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-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:20180311T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20181104T060000
END:STANDARD
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:20191010T150000
DTEND;TZID=America/Detroit:20191010T160000
DTSTAMP:20260608T181335
CREATED:20230905T171405Z
LAST-MODIFIED:20230905T171405Z
UID:10000246-1570719600-1570723200@micde.umich.edu
SUMMARY:MICDE Seminar: Ali Yilmaz\, Professor\, Electrical and Computer Engineering\, The University of Texas at Austin
DESCRIPTION:Bio: Ali Yilmaz is a Professor of Electrical and Computer Engineering and a core faculty member at the Institute for Computational Engineering and Sciences at the University of Texas at Austin. Dr. Yilmaz received the Ph.D. degree in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign in 2005. He spent 2005 to 2006 as a post-doctoral research associate with the Center for Computational Electromagnetics at the University of Illinois; in 2006\, he joined the faculty of The University of Texas at Austin. His research interests include computational electromagnetics (particularly fast frequency- and time-domain integral equation solvers)\, parallel algorithms\, antenna and scattering analysis\, bioelectromagnetics\, geoelectromagnetics\, and electronic packages. He has authored or co-authored over 170 papers in refereed journals and international conferences on these topics. \nUsing (Super)Computers Judiciously for Higher Fidelity Electromagnetic Analysis\nIncreasing the fidelity of the electromagnetic models generally increases the predictive power of the analyses based on the models. It also generally increases the results’ sensitivity to model features/parameters as well as the difficulty of constructing the models\, accurately solving the governing equations\, and interpreting the resulting data. Therefore\, one should base the analysis on the lowest-fidelity model one can get away with or\, equivalently\, the highest-fidelity model one can afford. The sweet spot for the tradeoff\, “the appropriate model”\, has changed over time in part because past successes in simulation-based science and engineering have increased expectations/requirements from electromagnetic analysis and in part because tremendous improvements in computing infrastructure and advances in computational methods have increased the affordability of complex analysis. Finding the appropriate model requires understanding both the benefits and the costs of analysis when a lower- or higher-fidelity model is used; neither side of the ledger\, however\, is known beforehand (unless one is repeating previously established analyses). A possible approach to revealing these unknowns is to construct models by gradually increasing their fidelity\, performing analysis at each fidelity level\, and comparing the analysis results and costs to those from the previous steps. I will show examples of this “analysis-driven modeling” in bioelectromagnetics (using the AustinMan and AustinWoman human body models) and signal integrity (using an electronic package example) by employing parallel algorithms and advanced integral-equation solvers on leading-edge supercomputers. \n The examples will highlight many of the challenges arising from this approach to modeling. An important one is that “the appropriate method” of analysis generally depends on the model\, e.g.\, a method can outperform alternatives for low-fidelity models but underperform them for high-fidelity ones; indeed\, inappropriate (but convenient) methods can not only inflate the cost side of the ledger but also deflate the benefit side\, leading to misjudgment of the appropriate model fidelity. Thus\, not surprisingly\, the development of appropriate electromagnetic models and appropriate computational methods are tightly linked (aka “if all you have is a hammer\, everything looks like a nail”). Unfortunately\, evaluating computational methods to find the appropriate one for a given model is surprisingly difficult\, even for unbiased experts\, as method performances depend not just on the models but also on the computers\, the software realizations of the methods\, and the users/developers of the software. On the one hand\, theoretical comparisons (e.g.\, of asymptotic complexities\, error convergence rates\, parallel scalability limits) are often incapable of factoring in the large impact of software and hardware infrastructure on the realized/observed performance of a computational method—a problem that has worsened as the traditional Dennard scaling of clock frequencies ended in the last decade. On the other hand\, empirical comparisons are beset by the same problems that physical measurements face (including irreproducible and uncertain results)\, require many (potentially low-efficiency) computations\, and suffer from the large number of alternative methods. I will discuss whether benchmark suites can improve the judicious use of computational methods for electromagnetic analysis and what the necessary ingredients for such benchmarks are. \nProf. Yilmaz is being hosted by Prof. Michielssen (EECS). If you would like to meet with him during his visit\, please send an email to micde-events@umich.edu. If you are an MICDE students\, or a EEC graduate student\, and would like to join Prof. Yilmaz for lunch\, please RSVP here by October 8th.  \n 
URL:https://micde.umich.edu/event/fall2019-yilmaz-utaustin/
