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DTSTART;TZID=America/Detroit:20191115T150000
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DTSTAMP:20260604T050047
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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
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20191106T150000
DTEND;TZID=America/Detroit:20191106T160000
DTSTAMP:20260604T050047
CREATED:20230905T171337Z
LAST-MODIFIED:20230905T171337Z
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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
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20191101T150000
DTEND;TZID=America/Detroit:20191101T160000
DTSTAMP:20260604T050047
CREATED:20230905T171337Z
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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
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20191017T113000
DTEND;TZID=America/Detroit:20191017T123000
DTSTAMP:20260604T050047
CREATED:20230905T171337Z
LAST-MODIFIED:20230905T171337Z
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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
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20191010T150000
DTEND;TZID=America/Detroit:20191010T160000
DTSTAMP:20260604T050047
CREATED:20230905T171405Z
LAST-MODIFIED:20230905T171405Z
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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
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190930T110000
DTEND;TZID=America/Detroit:20190930T120000
DTSTAMP:20260604T050047
CREATED:20230905T171405Z
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SUMMARY:MICDE Seminar: Jason MacLean\, Associate Professor\, Neurobiology\, University of Chicago
DESCRIPTION:Bio: Jason MacLean is an Associate Professor in the Department of Neurobiology and director of undergraduate studies in neuroscience at the University of Chicago.  His research aims to define how information is encoded in the brain by large groups of synaptically interconnected neurons using a range of analytical approaches. He complements this work by simulating and training spiking neuronal networks. Jason completed his Ph.D. at the University of Manitoba in Canada\, and worked at Cornell University and Columbia University before establishing his own group at the University of Chicago in 2008. He and his wife have two children and he no longer has time for hobbies. \nRecurrent interactions can explain the variance in single trial responses\nTo develop a complete description of sensory encoding\, it is necessary to account for trial-to-trial variability in cortical neurons. Using a generalized linear model with terms corresponding to the visual stimulus\, mouse running speed\, and experimentally measured neuronal correlations\, we modeled short term dynamics of L2/3 murine visual cortical neurons to evaluate the relative importance of each factor to neuronal variability within single trials. We find single trial predictions improve most when conditioning on the experimentally measured local correlations in comparison to predictions based on the stimulus or running speed. Specifically\, accurate predictions are driven by positively co-varying and synchronously active functional groups of neurons. Including functional groups in the model enhances decoding accuracy of sensory information compared to a model that assumes neuronal independence. Functional groups\, in encoding and decoding frameworks\, provide an operational definition of Hebbian assemblies in which local correlations largely explain neuronal responses on individual trials. \nProf. MacLean is being hosted by Prof. Watson (Psychiatry). 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 student and would like to join Prof. MacLean for lunch please RSVP by Saturday\, September 28th. 
URL:https://micde.umich.edu/event/fall2019-maclean-uchicago/
LOCATION:Weiser Hall\, Room 555\, 500 Church St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190925T150000
DTEND;TZID=America/Detroit:20190925T160000
DTSTAMP:20260604T050047
CREATED:20230905T171404Z
LAST-MODIFIED:20230905T171404Z
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SUMMARY:MICDE Seminar: H. Metin Aktulga\, Assistant Professor\, Computer Science and Engineering\, Michigan State University
DESCRIPTION:Bio: H. Metin Aktulga received his B.S. degree from Bilkent University in 2004\, M.S. and Ph.D. degrees from Purdue University in 2009 and 2010\, respectively; all in Computer Science. Before joining the Michigan State University (MSU) in 2014\, he was a postdoctoral researcher in the Computational Research Division at the Lawrence Berkeley Lab. He directs the Scalable Parallel Technologies and Algorithms (SParTA) Lab at MSU. Research in the SParTA Lab focuses on HPC and applications of HPC\, specifically on the design and development of algorithms\, numerical methods and software systems that can harness the full potential of state-of-the-art computing platforms to address challenging problems in large scale scientific computations and big-data analytics problems. Dr. Aktulga’s research is supported by NSF\, DOE\, AFRL\, NIH and the MSU Foundation. He is the recipient of the NSF CAREER award in 2019. \nTowards Fast\, Scalable and High Fidelity Reactive Molecular Dynamics Simulations\nReactive molecular dynamics (RMD) models bridge quantum-scale and classical MD approaches by explicitly modeling bond activity and redistribution of charges. As such they enable the study of important phenomena which otherwise is impractical using classical or quantum techniques. However\, RMD models have a significantly complex formulation\, making fast\, scalable and high fidelity RMD simulations extremely challenging to achieve. In this talk\, I will present our work towards addressing both the scalability and fidelity challenges. I will start by describing the parallel algorithms and numerical techniques that we developed for a fast implementation of the Reax Force Field (ReaxFF)\, which is used by hundreds of researchers worldwide. Particular emphasis will be on novel solvers we recently developed for the dynamic charge distribution problem that constitutes the most important scalability bottleneck in large RMD simulations. I will conclude the talk by outlining our efforts towards addressing the fidelity challenge\, i) through an automated force field framework for RMD models\, ii) by developing a novel hybrid ReaxFF/AMBER simulation software in the spirit of QM/MM techniques. \nProf. Aktulga is being hosted by the Glotzer Lab (Chemical Engineering). 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 Chemical Engineering graduate student\, and would like to join Prof. Aktulga for lunch\, please RSVP here by September 23rd.  \n 
URL:https://micde.umich.edu/event/fall2019-aktulga-msu/
LOCATION:1303 EECS\, 1301 Beal Ave\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190912T143000
DTEND;TZID=America/Detroit:20190912T153000
DTSTAMP:20260604T050047
CREATED:20230905T171404Z
LAST-MODIFIED:20230905T171404Z
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SUMMARY:MICDE Seminar: Ramanathan Vishnampet\, Senior Research Engineer\, ExxonMobil Upstream Integrated Solutions
DESCRIPTION:Bio: Ramanathan Vishnampet is a Computational Data Scientist at the Global Business Lines Analytics & Optimization group at ExxonMobil Upstream Integrated Solutions. He graduated with a Ph.D. in Theoretical and Applied Mechanics from the University of Illinois at Urbana-Champaign\, where his dissertation focused on an exact and consistent adjoint method for high-fidelity discretization of the compressible flow equations. Ramanathan started as a Senior Research Engineer at ExxonMobil in 2015\, where he worked in the Process Stratigraphy team\, an integrated team including Computational Scientists\, Geoscientists\, Seismic Interpreters\, and Stratigraphers. He helped develop a physics-based stratigraphic model for studying deepwater stratigraphy and showed the emergence of chaotic dynamics and self-organization that limit the ability of traditional model inversion techniques to be applied to the forward model. In his current team\, Ramanathan is working on a scheduling problem for ExxonMobil’s Unconventionals asset base using heuristics and discrete optimization. He is also leading his section’s efforts in adopting lean and agile software development practices\, cloud-based deployment using a service architecture\, and DevOps processes. Ramanathan’s hobbies include cooking\, traveling\, and spending time with his daughter. \nPrediction under chaos using a depth-averaged model of turbidity currents\nIn this talk\, I will demonstrate a forward stratigraphic model based on depth-averaged governing equations for the flow of submarine turbidity currents over an erodible bed. This model is being used with some success by the Process Stratigraphy team at ExxonMobil to generate stratigraphic models for deepwater environments of deposition. The mathematical model consists of a system of nonlinear hyperbolic PDEs\, with an additional so-called Exner equation for modeling the flow-bed sediment exchange and their bedload transport. The Exner equation plays a key role since a (slow time scale) change in the gradient of the bed influences the (fast time scale) momentum of the flow. The transport equations\, along with closure models for sediment transport\, TKE balance\, and water entrainment\, are solved using a first-order finite-volume method with a HLLC approximate Riemann solver and integrated using an explicit Euler scheme. The model shows the emergence of self-organized patterns in the deposits\, including the creation of bedforms\, channel formation\, and avulsions\, consistent with observations of modern systems and lab experiments. These occur even with uniform boundary conditions and symmetric initial conditions. The initial disturbances that trigger these mechanisms are ostensibly sourced by floating-point roundoff errors. An ensemble of simulations with slightly different initial conditions are used to analyze statistics on shapes of geomorphic elements and grain size distributions. The objective is to assess whether and under what conditions such a numerical model can be predictive and quantify the uncertainty in the results arising due to the irreducible chaos in the dynamical system. \nDr. Vishnampet is being hosted by Prof. Capecelatro (ME). If you would like to meet with him during his visit\, please send an email to micde-events@umich.edu.  
