webinar
ATTACH;FMTTYPE=image/jpeg:https://micde.umich.edu/wp-content/uploads/2023/02/jzelner-e1584116599101.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200326T160000
DTEND;TZID=America/Detroit:20200326T170000
DTSTAMP:20260603T235413
CREATED:20230905T171342Z
LAST-MODIFIED:20230905T171342Z
UID:10000352-1585238400-1585242000@micde.umich.edu
SUMMARY:POSTPONED - MICDE/EEB Seminar: Yun Song\, Professor\, Computer Science and Statistics\, University of California\, Berkeley
DESCRIPTION:Bio: Yun S. Song is a professor of EECS and Statistics. He received the BS degrees in mathematics and physics from MIT\, and a PhD in physics from Stanford University. After his PhD\, he spent a year at the Mathematical Institute at the University of Oxford\, where he decided to change fields. He became a postdoctoral researcher in the Department of Statistics at Oxford\, and started doing research in computational biology and mathematical population genetics. From 2004 to 2007\, he was a postdoctoral researcher at UC Davis in the Department of Computer Science\, and the Section of Evolution and Ecology. \nThe key parameters that govern translation efficiency\nTranslation of mRNA into protein is a fundamental biological process mediated by the flow of ribosomes on mRNA transcripts.  With multiple factors that can potentially affect its efficiency\, this transport process is highly complex and heterogeneous: different mRNAs can have different initiation rates\, local elongation rates can vary substantially along the mRNA\, and multiple ribosomes can simultaneously translate the same mRNA\, potentially leading to interference.  In this talk\, I will present new theoretical results on a probabilistic model of mRNA translation which allowed us to identify the key parameters that govern the overall rate of protein synthesis\, sensitivity to initiation rate changes\, and efficiency of ribosome usage.  I will then describe our ongoing study\, which combines in vitro translation experiments with mathematical modeling\, to elucidate the role of the 5′ UTR (particularly uAUGs and uORFs) in regulating translation initiation in eukaryotes.
URL:https://micde.umich.edu/event/micde-seminar-yun-song/
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2021/08/Yun-S.-Song.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200320T150000
DTEND;TZID=America/Detroit:20200320T160000
DTSTAMP:20260603T235414
CREATED:20230905T171343Z
LAST-MODIFIED:20230905T171343Z
UID:10000351-1584716400-1584720000@micde.umich.edu
SUMMARY:POSTPONED - MICDE/AIM Seminar: John Harlim\, Professor\, Mathematics and Meteorology\, Penn State University
DESCRIPTION:Bio: John Harlim is a Professor in the Department of Mathematics and the Department of Meteorology and Atmospheric Sciences. Harlim received his undergraduate degree in Mathematics from the Universitas Padjadaran (Indonesia)\, a master’s from the University of Guelph in Applied Mathematics\, and a PhD in Applied Mathematics and Scientific Computation from the University of Maryland at College Park. His research interests in applied mathematics include parameter estimation\, machine learning\, manifold learning\, operator estimation\, data assimilation. \n Learning Missing Dynamics through Data\nThe recent success of machine learning has drawn tremendous interest in applied mathematics and scientific computations. In this talk\, I would address the classical closure problem that is also known as model error\, missing dynamics\, or reduced-order-modeling in various community. Particularly\, I will discuss a general framework to compensate for the model error. The proposed framework reformulates the model error problem into a supervised learning task to approximate a very high-dimensional target function involving the Mori-Zwanzig representation of projected dynamical systems. Connection to traditional parametric approaches will be clarified as specifying the appropriate hypothesis space for the target function. Theoretical convergence and numerical demonstration on modeling problems arising from PDE’s will be discussed.