LOCATION:1008 FXB\, 1320 Beal Ave\, Ann Arbor\, MI\, 48109
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2019/07/Ali-Yilmaz.png
GEO:42.2934832;-83.7119819
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=1008 FXB 1320 Beal Ave Ann Arbor MI 48109;X-APPLE-RADIUS=500;X-TITLE=1320 Beal Ave:geo:-83.7119819,42.2934832
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20191017T113000
DTEND;TZID=America/Detroit:20191017T123000
DTSTAMP:20260608T181335
CREATED:20230905T171337Z
LAST-MODIFIED:20230905T171337Z
UID:10000247-1571311800-1571315400@micde.umich.edu
SUMMARY:MICDE Seminar: Janet Scheel\, Associate Professor\, Physics\, Occidental College
DESCRIPTION:Bio: Dr. Scheel has taught at a variety of higher education institutions\, including California Lutheran University\, Caltech\, and Cornell University. She also conducted research at Cal Lutheran\, Caltech\, Cornell\, and Argonne National Laboratory. She is coauthor of Analytical Mechanics\, an advanced undergraduate physics textbook. She is currently a Mercator Fellow as a part of the Priority Programme SPP 1881 of the Deutsche Forschungsgemeinschaft. Janet Scheel’s research deals with pattern formation and turbulence. The particular system she studies is Rayleigh-Benard convection. \nNumerical Simulations of Turbulence in Heated Fluids\nTurbulent systems are all around us\, from waves crashing on our beaches\, to smoke rising from the fires in our mountains\, to the air that can disrupt our smooth airline flights. But\, turbulent systems are not well understood. Rayleigh-Benard Convection is a more simplified system which captures some of the key features of turbulence\, including thermal plumes\, thin boundary layers and large-scale flow. In Rayleigh-Benard convection\, an enclosed fluid is bounded by horizontal parallel plates kept at a constant temperature difference. Results from numerical simulations of the equations which describe Rayleigh-Benard convection will be discussed and compared to experimental and theoretical results. These include flows in air and liquid metals in confined containers in addition to more horizontally extended systems. \nThis seminar is jointly sponsored with the department of Complex Systems. Prof. Scheel is being hosted by Prof. Doering (Complex Systems\, Mathematics and Physics). 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 students and would like to join Prof. Scheel for lunch\, please RSVP  by October 15th. 
URL:https://micde.umich.edu/event/fall2019-scheel-occidentalcollege/
LOCATION:Weiser Hall\, Room 747\, 500 Church St\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2019/07/Janet-Scheel.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20191101T150000
DTEND;TZID=America/Detroit:20191101T160000
DTSTAMP:20260608T181335
CREATED:20230905T171337Z
LAST-MODIFIED:20230905T171337Z
UID:10000248-1572620400-1572624000@micde.umich.edu
SUMMARY:MICDE Seminar: Sanjay Govindjee\, Professor\, Civil Engineering\, University of California\, Berkeley
DESCRIPTION:Bio: Sanjay Govindjee is the Horace\, Dorothy\, and Katherine Johnson Professor in Engineering.  His main interests are in theoretical and computational mechanics with an emphasis on micro-mechanics of nonlinear phenomena in solid materials.  He was the winner of the inaugural Zienkiewicz Prize and Medal in 1998 and more recently received a 2018 Alexander von Humboldt Foundation Research Prize in honor of his lifetime achievements.  For the last two and half years\, he has been the PI and co-Director of the NSF NHERI SimCenter at Berkeley. \nThe NSF Natural Hazards Engineering Research Infrastructure (NHERI) Computation and Simulation Center (SimCenter) at Berkeley: An Overview\nIn October 2016\, the National Science Foundation awarded the NHERI SimCenter to Berkeley.  The SimCenter is the computational satellite to the eight experimental sites of the NHERI constellation.  Its primary goal is to advance natural hazards engineering through the use of simulation.  The center develops and stands-up open-source software to simulate the effects of seismic\, wind\, and water loads on structures with a focus on regional assessments of damage at high resolution under uncertainty.  The SimCenter’s work includes both research and educational components. \nThe SimCenter has just completed Year 3 or its original mandate and now offers a wide selection of user friendly front end applications that permit local as well as HPC cloud based execution of simulations.  Simulations can be of single detailed structural models subjected to a variety of harzards using state-of-the-art and state-of-the-practice loading methodologies.  They can also be of a larger regional nature using simpler models and further coupled to forward uncertainty propogation with Monte Carlo methods with or without surrogating.  Engineering demands can be further propogated into damage and loss\, downtime and recovery\, using Hazus methodologies\, FEMA P58 methods\, or user provided techniques with our hazard-blind framework.  All elements of the SimCenter’s software are desgined in a plug-n-play fashion to promote detailed research into natural hazard effects with the ability to see impacts on a larger scale. \nIn this presentation\, I will give an overview of the SimCenter’s recent activities and discuss research needs and how researchers can participate in the SimCenter’s activities\, along with a preview of upcoming developments anticipated in Year 4 \nProf. Govindjee is being hosted by Prof. Garikipati (ME).