URL:https://micde.umich.edu/event/fall2019-vishnampet-exxonmobil/
LOCATION:Johnson Rooms\, Lurie Engineering Center\, 3rd Floor LEC 3213ABC\, 1221 Beal Ave.\, Ann Arbor\, MI\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190806T130000
DTEND;TZID=America/Detroit:20190806T150000
DTSTAMP:20260604T050047
CREATED:20230905T171403Z
LAST-MODIFIED:20230905T171403Z
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SUMMARY:Transitioning from Flux to Great Lakes
DESCRIPTION:Lecture w/ Q&A \n  \nNo Registration required. Drop-ins welcome. Thanks!
URL:https://micde.umich.edu/event/transitioning-from-flux-to-great-lakes-5/
LOCATION:Room 1450 – Institute for Social Research\, 426 Thompson Street\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,High Performance Computing,Info Session,Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190417T160000
DTEND;TZID=America/Detroit:20190417T170000
DTSTAMP:20260604T050047
CREATED:20230905T171400Z
LAST-MODIFIED:20230905T171400Z
UID:10000221-1555516800-1555520400@micde.umich.edu
SUMMARY:MICDE Seminar: Guy A. E. Vandenbosch\, Electrical Engineering\, KU Leuven
DESCRIPTION:Bio: Guy A. E. Vandenbosch is a Professor of Electrical Engineering at the Katholieke Universiteit Leuven in Leuven\, Belgium. He received the M.S. and Ph.D. degrees in Electrical Engineering from KU Leuven in 1985 and 1991\, respectively.\nHe was a research and teaching assistant from 1985 to 1991 with the Telecommunications and Microwaves section of the Katholieke Universiteit Leuven\, where he worked on the modeling of microstrip antennas with the integral equation technique. From 1991 to 1993\, he held a postdoctoral research position\, in 1993 he became a Lecturer\, and since 2005 he’s been a Full Professor at the same university. Guy Vandenbosch has taught or teaches courses on “Electromagnetic Waves”\, “Antennas”\, “Electromagnetic Compatibility”\, “Fundamentals of Communication and Information Theory”\, “Electrical Engineering\, Electronics\, and Electrical Energy”\, and ”Digital Steer- and Measuring Techniques in Physics”. \nProf. Vandenbosch’s research interests are in the area of electromagnetic theory\, computational electromagnetics\, planar antennas and circuits\, nano-electromagnetics\, EM radiation\, EMC\, and bio-electromagnetics. His work has been published in over 300 papers in international journals and has led to over 370 papers at international conferences. He was a member of the Management Committees‘ of the consecutive European COST actions on antennas between 1993 and 2017\, where he was leading the working group on modeling and software for antennas. \nOn a Boundary Integral Equation Approach Modeling the Interaction of Light with Nanostructured Metallic Objects\nComputational Electromagnetics (CEM) is the technology modeling the interaction of electromagnetic waves (EM waves) with physical objects and their surroundings. This technology has been demonstrated to be a key element in the design of\, e.g.\, modern antennas\, waveguiding/shaping devices\, etc..It has been playing a pivotal role in forging modern communication systems\, and therefore was\, is and will be greatly impacting peoples’ daily life. However\, despite of all these successes\, very recent experiments on the interaction of light (EM waves at optical frequencies) with deep-nanoscale metallic structures suggest the need of a paradigm shift in the classic CEM algorithms\, where a more refined material model is required. As the very first step in this direction\, we combine the dynamics of classical EM waves with the semi-classical hydrodynamic motion of free electrons in metals. The problem is formulated in the framework of Boundary Integral Equations (BIEs) and subsequently solved by the Method of Moments (MoM) algorithm. This research contributes to potentially bridging the computational gap between the classical macroscopic world and the quantum mechanical microscopic world\, and provides an essential tool for chemists and physicists to understand new physics in the nanoscopic world. \nProf. Vandenbosch is being hosted by Prof. Michielssen (Electrical Engineering). If you would like to meet with him during his visit\, please send an email to micde-events@umich.edu. If you are a student or postdoc and would like to join him for lunch on Thurs.\, April 18\, please RSVP here by April 16.