URL:https://micde.umich.edu/event/micde-seminar-john-harlim-psu/
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2020/03/John-Harlim.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200313T150000
DTEND;TZID=America/Detroit:20200313T160000
DTSTAMP:20260603T235414
CREATED:20230905T171343Z
LAST-MODIFIED:20230905T171343Z
UID:10000355-1584111600-1584115200@micde.umich.edu
SUMMARY:CANCELLED - MICDE/AIM Seminar: Lyudmyla Barannyk\, Associate Professor\, Mathematics\, University of Idaho
DESCRIPTION:Bio: Lyudmyla Barannyk is an Associate Professor in the Department of Mathematics at the University of Idaho. Barannyk received a masters in Applied Mathematics from the New Jersey Institute of Technology and a PhD in Mathematics Sciences from the New Jersey Institute of Technology and Rutgers the State University of New Jersery. She is currently a visiting Associate Professor of Mathematics at the University of Michigan. \nModeling of the solid-liquid phase change in materials with internal heat generation\nWe study a simple model for the evolution of the solid-liquid interface during melting and solidification (Stefan problem) of a material with constant internal heat generation and prescribed heat flux at the boundary in the cylindrical geometry. The problem is motivated by the need to control the behavior of nuclear fuel rods in a potential meltdown scenario. The equations are solved by splitting them into transient and steady-state components and then using separation of variables. This results in an ordinary differential equation for the interface that involves infinite series. The initial value problem is solved numerically\, and solutions are compared to the previously published quasi-static solutions. We show that when the internal heat generation and boundary heat flux are close in value\, the motion of the phase change front takes longer to reach steady-state than when the values are farther apart. As the difference between the internal heat generation and boundary heat flux increases\, the transient solutions become more dominant and the phase change front does not reach steady-state before the outer boundary or centerline is reached. Hence the difference between the internal heat generation and boundary heat flux can be used to control the motion and speed of the solid-liquid interface. Limitations of the present model and possible future extensions will be discussed. \n\n\n\nThis is joint work with Sidney Williams (Georgia Tech)\, Irene Ogidan (University of Idaho)\, John Crepeau (University of Idaho)\, and Alexey Sakhnov (Kutateladze Institute of Thermophysics\, Novosibirsk\, Russia).
URL:https://micde.umich.edu/event/micde-aim-seminar-lyudmyla-barannyk/
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2020/03/Lyudmyla-Barannyk.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200313T150000
DTEND;TZID=America/Detroit:20200313T160000
DTSTAMP:20260603T235414
CREATED:20230905T171343Z
LAST-MODIFIED:20230905T171343Z
UID:10000009-1584111600-1584115200@micde.umich.edu
SUMMARY:MICDE Seminar: Demetrios Papageorgiou\, Professor\, Applied Mathematics\, Imperial College London
DESCRIPTION:POSTPONED UNTIL FURTHER NOTICE\nBio: Demetrious Papageorgiou is a Professor at Imperial College London.  He is an applied mathematician that works on problems that arise in fluid dynamics. He is interested in systems involving immiscible fluids that are characterized by the presence of spatiotemporally evolving sharp interfaces.  \nElectric field effects in immiscible multilayer flows\nMultilayer flows such as falling films and coating flows\, or pressure-driven flows of immiscible fluids in channels and pipes\, are fundamental in applications. Such flows are typically stable if they are slow enough (highly viscous). Such regimes arise in small-scale geometries (e.g. microfluidics)\, and electric fields can be used to drive the system out of equilibrium to produce patterning\, mixing and phase separation. \nI will begin with some experiments and direct numerical simulations (DNS) that show how electric fields can be utilized in their dual role of inducing instabilities or stability depending on geometry and orientation. I will then review the theoretical models underpinning such phenomena and will use asymptotic theories to derive and study reduced-dimension model equations that describe nonlinear interfacial waves in the presence of fields. Computations predict rich dynamics including spatiotemporal chaos and singularity formation. Some novel inertialess nonlinear interfacial instabilities will also be described – these arise due to flux functions of derived evolution equations changing type from hyperbolic to elliptic. Finally\, I will present results on the use of electric fields and/or blowing suction in achieving feedback and optimal control of falling film flows. Comparisons with DNS will be made and these will be used beyond the range of validity of asymptotic models to predict phenomena such as electrostatic suppression of Rayleigh-Taylor instabilities\, and electrostatically induced pumping in microchannels. \nThis seminar is co-sponsored by the Applied & Interdisciplinary Mathematics program. Prof. Papageorgiou is being hosted by Prof. Krasny (MATH).