URL:https://micde.umich.edu/event/fall2019-govindjee-ucberkeley/
LOCATION:1680 IOE\, 1205 BEAL AVE\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2019/07/Sanjay-Govindjee.png
GEO:42.2910524;-83.7137013
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=1680 IOE 1205 BEAL AVE Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=1205 BEAL AVE:geo:-83.7137013,42.2910524
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20191106T150000
DTEND;TZID=America/Detroit:20191106T160000
DTSTAMP:20260608T181335
CREATED:20230905T171337Z
LAST-MODIFIED:20230905T171337Z
UID:10000292-1573052400-1573056000@micde.umich.edu
SUMMARY:MICDE Seminar: Pablo Zavattieri\, Professor\, Civil Engineering\, Purdue University
DESCRIPTION:Bio: Dr. Pablo Zavattieri is a Professor of Civil Engineering and University Faculty Scholar at Purdue University. Zavattieri received his BS/MS degrees in Nuclear Engineering from the Balseiro Institute (Argentina) and PhD in Aeronautics and Astronautics Engineering from Purdue University. He worked at the General Motors Research and Development Center as a staff researcher for 9 years\, where he led research activities in the general areas of computational solid mechanics\, smart and biomimetic materials. His current research lies at the interface between solid mechanics and materials engineering. He has focused on the fundamental aspects of how Nature uses elegant and efficient ways to make remarkable materials and their translation to engineering materials. He has contributed to the area of biomimetic materials by investigating the structure-function relationship of naturally-occurring high-performance materials at multiple length-scales\, combining state-of-the-art computational techniques and experiments to characterize the properties.   \nCLEVER ARCHITECTURES\, INTERFACES AND COMPETING MECHANISMS IN BIOLOGICAL MATERIALS\nNature uses modest constituents to synthesize composite materials with exceptional mechanical properties for structural and impact resistance purposes. In most cases\, these materials achieved outstanding mechanical properties avoiding the typical trade-offs often attained by manmade materials. While these materials require modern microscopy techniques to characterize their complex hierarchical structures\, most of our learnings come from the way these materials mitigate catastrophic damage\, revealing the most important mechanisms and features of their inner structure that contribute to energy dissipation and toughening. Considering the current progress in material synthesis and manufacturing\, these new concepts have converged to the field of architected materials.  In this talk\, I will describe some interesting mechanics problems that we encountered as we studied some extraordinary species\, and how we can translate these lessons learned to architected materials. In particular\, I will focus on a few examples related to how the combination of clever architectures\, interfaces\, material properties and competing mechanisms can promote delocalization to mitigate catastrophic failure\, hence\, improving toughness and impact resistance without sacrificing other important mechanical properties. Most of this discussion is driven by how we can eventually translate these lessons learned to the development and manufacturing of architected materials. \nProf. Zavattieri is being hosted by Prof. Evgueni Flipov (CEE). If you would like to meet with him during his visit\, please send an email to micde-events@umich.edu. If you are an MICDE or CEE student and would like to join Prof. Zavattieri for lunch please RSVP by Monday\, November 4th. 