URL:https://micde.umich.edu/event/win2019-vandenbosch-kuleuven/
LOCATION:1008 EECS\, 1301 Beal Ave.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190410T080000
DTEND;TZID=America/Detroit:20190410T170000
DTSTAMP:20260604T050047
CREATED:20230905T171359Z
LAST-MODIFIED:20230905T171359Z
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SUMMARY:The 2019 MICDE Symposium
DESCRIPTION:[vc_row type=”in_container” full_screen_row_position=”middle” scene_position=”center” text_color=”dark” text_align=”left” overlay_strength=”0.3″ shape_divider_position=”bottom” bg_image_animation=”none”][vc_column column_padding=”no-extra-padding” column_padding_position=”all” background_color_opacity=”1″ background_hover_color_opacity=”1″ column_link_target=”_self” column_shadow=”none” column_border_radius=”none” width=”1/1″ tablet_width_inherit=”default” tablet_text_alignment=”default” phone_text_alignment=”default” column_border_width=”none” column_border_style=”solid” bg_image_animation=”none”][vc_column_text]The Michigan Institute for Computational Discovery and Engineering 2019 Symposium will feature eminent scientists from around the world and the U-M campus. \n\n\nSPEAKERS\n\n\n\n\n\n\n\n\n\n\nMarsha Berger\nProfessor\, Computer Science and Mathematics\nNew York University Courant Institute of Mathematical Sciences \n\nMarisa Eisenberg\nAssociate Professor\, Epidemiology and Mathematics\nUniversity of Michigan \n\nCarla Gomes\nProfessor and Director\, Institute for Computational Sustainability\nCornell University \n\nJan Hesthaven\nDean\, School of Basic Sciences\nEPFL\, Switzerland \n\nNecmiye Ozay\nAssistant Professor\, Electrical Engineering and Computer Science\nUniversity of Michigan \n\nStephen Wolfram\nFounder and CEO\, Wolfram Research\nCreator of Mathematica \n\n\n\n\n\n\n\nA poster competition will be held\, open to post-docs and graduate students. \nMore information will be posted here as it becomes available. Also see micde.umich.edu/symposium19[/vc_column_text][/vc_column][/vc_row]
URL:https://micde.umich.edu/event/the-2019-micde-symposium/
LOCATION:Michigan League\, 911 N. University\, Ann Arbor\, MI\, 48104\, United States
CATEGORIES:Featured Events,Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190404T120000
DTEND;TZID=America/Detroit:20190404T130000
DTSTAMP:20260604T050047
CREATED:20230905T171359Z
LAST-MODIFIED:20230905T171359Z
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SUMMARY:MICDE Seminar: Prith Banerjee\, Chief Technology Officer\, ANSYS\, Inc.
DESCRIPTION:Bio: Prith Banerjee is the Chief Technology Officer of ANSYS where he is responsible for leading the evolution of ANSYS’ Technology strategy and champion the company’s next phase of innovation and growth. He also serves on the Board of Directors of Cray\, Inc. and Cubic Corporation. Previously he used to be Senior Client Partner at Korn Ferry where he was responsible for IOT and Digital Transformation in the Global Industrial Practice. Formerly\, he was Executive Vice President\, Chief Technology Officer of Schneider Electric. Previously\, he was Managing Director of Global Technology Research and Development at Accenture. Formerly\, he was Chief Technology Officer and Executive Vice President of ABB. Earlier\, he was Senior Vice President of Research at HP and Director of HP Labs. Formerly\, he was Dean of the College of Engineering at the University of Illinois at Chicago. Formerly\, he was the Walter P. Murphy Professor and Chairman of Electrical and Computer Engineering at Northwestern University. Prior to that\, he was Professor of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign. In 2000\, he founded AccelChip\, a developer of products for electronic design automation\, which was acquired by Xilinx Inc. in 2006. During 2005-2011\, he was Founder\, Chairman and Chief Scientist of BINACHIP Inc.\, a developer of products in electronic design automation. He was listed in the FastCompany list of 100 top business leaders in 2009. He is a Fellow of the AAAS\, ACM and IEEE\, and a recipient of the 1996 ASEE Terman Award and the 1987 NSF Presidential Young Investigator Award. He received a B.Tech. in electronics engineering from the Indian Institute of Technology\, Kharagpur\, and an M.S. and Ph.D. in electrical engineering from the University of Illinois\, Urbana. \nFUTURE OF SIMULATION-BASED PRODUCT INNOVATION IN THE DIGITAL WORLD\nDigital transformation refers to the use of digital technologies such as cloud\, IOT\, AI/ML\, to transform the way business is executed. Digital transformation is impacting every industry – automotive\, agriculture\, logistics\, healthcare and manufacturing. In this talk we will discuss how Digital Transformation is disrupting the manufacturing industry. In the past\, engineered products were designed with mechanical and electrical CAD tools\, simulated and validated for correctness with CAE tools\, prototypes were fabricated and tested\, and products were then manufactured at scale in factories. This process required long product cycles often requiring years to build a new product. Today\, one can use unlimited computing and storage available from the cloud to do generative design to explore 10\,000 design choices in near real-time\, verify these products accurately through simulation (eliminating the need to build physical prototypes) and manufacture the products using additive manufacturing and factory automation (Industrie 4.0). In the past\, simulation tools were used to model specific physics such as mechanical structures\, or fluid dynamics\, or electromagnetic interactions by solving second order partial differential equations using numerical methods. Today the simulation tools are being used to solve multi-physics problems (fluid-structure-electromagnetics interactions) at scale using the most complex solvers. These products once built are connected using IOT so that manufacturers have 24/7 connectivity to all these products\, and can monitor how customers are using these product; this helps the manufacturers design future generations of products even faster. The connectivity also allows them to monitor the products for failures using predictive analytics\, and service these products remotely. In this talk I will discuss how the ANSYS Pervasive Simulation Platform allows hardware and software developers to work together in all phases of a product development lifecycle including Ideation\, Design Manufacturing\, and Operations. Simulation tools are increasingly being used in the ideation phase by designers to get real-time simulation of the parts as soon as they are being conceptualized. This has resulted in shorter\, agile product cycles even for hardware products allowing innovative products to be designed and produced in months and days. Companies are increasingly using model-based systems engineering concepts to take high level requirements of products\, and manage the complexity of product design using concepts of Digital Threads\, Digital Twins\, and Digital Continuity. We will touch upon some future directions of simulation-based product innovation around AI/Machine Learning\, Multi-physics Platforms\, Hyperscale Simulation\, and the convergence of the Digital and Physical worlds using IOT and Augmented Reality/Virtual Reality.