URL:https://micde.umich.edu/event/fall2019-papageorgiou-imperialcollege/
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/jpeg:https://micde.umich.edu/wp-content/uploads/2023/02/portrait.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200228T150000
DTEND;TZID=America/Detroit:20200228T160000
DTSTAMP:20260603T235414
CREATED:20230905T171341Z
LAST-MODIFIED:20230905T171341Z
UID:10000333-1582902000-1582905600@micde.umich.edu
SUMMARY:MICDE Seminar: Sarah D. Olson\, Associate Professor\, Mathematical Sciences\, Worcester Polytechnic Institute
DESCRIPTION:Bio:Sarah Olson is an Associate Professor in the Department of Mathematical Sciences at Worcester Polytechnic Institute. Olson received her undergraduate degrees in Mathematics and Biology from Providence College\, a master’s from the University of Rhode Island in Mathematics\, and a PhD in Biomathematics from North Carolina State University. She has worked in the general areas of fluid dynamics\, scientific computing\, and mathematical biology. \nSperm Navigation in Complex Environments\nMicroorganisms can swim in a variety of environments\, interacting with chemicals and other proteins in the fluid. In this talk\, we will highlight recent computational methods and results for swimming efficiency and hydrodynamic interactions of swimmers in different fluid environments. Sperm are modeled via a centerline representation where forces are solved for using elastic rod theory. The method of regularized Stokeslets is used to solve the fluid-structure interaction where emergent swimming speeds can be compared to asymptotic analysis. In the case of fluids with extra proteins or cells that may act as friction\, swimming speeds may be enhanced and attraction may not occur. \nThis seminar is co-sponsored by the Applied & Interdisciplinary Mathematics program. Prof. Olson is being hosted by Prof. Alben (MATH). If you would like to meet with her during her visit\, please send an email to micde-events@umich.edu. If you are an MICDE student or a MATH student and you would like to join Professor Olson for lunch during her visit\, please RVSP by Feb. 27. 
URL:https://micde.umich.edu/event/micde-seminar-sarah-d-olson-wpi/
LOCATION:1084 East Hall\, 530 Church St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2020/01/Sarah-Olson.png
GEO:42.2757302;-83.7351764
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=1084 East Hall 530 Church St. Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=530 Church St.:geo:-83.7351764,42.2757302
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200225T113000
DTEND;TZID=America/Detroit:20200225T130000
DTSTAMP:20260603T235414
CREATED:20230905T171342Z
LAST-MODIFIED:20230905T171342Z
UID:10000354-1582630200-1582635600@micde.umich.edu
SUMMARY:Complex Systems Seminar: David Goluskin\, Assistant Professor\, Mathematics and Statistics\, University of Victoria
DESCRIPTION:Bio: David Goluskin is an Assistant Professor in the Department of Mathematics and Statistics at the University of Victoria. Goluskin received his undergraduate degrees from the University of Colorado\, Boulder\, a master’s from Columbia University\, and a PhD in Applied Mathematics from Columbia University. His research is in the broad area of applied nonlinear dynamics and incorporates both computation and analysis. Much of Professor Goluskin’s work concerns fluid dynamics\, but he also studies simpler ordinary and partial differential equations. \nStudying dynamics using computational polynomial optimization\nMany complex systems are governed by nonlinear ODEs or PDEs that cannot be solved exactly. Various properties of such solutions can be inferred by constructing auxiliary functions that satisfying suitable inequalities. The most familiar example is the construction of Lyapunov functions to infer stability of particular states\, but similar approaches can produce many other types of mathematical statements\, including for systems with chaotic or otherwise complicated behavior. Such statements include estimates of time-averaged quantities and extreme transient behavior\, approximation of nonlinear stability properties\, and design of controls. In many cases\, the search for the auxiliary function that implies the strongest mathematical statement can be posed as a convex optimization problem. Such problems can be studied analytically or computationally\, but in most cases computation is needed to find solutions that are close to optimal. Of particular use are computational methods of polynomial optimization\, where the optimization constraints include polynomial inequalities. This talk will provide an overview of different ways in which auxiliary functions can be used to study nonlinear ODEs and PDEs\, as well as how polynomial optimization can be used to implement these methods computationally. Methods will be illustrated using applications to various complex systems.
URL:https://micde.umich.edu/event/complex-systems-seminar-david-goluskin-assistant-professor-mathematics-and-statistics-university-of-victoria/
LOCATION:Weiser Hall\, Room 747\, 500 Church St\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,Seminar
ATTACH;FMTTYPE=image/jpeg:https://micde.umich.edu/wp-content/uploads/2023/02/event_72568_original-1-e1582558578476.jpg
END:VEVENT
END:VCALENDAR