URL:https://micde.umich.edu/event/micde-seminar-pablo-zavattieri-professor-civil-engineering-purdue-university/
LOCATION:1303 EECS\, 1301 Beal Ave\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2019/10/Pablo-Zavattieri.png
GEO:42.292322;-83.713272
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=1303 EECS 1301 Beal Ave Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=1301 Beal Ave:geo:-83.713272,42.292322
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20191115T150000
DTEND;TZID=America/Detroit:20191115T160000
DTSTAMP:20260608T181335
CREATED:20230905T171339Z
LAST-MODIFIED:20230905T171339Z
UID:10000249-1573830000-1573833600@micde.umich.edu
SUMMARY:MICDE Seminar: Irene Beyerlein\, Professor\, Mechanical Engineering\, University of California\, Santa Barbara
DESCRIPTION:Bio: Irene J. Beyerlein is a Professor at the University of California at Santa Barbara (UCSB) with a joint appointment in the Mechanical Engineering and Materials Departments. She currently holds the Robert Mehrabian Interdisciplinary Endowed Chair in the College of Engineering. After receiving her Ph.D. degree in Theoretical and Applied Mechanics at Cornell University in 1997\, she began a postdoctoral appointment as a J.R. Oppenheimer Fellow at Los Alamos National Laboratory\, where she remained on the scientific staff in the Theoretical Division\, until 2016\, when she joined UCSB. She has published one book\, nine book chapters\, and more than 300 peer-reviewed articles in the field of structural composites\, materials processing\, multiscale modeling of microstructure/property relationships\, deformation mechanisms\, and polycrystalline plasticity. She is an Editor for Acta Materialia and Scripta Materialia and an Associate Editor for Modelling and Simulation in Materials Science and Engineering.  In recent years\, she has been awarded the Los Alamos National Laboratory Fellow’s Prize for Research (2012)\, the International Plasticity Young Researcher Award (2013)\, the TMS Distinguished Scientist/Engineering Award (2018)\, and the Brimacombe Metal (2019). \nA COMPOSITE OF SUPERIOR PROPERTIES WITH NANOSTRUCTURED COMPOSITE MATERIAL\nMany future engineering systems will rely on high-performance metallic materials that are several times stronger and tougher than those in use today. In many situations\, these superior properties will be desired in harsh environments\, such as elevated temperatures\, at high rates\, and under irradiation. Nanolaminates\, built from stacks of crystalline layers\, each with nanoscale individual thicknesses\, are proving to exhibit a composite of many of these target properties. Examples span from nanotwinned materials to biphase nanolaminates\, comprised of alternating nano-thick layers that differ in orientation\, chemistry and crystal structure. Studies on these materials report exceptional properties far beyond a volume average value of their constituents\, such as strengths that are over five to ten times higher\, hardness values that are several orders of magnitude higher\, and unprecedented microstructural stability in harsh environments\, such as irradiation\, sudden impact\, or elevated temperatures. While the combination of properties is clearly attractive\, one roadblock to applying the nanolaminate concept to any general composite material system is their complex\, highly anisotropic deformation behavior\, making them less reliable than coarsely structured materials. Critical to designing the material nanostructure to achieve uniformity and reliability is understanding and predicting the strength properties of nanostructure materials based on known conditions and measurable variables\, such as basic nanostructure size scales and chemical composition. Multiscale models for conventional coarse-grained materials have been in development for several decades\, but analogous versions for nanostructured materials require extensions to explicitly account for the overriding dominance of internal boundaries on these microstructure/property relationships.  The computational materials challenge lies in how to represent the discrete and statistical dislocation glide processes in nanostructured materials so that the profound influence of the fine nanoscale crystals can be properly replicated in simulation. In this talk\, we will present recent examples of computational techniques and some unanticipated couplings between nanostructural size effects and microstructural evolution and strength that arise from their application. \nProf. Beyerlein is being hosted by Prof. Fan (ME). 
URL:https://micde.umich.edu/event/fall2019-beyerlein-ucsb/
LOCATION:1680 IOE\, 1205 BEAL AVE\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2019/07/Irene-Beyerlein.png
GEO:42.2910524;-83.7137013
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=1680 IOE 1205 BEAL AVE Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=1205 BEAL AVE:geo:-83.7137013,42.2910524
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20191206T150000
DTEND;TZID=America/Detroit:20191206T160000
DTSTAMP:20260608T181335
CREATED:20230905T171338Z
LAST-MODIFIED:20230905T171338Z
UID:10000243-1575644400-1575648000@micde.umich.edu
SUMMARY:MICDE Seminar: Anna Vainchtein\, Professor\, Mathematics\, University of Pittsburgh
DESCRIPTION:Bio: Anna Vainchtein is a professor in the Department of Mathematics at the University of Pittsburgh. She is generally interested in mathematical modeling and analysis of nonlinear phenomena in materials science\, physics and biology. Examples include dynamics of phase boundaries\, cracks and dislocations in crystals\, hysteresis in phase-transforming materials\, solitary and heteroclinic traveling waves in nonlinear lattices and DNA overstretching. The resulting mathematical problems typically involve minimization of nonconvex functionals\, nonlinear PDEs that change type\, dynamical systems with many degrees of freedom and functional differential equations. Thus nonstandard analytical and numerical techniques are required. \nStrictly supersonic solitary waves in lattices\nWe consider a nonlinear mass-spring chain with first and second-neighbor interactions and show that there is a parameter range where solitary waves in this system are strictly supersonic. In these regimes standard quasicontinuum theories\, targeting long-wave limits of lattice models\, are not adequate since even weak strictly supersonic solitary waves are of envelope type and crucially involve a microscopic scale in addition to the mesoscopic scale of the envelope. To capture this effect in a continuum setting it is necessary to employ unconventional\, higher-order quasicontinuum approximations carrying more than one length scale. This talk is based on recent joint work with Lev Truskinovsky (ESPCI). \nThis seminar is co-sponsored by the Applied & Interdisciplinary Mathematics program. Prof. Vainchtein is being hosted by Prof. Garikipati (ME). If you would like to meet with her during her visit\, please send an email to micde-events@umich.edu. 