URL:https://micde.umich.edu/event/prith-banerjee-ansys/
LOCATION:1005 EECS\, 1301 Beal Ave\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190314T150000
DTEND;TZID=America/Detroit:20190314T160000
DTSTAMP:20260604T050047
CREATED:20230905T171358Z
LAST-MODIFIED:20230905T171358Z
UID:10000154-1552575600-1552579200@micde.umich.edu
SUMMARY:MICDE Seminar: Narayana R. Aluru\, Professor\, Department of Mechanical Science and Engineering\, Beckman Institute for Advanced Science and Technology\, University of Illinois at Urbana-Champaign
DESCRIPTION:Bio: Professor Aluru studies problems at the crossroads of mechanical engineering\, electrical engineering\, materials science and chemical engineering. His work in the area of microelectromechanical systems (MEMS) and nanoelectromechanical systems (NEMS) revealed previously unknown nonlinear dynamic phenomena\, such as complex oscillations\, period doubling bifurcation to chaos\, and U-sequence. These insights led him to perform fundamental studies on thermoelastic damping in MEMS and to develop a new model to predict thermoelastic damping for complex nonlinear oscillations encountered in NEMS. \nIn another effort\, he developed the first bio-MEMS and microfluidics models for the analysis and design of lab-on-a-chip applications\, as well as mathematical models for pH- and electric field-responsive hydrogels-materials with potential applications in small-scale sensing and actuation. \nProfessor Aluru also studies the unique physics that occur at the nanometer level. He discovered several new physical phenomena through nanofluidics research\, including charge inversion\, flow reversal\, anomalously immobilized water\, asymmetric dependence of fluid and ion transport on surface charge\, and enhanced conductivity in nanopores. His recent investigations of surface diffusion demonstrated that liquid molecules move as much as 30 times faster over a solid surface when that surfaced is only partially covered by such molecules\, and that larger molecules move faster on a partially covered surface than shorter ones do. His other work in nanofluidics includes the multiscale modeling of the transport of water and other ions through membranes\, studying the function of biological channels in the membranes of living cells\, investigating the use of carbon nanotubes to filter pathogens and other toxins out of water\, and exploring the use of carbon and boron nanotubes to speed the removal of salt from water during reverse osmosis. \nCOMPUTATIONAL NANOSCALE HYDRODYNAMICS\nMany applications in biology\, engineering and science rely on efficient hydrodynamic transport through nanometer scale pores and channels. For example\, channels and pores in cellular membranes regulate the functionality of the cell by selectively and efficiently exchanging water and ions between extra and intra cellular environments. Selective pores in ultrathin membranes have been shown to be highly efficient for water desalination and power generation. Classical theories often fail to describe fluid physics at nanometer scale. For example\, density layering\, size dependent fluid properties\, restricted translational and rotational motions\, charge inversion\, flow reversal and several other important phenomena have been observed at nanometer scale. The focus of this talk is to develop efficient theories and computational approaches to accurately describe fluid physics at nanometer scales. First\, we will introduce an empirical potential-based quasi-continuum theory (EQT) to accurately predict the structure of confined fluids. We show that the density layering from EQT matches well with molecular dynamics (MD) and EQT is many orders of magnitude faster compared to MD. Next\, we show that the EQT framework can be combined with the generalized Langevin theory to compute diffusion of confined fluids and with the classical Navier-Stokes equations to compute the transport of confined fluids. We will show several examples to demonstrate the accuracy and efficiency of the quasi-continuum theory for confined fluids. \nProf. Aluru is being hosted Professors Krishna Garikipati and Eric Michielssen. If you would like to meet Prof. Aluru\, please send an email to micde-events@umich.edu. If you are an MICDE student or fellow\, or a post-doc\, and would like to join Prof. Aluru for lunch\, please RSVP here.
URL:https://micde.umich.edu/event/micde-seminar-narayana-aluru-department-of-mechanical-engineering-uicuc/
LOCATION:1005 EECS\, 1301 Beal Ave\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190218T150000
DTEND;TZID=America/Detroit:20190218T160000
DTSTAMP:20260604T050047
CREATED:20230905T171358Z
LAST-MODIFIED:20230905T171358Z
UID:10000207-1550502000-1550505600@micde.umich.edu
SUMMARY:MICDE Seminar: Jim Haxby\, Evans Family Distinguished Professor; Director\, Center for Cognitive Neuroscience\, Dartmouth College
DESCRIPTION:Bio1: James V. Haxby is a professor in the Department of Psychological and Brain Sciences at Dartmouth College and the Director for the Dartmouth Center for Cognitive Neuroscience. He is best known for his work on face perception and applications of machine learning in functional neuroimaging. Haxby received a BA from Carleton College in 1973 and completed a Fulbright Scholarship at the University of Bonn in 1974. He obtained a PhD in clinical psychology at the University of Minnesota in 1981. After receiving his PhD\, Haxby held several clinical psychology positions at the Minneapolis VA Medical Center. Starting in 1982\, Haxby began a two-decade tenure at the National Institutes of Health\, working as a research psychologist at the National Institute on Aging and later as chief of the Section on Functional Brain Imaging at the National Institute of Mental Health. In 2002\, Haxby began a professorship in the Department of Psychology at Princeton University\, and in 2008 became the Evans Family Distinguished Professor of Psychological and Brain Sciences at Dartmouth College. \nHaxby’s scientific contributions span several topics in cognitive neuroscience. He has published numerous papers using functional neuroimaging to investigate the cortical organization underlying visual perception and semantic memory.He has also proposed an influential model of face perception where certain brain areas process invariant face properties such identity\, while others process dynamic features critical for social interaction\, such as emotional expressions and eye gaze. Haxby has played a critical role in introducing machine learning methods to functional magnetic resonance imaging (fMRI) data analysis. This approach was popularized by a paper demonstrating that neural representations of faces and object categories are encoded in a distributed fashion in human ventral temporal cortex\, a position that is typically contrasted with more modular accounts of the functional neuroanatomy of face processing. \n[1] https://en.wikipedia.org/wiki/James_V._Haxby \nBRIDGING THE DIVIDE: FOSTERING INTERDISCIPLINARY COLLABORATIVE RESEARCH IN COMPUTATIONAL COGNITIVE NEUROSCIENCE\nComputational cognitive neuroscience is a burgeoning field. Sensitive imaging methods can now measure changing patterns of brain activity