URL:https://micde.umich.edu/event/fall2019-vainchtein-upitt/
LOCATION:1084 East Hall\, 530 Church St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2019/07/Anna-Vainchtein.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:20191209T150000
DTEND;TZID=America/Detroit:20191209T160000
DTSTAMP:20260608T181335
CREATED:20230905T171338Z
LAST-MODIFIED:20230905T171338Z
UID:10000250-1575903600-1575907200@micde.umich.edu
SUMMARY:MICDE Seminar: Bo Zhu\, Assistant Professor\, Computer Science\, Dartmouth College
DESCRIPTION:Bio: Bo Zhu is an assistant professor of Computer Science at Dartmouth College. Prior to that\, he was a postdoctoral associate at MIT CSAIL. He received his Ph.D. in Computer Science from Stanford University in 2015. His research interests encompass computer graphics\, computational physics\, and computational fabrication. In particular\, he focuses on building computational approaches to automate the process of exploring complex physical systems. \nSuper-Resolution Structural Simulation and Optimization\nComplex physical systems exhibiting mixed-dimensional geometry and multi-scale mechanics are ubiquitous. Examples include biological structures\, such as insect wing exoskeletons\, fluid phenomena\, such as bubbles and jets\, and human-made objects\, such as microrobots. The beauty and complexity of these systems attract efforts from scientists\, engineers\, and artists in various fields. However\, a computational investigation of these systems on the level of super-resolution  –with millions to billions of computational elements — is still challenging\, due to the non-manifold geometric structures\, non-linear governing physics\, and the tight coupling between them. \nMy work tackles these challenges by rethinking of the computation pipeline—from a perspective that aims to blur the line between discrete geometry and continuous physics. My guiding principle is to study the hidden low-dimensional topological and structural characteristics underpinning these complex systems and to create the most natural geometric analogs in a discrete setting for efficient simulation and optimization. In this talk\, I will present two examples to demonstrate this methodology\, including a super-resolution topology optimization algorithm based on sparse grids to emerge biomimetic structures and a numerical simulation approach based on simplicial complexes to model codimensional fluids. These computational tools enable the investigation\, discovery\, and development of a broad range of complex physical systems that are multi-scale and mixed-dimensional\, with applications in computer graphics\, computational physics\, and additive manufacturing. \n  \nProf. Zhu is being hosted by Prof. Saitou (ME).  If you would like to meet with him during his visit\, please send an email to micde-events@umich.edu. If you are an MICDE graduate student and would like to join Prof. Zhu for lunch please RSVP by Friday\, December 6th .  \n 
URL:https://micde.umich.edu/event/fall2019-zhu-dartmouth/
LOCATION:1303 EECS\, 1301 Beal Ave\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2019/07/Bo-Zhu.png
GEO:42.292322;-83.713272
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=1303 EECS 1301 Beal Ave Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=1301 Beal Ave:geo:-83.713272,42.292322
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200115T120000
DTEND;TZID=America/Detroit:20200115T130000
DTSTAMP:20260608T181335
CREATED:20230905T171340Z
LAST-MODIFIED:20230905T171340Z
UID:10000311-1579089600-1579093200@micde.umich.edu
SUMMARY:MICDE Seminar: Allen Sanderson\, Research Scientist\, Scientific Computing and Imaging Institute\, The University of Utah
DESCRIPTION:Bio: Allen Sanderson\, Ph.D. is a Research Scientist at the University of Utah’s Scientific Computing and Imaging Institute. His interest lies in visualization and analysis of large data coming from application areas ranging from plasma physics to combustion. Recently he has focused on new ways to utilize in situ data analysis and visualization which often has him working directly on the science application infrastructure. \nTeasing out Ephemeral Data from HPC Applications for In Situ Visualization and Analysis\nIt is well known that as HPC applications have grown\, I/O has become a bottleneck\, which has required scientists to turn to in situ tools for data exploration. The focus of this exploration has typically been on simulation data. However\, applications also produce ephemeral data that is optionally written to disk for post hoc analysis\, but not otherwise saved or utilized by the application in subsequent time steps. One example of ephemeral data is runtime performance data. In this talk I will present the infrastructure implemented for efficiently collecting this and other data within the Uintah framework which was coupled to VisIt’s in situ toolkit for analysis and visualization. This collection and coupling allows performance data to be visualized using multiple domains giving insight previously not possible. As part this coupling\, we take advantage of VisIt’s in situ custom user interface to create a “simulation dashboard” that allows for in situ computational steering and visual debugging allowing for improvements in the development and simulation workflow. \nDr. Sanderson is being hosted by the Scientific Computing Student Club [SC2].  If you would like to meet with him during his visit\, please send an email to micde-events@umich.edu. Limited lunch will be provided. 