noninvasively producing massive\, rich datasets. With open neuroscience\, vast amounts of functional brain imaging data are publicly available. Advances in computational methods for analyzing these data and modeling the underlying cognitive processes have produced a host of sophisticated algorithms that produce surprising new insights\, and these algorithms are available in extensive repositories of open source code. Building the interdisciplinary community for this type of collaborative research\, however\, presents challenges. Taking advantage of these resources requires integration of knowledge of cognitive neuroscience to direct projects to important questions and knowledge of rapidly evolving computational approaches that can tackle these questions in innovative ways. Building an interdisciplinary community will involve developing both productive interdisciplinary collaborative teams and a new breed of “bilingual” computational cognitive neuroscientist. \nProf. Haxby is being hosted my MICDE and the Michigan Neuroimaging Initiative. If you would like to meet Prof. Haxby\, please send an email to micde-events@umich.edu. If you are an MICDE\, MIDAS or Neuroscience student or postdoc and would like to join him for lunch\, please RSVP here (space is limited\, first-come\, first-serve)
URL:https://micde.umich.edu/event/micde-seminar-jim-haxby-evans-family-distinguished-professor-director-center-for-cognitive-neuroscience-dartmouth-college/
LOCATION:1017 H. H. Dow\, 2300 Hayward St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190215T130000
DTEND;TZID=America/Detroit:20190215T140000
DTSTAMP:20260604T050047
CREATED:20230905T171358Z
LAST-MODIFIED:20230905T171358Z
UID:10000205-1550235600-1550239200@micde.umich.edu
SUMMARY:MICDE Seminar: Rhonda Dzakpasu\, Associate Professor\, Department of Physics\, Georgetown University
DESCRIPTION:Bio: Rhonda Dzakpasu received a B.S. in Computer Science from The City College of New York. After working as a research assistant in a semiconductor laboratory\, she entered the PhD program at the University of Michigan where she completed a PhD in experimental optical physics. Her thesis work resulted in the development of an optical technique that images dynamically scattered light fluctuation decay rates.  She remained at the University of Michigan for her postdoctoral training where she performed computational modeling to study how architecture influences the dynamics within networks of coupled non-linear oscillators. As part of her postdoctoral training\, she also participated in two intensive neuroscience summer courses at the Marine Biological Laboratory (MBL) in Woods Hole\, MA: SPINES and Neurobiology. Prof. Dzakpasu joined the faculty in the Department of Physics as well as the Department of Pharmacology and Physiology at Georgetown University in 2008. Her current research incorporates experimental in vitro as well as computational techniques to probe the dynamical patterns that arise from the interactions within networks of neurons. \nWhat can we learn from neurochemical and cellular perturbations of in vitro neuronal network dynamics?\nProbing neural systems is essential to understanding the circuitry that underlies complex neuronal dynamics. Tools such as pharmacological assays are widely employed to assess differences between healthy and pathological states of a network and to elucidate biochemical mechanisms of a variety of cognitive processes. Manipulating the cellular composition of neural systems can also provide insights into the basic interactions between the constituent partners within the neural circuit.\nI will discuss results from two studies. In the first study\, we use neuromodulation to perturb the excitatory/inhibitory balance within a network of hippocampal neurons using pharmacological agents. Neuromodulation impacts oscillatory activity within cortical and hippocampal circuits and these oscillations have been shown to be important for cognitive processes such as working memory and attention. The oscillatory states are indicative of information transmission within the neural circuit and to examine changes in information transmission\, we perform extracellular recordings of action potentials from cultured hippocampal neuronal networks using an array of microelectrodes. We show a time-dependent effect on bursting dynamics after application of one of these agents and will discuss two possible mechanisms that may be involved.\nIn the second study\, I will present results from a new tissue co-culture system designed to investigate the network effects due to APOE\, the strongest genetic risk factor for Alzheimer’s disease. While the pathogenesis of Alzheimer’s is not well understood\, neural seizure-like activity has been shown to influence disease progression. Recent research suggests a link between Alzheimer’s disease and seizure-like brain activity. However\, little is known about how APOE affects activity across networks of neurons. I will discuss how APOE genotype impacts spiking dynamics of developing in vitro neuronal networks and its impact on the basic biophysical properties of the extracellular network voltage. \nProf. Dzakpasu is being hosted by Prof. Zochowski (Physics & Biophysics). 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\, or a Physics graduate student and would like to join Prof. Dzakpasu for lunch\, please sign up here.
URL:https://micde.umich.edu/event/micde-seminar-rhonda-dzakpasu-associate-professor-department-of-physics-georgetown-university/
LOCATION:411 West Hall (1085 S. University)\, 1085 S. University Ave\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190208T150000
DTEND;TZID=America/Detroit:20190208T160000
DTSTAMP:20260604T050047
CREATED:20230905T171357Z
LAST-MODIFIED:20230905T171357Z
UID:10000206-1549638000-1549641600@micde.umich.edu
SUMMARY:MICDE Seminar: David Nordsletten\, Associate Professor\, Department of Biomedical Engineering and Cardiac Surgery\, U-M
DESCRIPTION:Bio: Dr. Nordsletten joined the University of Michigan in January 2019 as an Associate Professor\, is a Reader in cardiovascular biomechanics at King’s College London\, and is the recipient of the EPSRC HTCA leadership fellowship. His research focuses on the novel application of biomechanics integrated with magnetic resonance imaging (MRI) for the advancement of human cardiovascular health. This broad focus encompasses a range of projects spanning from numerical methods development through to direct analysis of medical imaging data for diagnostics in cardiovascular disease. \nTRANSLATIONAL CARDIOVASCULAR BIOMECHANICS AND MAGNETIC RESONANCE IMAGING\nThe application of biomechanics in the heart and cardiovascular system has presented many opportunities to provide unique insights into physiology as well as potential tools for translation to clinical medicine. Key to this analysis is the merger with imaging and experimental tissue mechanics\, providing a core underpinning for studying the heart and cardiovascular system. In this presentation\, I will present recent work in my team exploring a variety of ways in which imaging\, biomechanics and modelling can be leveraged to better understand tissues and blood flow in health and disease.