URL:https://micde.umich.edu/event/micde-seminar-allen-sanderson/
LOCATION:Johnson Rooms\, Lurie Engineering Center\, 3rd Floor LEC 3213ABC\, 1221 Beal Ave.\, Ann Arbor\, MI\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2019/12/Allen-Sanderson.png
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
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200124T130000
DTEND;TZID=America/Detroit:20200124T140000
DTSTAMP:20260608T181335
CREATED:20230905T171341Z
LAST-MODIFIED:20230905T171341Z
UID:10000312-1579870800-1579874400@micde.umich.edu
SUMMARY:MICDE Seminar: Andrew Wetzel\, Assistant Professor\, Physics\, University of California\, Davis
DESCRIPTION:Bio: Professor Wetzel is an assistant professor in the physics department and in the astrophysics and cosmology group at the University of California\, Davis. He is a theoretical/computational astrophysicist and cosmologist. Using the world’s most powerful supercomputers\, he generates cosmological simulations to model the formation of cosmic structures\, including galaxies and their stars. He uses these simulations as theoretical laboratories to develop and test models of galaxy formation\, stellar dynamics\, and the nature of dark matter\, with emphasis on our own Milky Way galaxy. \nSimulating the Milky Way\nThe Gaia satellite mission\, together with a multitude of ground-based observational surveys\, now measure 6-D phase-space coordinates and multi-species elemental abundances for hundreds of millions of stars across the Milky Way. This new era of galactic archeology and near-field cosmology demands a new generation of simulations that achieve high dynamic range to resolve scales of individual stellar populations within a cosmological context. I will describe the new Latte suite of massively parallelized cosmological zoom-in simulations\, run on the nation’s most powerful supercomputers\, that model the formation of Milky Way-like galaxies at parsec-scale resolution\, using the FIRE (Feedback in Realistic Environments) model for star formation and feedback. First I will discuss the formation of the Milky Way disk\, including resolving for the first time the dynamics and lifetimes of giant molecular clouds and stars clusters at z = 0. These simulations also self-consistently resolve the formation of satellite dwarf galaxies around each Milky Way-like host. These low-mass galaxies have presented significant challenges to the cold dark matter model\, but I will show progress in addressing the “missing satellites” and “too-big-to-fail” problems. Finally\, I will discuss synthetic Milky Way surveys that we have created from the Latte simulations\, which are publicly available\, to provide theoretical modeling insight for the era of Gaia. \nProf. Wetzel is being hosted by Prof. Gnedin (Astronomy).  If you would like to meet with him during his visit\, please send an email to micde-events@umich.edu. If you are an MICDE graduate student and would like to join Prof. Wetzel for lunch please RSVP by Thursday\, January 23. 
URL:https://micde.umich.edu/event/micde-seminar-andrew-wetzel-uc-davis/
LOCATION:411 West Hall (1085 S. University)\, 1085 S. University Ave\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2019/12/Andrew-Wetzel.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200131T153000
DTEND;TZID=America/Detroit:20200131T163000
DTSTAMP:20260608T181335
CREATED:20230905T171340Z
LAST-MODIFIED:20230905T171340Z
UID:10000331-1580484600-1580488200@micde.umich.edu
SUMMARY:MICDE Seminar: Amir Salaree\, Postdoctoral Fellow\, Earth and Environmental Sciences\, University of Michigan
DESCRIPTION:Due to unforeseen circumstances the originally scheduled talk by Professor Brandon Johnson has been cancelled and replaced with the following seminar. \nTheoretical and Computational Contributions to the Modeling of Global Tsunamis\nThe distribution of tsunami amplitudes in the open ocean is controlled by source mechanism as well as bathymetry geometry and resolution\, with the latter controlling far-field tsunami features. However\, large detailed bathymetry grids result in long computer simulation times for tsunamis. It is therefore of interest to investigate the amount of physical detail in bathymetric grids that control the most important features in tsunami amplitudes\, to assess what constitutes sufficient level for grids in numerical simulations. By decomposing the Pacific bathymetry using a spherical harmonics approach one can create “smoothed” versions of the original field. Using these simplified bathymetries to simulate tsunamis from potential ruptures around the Pacific\, we can see that for large megathrust events (M0=1029 dyn-cm)\, only a resolution of ~1000 km (equivalent to l=40)\, or ~1% surface smoothness of the Pacific is needed in order to reproduce the main components of the true distribution of tsunami amplitudes. This would result in simpler simulations\, and faster computations in the context of tsunami warning algorithms. \nIn a separate context\, an overview of tsunami studies and a report on a study of a meteotsunami are presented. These scenarios are evidence for the fact that tsunami studies are interdisciplinary fields of research that require coordinated efforts by investigators from various backgrounds. \nMICDE is co-hosting this seminar with the Earth and Environmental Sciences department. 
URL:https://micde.umich.edu/event/micde-seminar-brandon-johnson-purdue/
LOCATION:RM1528\, 1100 North University Building
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2020/01/Amir-Salaree.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200221T150000
DTEND;TZID=America/Detroit:20200221T160000
DTSTAMP:20260608T181335
CREATED:20230905T171342Z
LAST-MODIFIED:20230905T171342Z
UID:10000332-1582297200-1582300800@micde.umich.edu
SUMMARY:MICDE Seminar: Osman Basaran\, Professor\, Chemical Engineering\, Purdue University
DESCRIPTION:Bio: Professor Osman Basaran is a Burton and Kathryn Gedge Professor of Chemical Engineering at Purdue University. He received his undergraduate degree at Massachusetts Institute of Technology and a PhD from the University of Minnesota. Prof. Basaran’s research involves the use of a balanced approach based on computation\, theory\, and experiment to attack a number of fundamental issues that lie at the heart of such practical problems. \nHigh-accuracy simulation of free surface flows near finite-time pinch-off and coalescence singularities\nMotivated by applications such as ink jet printing\, drop-by-drop manufacturing\, sprays\, emulsions\, and chemical separations\, we study the dynamics of breakup and coalescence through high-accuracy simulation\, theory\, and experiment.  In this talk\, I will highlight our group’s work on accurately capturing the fluid dynamics that takes place in the vicinity of finite-time singularities. The free surface flow algorithms and solvers that we develop and use rely on a sharp interface representation of phase boundaries.  In the simulations\, we are able to analyze situations that involve disparate length scales that differ by up to seven orders of magnitude (commercial codes can handle about 2-3 orders and custom codes can capture at most 3-4 orders of magnitude disparity in length scales). The primary focus of the talk will be on simulations of the breakup of surfactant-covered filaments where I will pay special attention to the pinch-off singularity.  I will also summarize some of our recent work on the pre- and post-coalescence singularities that arise when two drops or bubbles are driven together and made to merge into one.  \nThis seminar is co-sponsored by the Applied & Interdisciplinary Mathematics program. Prof. Basaran is being hosted by Prof. Deegan (Physics). If you would like to meet with Prof. Basaran during his visit\, please send an email to micde-events@umich.edu. If you are an MICDE student or an AIM student and you’re interested in having lunch with Prof. Basaran during his visit\, please RSVP by Thursday\, February 20\, 2020.