URL:https://micde.umich.edu/event/micde-seminar-david-nordsletten-associate-professor-department-of-biomedical-engineering-and-cardiac-surgery-u-m/
LOCATION:NCRC Building 10 Research Auditorium\, 2800 Plymouth Rd\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2019/01/David-Nordsletten.png
GEO:42.3016367;-83.7054664
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=NCRC Building 10 Research Auditorium 2800 Plymouth Rd Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=2800 Plymouth Rd:geo:-83.7054664,42.3016367
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190207T120000
DTEND;TZID=America/Detroit:20190207T130000
DTSTAMP:20260604T050047
CREATED:20230905T171357Z
LAST-MODIFIED:20230905T171357Z
UID:10000129-1549540800-1549544400@micde.umich.edu
SUMMARY:MICDE 2019 Catalyst Grants Informational Session
DESCRIPTION:MICDE seeks proposals for innovative research projects in computational science that combine elements of mathematics\, computer science\, and cyberinfrastructure. Of interest is innovative computational research in any emerging area\, including but not limited to  \n\nComputational science approaches\, algorithms\, frameworks\, etc.\nEmerging paradigms in computing (exascale computing\, quantum computing\, FPGA computing\, etc.)\nApplications in emerging areas (neuroscience\, ecology\, evolutionary biology\, human-made complex systems\, mobility etc.)\nExtensions of traditional computational sciences to complex decision making (reinforcement learning\, transfer learning\, neuromorphic computing\, etc.)\nArtificial Intelligence informing and informed by science\n\nGeneric big data problems that do not fundamentally advance computational science algorithms are not suitable for MICDE Catalyst Grants. Priority will be given to high-impact projects with potential to eventually attract external funding. MICDE expects to fund 3-4 one-year projects at up to $100\,000 each. \nIn this informational session\, MICDE officials will clarify the program’s intent\, answer questions and facilitate team formation among attendees. \nRSVP is appreciated\, but not required. Lunch will be provided. \nThe session will be broadcasted via this bluejeans link. For more information go to micde.umich.edu/catalyst/
URL:https://micde.umich.edu/event/micde-2019-catalyst-grants-info-session/
LOCATION:Weiser Hall\, Room 747\, 500 Church St\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,Info Session
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190201T110000
DTEND;TZID=America/Detroit:20190201T120000
DTSTAMP:20260604T050047
CREATED:20230905T171423Z
LAST-MODIFIED:20230905T171423Z
UID:10000176-1549018800-1549022400@micde.umich.edu
SUMMARY:MICDE Seminar: Amir Ali Ahmadi\, Assistant Professor\, Operations Research and Financial Engineering\, Princeton University
DESCRIPTION:Bio: Amir Ali Ahmadi is an Assistant Professor at the Department of Operations Research and Financial Engineering at Princeton University and an Associated Faculty member of the Program in Applied and Computational Mathematics\, the Department of Computer Science\, the Department of Mechanical and Aerospace Engineering\, and the Center for Statistics and Machine Learning. Amir Ali received his PhD in EECS from MIT and was a Goldstine Fellow at the IBM Watson Research Center prior to joining Princeton. His research interests are in optimization theory\, computational aspects of dynamics and control\, and algorithms and complexity. Amir Ali’s distinctions include the Sloan Fellowship in Computer Science\, a MURI award from the AFOSR\, the NSF CAREER Award\, the AFOSR Young Investigator Award\, the DARPA Faculty Award\, the Google Faculty Award\, the Howard B. Wentz Junior Faculty Award as well as the Innovation Award of Princeton University\, the Goldstine Fellowship of IBM Research\, and the Oberwolfach Fellowship of the NSF. His undergraduate course at Princeton (ORF 363\, “Computing and Optimization’’) has received the 2017 Excellence in Teaching of Operations Research Award of the Institute for Industrial and Systems Engineers and the 2017 Phi Beta Kappa Award for Excellence in Undergraduate Teaching at Princeton University. Amir Ali is also the recipient of a number of best-paper awards\, including the INFORMS Optimization Society’s Young Researchers Prize\, the INFORMS Computing Society Prize (for best series of papers at the interface of operations research and computer science)\, the Best Conference Paper Award of the IEEE International Conference on Robotics and Automation\, and the prize for one of two most outstanding papers published in the SIAM Journal on Control and Optimization in 2013-2015. \nPOLYNOMIAL OPTIMIZATION AND DYNAMICAL SYSTEMS\nIn recent years\, there has been a surge of exciting research activity at the interface of optimization (in particular polynomial\, semidefinite\, and sum of squares optimization) and the theory of dynamical systems. In this talk\, we focus on two of our current research directions that are at this interface. In part (i)\, we propose more scalable alternatives to sum of squares optimization and show how they impact verification problems in control and robotics\, as well as some classic questions in polynomial optimization and statistics. Our new algorithms do not rely on semidefinite programming\, but instead use linear programming\, or second-order cone programming\, or are altogether free of optimization. In particular\, we present the first Positivstellensatz that certifies infeasibility of a set of polynomial inequalities simply by multiplying certain fixed polynomials together and checking nonnegativity of the coefficients of the resulting product.\nIn part (ii)\, we introduce a new class of optimization problems whose constraints are imposed by trajectories of a dynamical system. As a concrete example\, we consider the problem of optimizing a linear function over the set of initial conditions that forever remain inside a given polyhedron under the action of a linear\, or a switched linear\, dynamical system. We present a hierarchy of linear and semidefinite programs that respectively lower and upper bound the optimal value of such problems to arbitrary accuracy. \nThis seminar is co-sponsored by the department of Industrial and Operations Engineering. Prof. Ahmadi is being hosted by Prof. Shen (IOE). If you would like to meet with him during his visit\, please send an email to micde-events@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-amir-ali-ahmadi-assistant-professor-operations-research-and-financial-engineering-princeton-university/
LOCATION:2717 IOE\, 1205 BEAL AVE\, ANN ARBOR\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190118T150000
DTEND;TZID=America/Detroit:20190118T160000
DTSTAMP:20260604T050047
CREATED:20230905T171422Z
LAST-MODIFIED:20230905T171422Z
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SUMMARY:MICDE Seminar: Mattia Gazzola\, Department of Mechanical Science and Engineering\, University of Illinois at Urbana-Champaign
DESCRIPTION:Bio: Mattia Gazzola is an Assistant Professor in the department of Mechanical and Science Engineering at the University of Illinois\, Urbana-Champaign. Originally from Galliate\, Italy\, he obtained his B. Sc. in Energy Engineering and M. Sc. in Nuclear Engineering from the Politecnico di Milano. He then was granted a PhD. in Mechanical Engineering from ETH Zurich where he worked with Prof. Petros Koumoutsakos specializing in simulation\, optimization and learning of artificial swimmers. His research interests include locomotion in fluids\, where he combines theory\, numerical simulations and AI to advance our understanding of the physical mechanisms involved. He is also interested in creating artificial animals – or cyborgs – to link neuro-dynamics\, mechanics and complex controllable gaits-coupling sensory information to motor coordination and movement that leads to behavior. His research group develops numerical algorithms that allow the integration of AI with large scale simulations. \nMODELING\, SIMULATION AND CONTROL OF COMPLEX MUSCULOSKELETAL ARCHITECTURES\nWe introduce a modeling approach based on assemblies of Cosserat rods for the simulation and characterization of arbitrary muscoloskeletal architectures. The obtained solver is coupled to evolutionary optimization techniques for the rational design of soft artificial creatures characterized by different scales and operating across environments. A control approach for these distributed mechanical systems is outlined and demonstrated in simple settings. Applications range from slithering\, swimming and flying biolocomotion strategies to bio-hybrid systems. \nThis is a joint seminar with the Applied and Interdisciplinary Mathematics seminar series. Prof. Gazzola is being hosted by Prof. Alben (Mathematics). If you would like to meet with him during his visit\, please send an email to micde-events@umich.edu.
URL:https://micde.umich.edu/event/micde-seminar-mattia-gazzola-department-of-mechanical-science-and-engineering-uicuc/
LOCATION:1084 East Hall\, 530 Church St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190111T150000
DTEND;TZID=America/Detroit:20190111T160000
DTSTAMP:20260604T050047
CREATED:20230905T171422Z
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SUMMARY:MICDE Seminar: Yuri Bazilevs\, School of Engineering\, Brown University
DESCRIPTION:Bio: Yuri Bazilevs is the E. Paul Sorensen Chair in the School of Engineering at Brown University. He was previously a Professor and Vice Chair in the Structural Engineering Department at the University of California\, San Diego. Yuri is the original developer of Isogeometric Analysis (IGA)\, a new computational methodology that aims to integrate engineering design (CAD) and simulation (FEM). For his research contributions Yuri received a number of awards and honors\, including the 2018 ASCE Walter L. Huber Research Prize. He is included in the 2014-2018 lists of Highly Cited Researchers\, both in the Engineering and Computer Science categories. \nISOGEOMETRIC METHODS FOR SOLIDS\, STRUCTURES\, AND FLUID-STRUCTURE INTERACTION: FROM EARLY RESULTS TO RECENT DEVELOPMENTS\nThis presentation is focused on Isogeometric Analysis (IGA) with applications to solids and structures\, starting with early developments and results\, and transitioning to more recent work. Novel IGA-based thin-shell formulations are discussed\, and applications to progressive damage modeling in composite laminates due to low-velocity impact and their residual-strength prediction are shown. Fluid–structure interaction (FSI) employing IGA is also discussed\, and a novel framework for air-blast-structure interaction (ABSI) based on an immersed approach coupling IGA and RKPM-based Meshfree methods is presented and verified on a set of challenging examples. The presentation is infused with examples that highlight effective uses of IGA in advanced engineering applications. \nProf. Bazilevs is being hosted by Prof. Garikipati (Mechanical Engineering). If you would like to meet him during his visit please send an email to micde-events@umich.edu. If you are an MICDE or ME student and would like to join Prof. Bazilevs for lunch please RVSP here by Wednesday\, January 9.
URL:https://micde.umich.edu/event/micde-seminar-yuri-bazilev-school-of-engineering-brown-university/
LOCATION:2540 G.G. Brown (2350 Hayward St.)\, 2300 Hayward St\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20181212T160000
DTEND;TZID=America/Detroit:20181212T170000
DTSTAMP:20260604T050047
CREATED:20230905T171422Z
LAST-MODIFIED:20230905T171422Z
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SUMMARY:MICDE Seminar: Aaron Frank\, Chemistry and Biophysics\, University of Michigan
DESCRIPTION:Bio: Aaron Frank is originally from Grenada\, a small island in the Caribbean. After moving to the US in 2001\, Aaron received his BA in chemistry from Brooklyn College in 2006\, where he carried out research in the groups of Professors Charlene Forest\, Shaneen Singh\, and Alexander Greer. He then moved to Michigan to attend graduate school at the University of Michigan and then\, with his Ph.D advisor Professor Ioan Andricioaei\, moved to UC Irvine in 2008. Aaron received his Ph.D in chemistry in 2011. Following a 2 year stint at Nymirum Inc. — a small biotech company in Ann Arbor founded by a close collaborator\, Professor Hashimi Al-Hashimi — he returned to the University of Michigan as a Presidential Postdoctoral Fellow where he was mentored by Professor Charles L. Brooks\, III. Aaron is now an Assistant Professor at the University of Michigan in the Chemistry Department and the Biophysics Department. \nDATA SCIENCE AT THE INTERFACE OF BIOLOGY\, CHEMISTRY\, AND PHYSICS\nIn this talk\, I will describe examples of how my research group uses data science tools to tackle research problems that fall at the interface between Biology\, Chemistry\, and Physics. First\, I will describe ongoing research focused on mapping the structure-landscape of functional ribonucleic acids (or RNAs). In this project\, we combined machine learning and secondary structure modeling tools to predict the structure of RNAs conditioned on available NMR chemical shift data. This method now enables us to model individual conformational states\, including previously invisible states of an RNA\, based on its sequence and available chemical shift data. Second\, I will describe ongoing research centered around decoding structure-kinetic relationships (SKRs) in sparse datasets. There is now immense interest in developing drugs that exhibit elevated residence times on their target. In this project\, we used machine learning to encapsulate SKRs for CDK2\, a prominent cancer target\, from a dataset containing only fourteen (14) samples. I will describe our efforts to build and test CDK2-specific SKR models that take as input\, the atomic structure of receptor-ligand complexes and output estimates of their residence times. Additionally\, I will describe proof-of-concept studies that demonstrate the utility of our CDK2-specific SKR models as tools to help efficiently explore chemical space in search of novel chemical scaffolds that are enriched with high-residence time and potent inhibitors of CDK2.