URL:https://micde.umich.edu/event/micde-seminar-osman-basaran-purdue/
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/Osman-Basaran.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:20200228T150000
DTEND;TZID=America/Detroit:20200228T160000
DTSTAMP:20260608T181335
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:20200313T150000
DTEND;TZID=America/Detroit:20200313T160000
DTSTAMP:20260608T181335
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/
LOCATION:MI
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:20200313T150000
DTEND;TZID=America/Detroit:20200313T160000
DTSTAMP:20260608T181335
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/
LOCATION:MI
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:20200320T150000
DTEND;TZID=America/Detroit:20200320T160000
DTSTAMP:20260608T181335
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/
LOCATION:MI
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:20200326T160000
DTEND;TZID=America/Detroit:20200326T170000
DTSTAMP:20260608T181335
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/
LOCATION:MI
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:20200417T150000
DTEND;TZID=America/Detroit:20200417T163000
DTSTAMP:20260608T181335
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:20200602T150000
DTEND;TZID=America/Detroit:20200602T160000
DTSTAMP:20260608T181335
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:20200929T140000
DTEND;TZID=America/Detroit:20200929T150000
DTSTAMP:20260608T181335
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:20201020T113000
DTEND;TZID=America/Detroit:20201020T130000
DTSTAMP:20260608T181335
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:20201020T150000
DTEND;TZID=America/Detroit:20201020T160000
DTSTAMP:20260608T181335
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:20201112T110000
DTEND;TZID=America/Detroit:20201112T120000
DTSTAMP:20260608T181335
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:20201120T150000
DTEND;TZID=America/Detroit:20201120T160000
DTSTAMP:20260608T181335
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:20201203T150000
DTEND;TZID=America/Detroit:20201203T160000
DTSTAMP:20260608T181335
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:20210119T160000
DTEND;TZID=America/Detroit:20210119T170000
DTSTAMP:20260608T181335
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:20210126T150000
DTEND;TZID=America/Detroit:20210126T160000
DTSTAMP:20260608T181335
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:20210204T110000
DTEND;TZID=America/Detroit:20210204T120000
DTSTAMP:20260608T181335
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:20210209T160000
DTEND;TZID=America/Detroit:20210209T170000
DTSTAMP:20260608T181335
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:20210216T150000
DTEND;TZID=America/Detroit:20210216T160000
DTSTAMP:20260608T181335
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:20210301T130000
DTEND;TZID=America/Detroit:20210301T140000
DTSTAMP:20260608T181335
CREATED:20230905T171259Z
LAST-MODIFIED:20230905T171259Z
UID:10000450-1614603600-1614607200@micde.umich.edu
SUMMARY:MICDE Seminar: Santo Fortunato\, Director of the Indiana University Network Science Institute (IUNI)\, Professor\, School of Informatics\, Computing\, and Engineering (SICE)\, Indiana University at Bloomington
DESCRIPTION:About Dr. Fortunato: Santo Fortunato is the Director of the Indiana University Network Science Institute (IUNI) and a faculty at Luddy School of Informatics\, Computing and Engineering. Previously he was professor of complex systems at the Department of Computer Science of Aalto University\, Finland. Prof. Fortunato got his PhD in Theoretical Particle Physics at the University of Bielefeld In Germany. He then moved to the field of complex systems\, via a postdoctoral appointment at Luddy School of Informatics\, Computing and Engineering of Indiana University. His current focus areas are network science\, especially community detection in graphs\, computational social science\, science of science\, climate change. His research has been published in leading journals\, including Nature\, Science\, PNAS\, Physical Review Letters\, Reviews of Modern Physics\, Physics Reports and has collected over 33\,000 citations (Google Scholar). His review article Community detection in graphs (Physics Reports 486\, 75-174\, 2010) is one of the best known and most cited papers in network science. He received the Young Scientist Award for Socio- and Econophysics 2011\, a prize given by the German Physical Society\, for his outstanding contributions to the physics of social systems. He is the Founding Chair of the International Conference on Computational Social Science (IC2S2) and Chair of Networks 2021\, the first merger of the NetSci and the Sunbelt conferences\, possibly the largest ever event in network science. \nCOMMUNITY DETECTION IN NETWORKS: Complex systems typically display a modular structure\, as modules are easier to assemble than the individual units of the system\, and more resilient to failures. In the network representation of complex systems\, modules\, or communities\, appear as subgraphs whose nodes have an appreciably larger probability to get connected to each other than to other nodes of the network. In this talk I will discuss three main issues in this area. I will address the limits of the most popular class of clustering algorithms\, those based on the optimization of a global quality function\, like modularity maximization. Testing algorithms is probably the single most important issue of network community detection\, as it implicitly involves the concept of community\, which is ill-defined. I will discuss the importance of using realistic benchmark graphs with built-in community structure. Finally\, I will introduce an increasingly popular post-processing technique that allows to “average” the results of stochastic clustering algorithms\, improving their quality: consensus clustering. \n\nWatch the full webinar recording. \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. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-santo-fortunato-director-of-the-indiana-university-network-science-institute-iuni-professor-school-of-informatics-computing-and-engineering-sice-indiana-university-at-blooming/
LOCATION:Zoom Event\, MI\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2021/01/Santo-Fortunato.png
END:VEVENT
END:VCALENDAR