URL:https://micde.umich.edu/event/micde-seminar-aaron-frank-chemistry-and-biophysics-university-of-michigan/
LOCATION:1210 Chemistry & Willard H Dow Laboratory\, 930 University Ave.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
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GEO:42.2780183;-83.7370191
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20181203T160000
DTEND;TZID=America/Detroit:20181203T170000
DTSTAMP:20260604T050047
CREATED:20230905T171421Z
LAST-MODIFIED:20230905T171421Z
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SUMMARY:MICDE Seminar: Youssef Marzouk\, Department of Aeronautics and Astronautics\, MIT
DESCRIPTION:Bio: Youssef Marzouk is an associate professor in the Department of Aeronautics and Astronautics at MIT\, and co-director of the MIT Center for Computational Engineering. He is also director of MIT’s Aerospace Computational Design Laboratory. \nHis research interests lie at the intersection of physical modeling with statistical inference and computation. In particular\, he develops methodologies for uncertainty quantification\, inverse problems\, large-scale Bayesian computation\, and optimal experimental design in complex physical systems. His methodological work is motivated by a wide variety of engineering\, environmental\, and geophysics applications. \nHe received his SB\, SM\, and PhD degrees from MIT and spent several years at Sandia National Laboratories before joining the MIT faculty in 2009. He is a recipient of the Hertz Foundation Doctoral Thesis Prize (2004)\, the Sandia Laboratories Truman Fellowship (2004-2007)\, the US Department of Energy Early Career Research Award (2010)\, and the Junior Bose Award for Teaching Excellence from the MIT School of Engineering (2012). He is an Associate Fellow of the AIAA and currently serves on the editorial boards of the SIAM Journal on Scientific Computing\, Advances in Computational Mathematics\, and the SIAM/ASA Journal on Uncertainty Quantification. He is also an avid coffee drinker and classical pianist. \nA TOUR OF TRANSPORT METHODS FOR BAYESIAN COMPUTATION\nBayesian inference provides a natural framework for quantifying uncertainty in parameter estimates and model predictions\, and for combining heterogeneous sources of information. Characterizing the results of Bayesian inference—by simulating from the posterior distribution—often proceeds via Markov chain Monte Carlo or sequential Monte Carlo sampling\, but remains computationally challenging for complex posteriors and large-scale models. \nThis talk will describe a broad framework for using measure transport in Bayesian computation. This framework seeks deterministic couplings of the posterior measure with a tractable “reference” measure (e.g.\, a standard Gaussian). Such couplings are induced by transport maps\, and enable direct simulation from the desired measure simply by evaluating the transport map at samples from the reference. Approximate transports can also be used to “precondition” and accelerate standard Monte Carlo schemes. Within this framework\, one can describe many useful notions of low-dimensional structure associated with inference: for instance\, sparse or decomposable transports underpin modeling and computation with non-Gaussian Markov random fields\, and low-rank transports arise frequently in inverse problems. \nWe will then describe recent work specializing transport maps to the problem of nonlinear filtering in high-dimensional state-space models. The idea is to transform a forecast ensemble into samples from the current filtering distribution via a sequence of nonlinear transport maps\, computed via convex optimization. Construction of the maps is regularized by leveraging potential structure in the filtering problem—e.g.\, decay of correlations\, approximate conditional independence\, and local likelihoods—thus extending notions of localization to nonlinear updates. The proposed framework can be understood as a non-Gaussian generalization of the ensemble Kalman filter. \nThis is joint work with Alessio Spantini\, Daniele Bigoni\, Ricardo Baptista\, and Matthew Parno. \nProf. Marzouk is being hosted by Prof. Duraisamy (Aerospace). If you would like to meet him during his visit please send an email to micde-events@umich.edu. If you are an MICDE student and would like to join Prof. Marzouk for lunch please RVSP here by Friday\, November 30.
URL:https://micde.umich.edu/event/micde-seminar-youssef-marzouk-department-of-aeronautics-and-astronautics-mit/
LOCATION:107 Gorguze Family Laboratory\, 2609 Draper Dr\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2018/08/Youssef-Marzouk.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20181126T150000
DTEND;TZID=America/Detroit:20181126T160000
DTSTAMP:20260604T050047
CREATED:20230905T171421Z
LAST-MODIFIED:20230905T171421Z
UID:10000162-1543244400-1543248000@micde.umich.edu
SUMMARY:CANCELLED --MICDE Seminar: Ali Yilmaz\, Electrical Engineering\, University of Texas at Austin
DESCRIPTION:CANCELLED\nBio: Ali Yilmaz is an Associate 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. \nDr. 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. \nHis 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. \nThe 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 student and would like to join Prof. Yilmaz for lunch\, please fill out this form.
URL:https://micde.umich.edu/event/micde-seminar-ali-yilmaz-electrical-engineering-university-of-texas-at-austin/
LOCATION:1311 EECS\, 1301 Beal Ave.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20181109T130000
DTEND;TZID=America/Detroit:20181109T140000
DTSTAMP:20260604T050047
CREATED:20230905T171421Z
LAST-MODIFIED:20230905T171421Z
UID:10000173-1541768400-1541772000@micde.umich.edu
SUMMARY:SC2 Alumni Seminar Series: Eric Harper\, NRC Research Associate\, AFRL
DESCRIPTION:Bio: Dr. Eric Harper is a Postdoctoral Fellow at the Air Force Research Laboratories (AFRL) at Wright-Patterson Air Force Base (WPAFB) in Dayton\, Ohio as part of the Air Force Science and Technology Fellowship Program (STFP). He is a member of the Optical Theory Group (OTG)\, simulating optical metamaterials to optimize their design using scientific computing techniques. He earned his B.S. in Chemical Engineering at the University of Dayton (2011) and his M.S. (2014) and Ph.D. at the University of Michigan (2017). \nMachine Accelerated Nano-targeted Inhomogenous Structures\nThe ability for nanoscale materials to control the propagation of light is well-known\, both in biological systems and synthetic applications. However\, the possible “solution-space” to search for nanoscale designs is near-infinite\, requiring advanced computational techniques to optimize structures for targeted device performance. Here we consider a subset of the infinite design space\, a simple bilayer structure of nanocylinders\, to demonstrate the capabilities of machine learning to accelerate the design process. We compare the performance of human-driven optimization to a genetic algorithm based optimization routine. We also consider potential machine-learning tools to further accelerate the design of these structures. \nThe SC2 is holding a Meet the Speaker lunch at noon. If you would like to attend\, please RSVP here.
URL:https://micde.umich.edu/event/sc2-alumni-seminar-series-eric-harper-nrc-research-associate-afrl/
LOCATION:2540 G.G. Brown (2350 Hayward St.)\, 2300 Hayward St\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,SC2,Seminar
ATTACH;FMTTYPE=image/jpeg:https://micde.umich.edu/wp-content/uploads/2023/02/EricHaperatAFRL.jpeg
GEO:42.292998;-83.7152904
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20181024T160000
DTEND;TZID=America/Detroit:20181024T170000
DTSTAMP:20260604T050047
CREATED:20230905T171421Z
LAST-MODIFIED:20230905T171421Z
UID:10000150-1540396800-1540400400@micde.umich.edu
SUMMARY:MICDE/IOE Seminar: Juan Pablo Vielma\, Sloan School of Management\, MIT
DESCRIPTION:Bio: Juan Pablo Vielma is the Richard S. Leghorn (1939) Career Development Associate Professor at MIT Sloan School of Management and is affiliated to MIT’s Operations Research Center. Dr. Vielma has a B.S. in Mathematical Engineering from University of Chile and a Ph.D. in Industrial Engineering from the Georgia Institute of Technology. His current research interests include the theory and practice of mixed-integer mathematical optimization and applications in natural resource management\, marketing and statistics. In January of 2017 he was named by President Obama as one of the recipients of the Presidential Early Career Award for Scientists and Engineers (PECASE). Some of his other recognitions include the NSF CAREER Award\, the INFORMS Computing Society Prize and a first prize in the INFORMS Junior Faculty Interest Group Paper Competition. He served as vice-chair of Integer and Discrete Optimization for the INFORMS Optimization Society and as chair of the INFORMS Section on Energy\, Natural Resources\, and the Environment. He is currently an associate editor for Operations Research and Operations Research Letters\, a member of the NumFocus steering committee for JuMP\, and the Faculty Director for the MIT-Chile program of MIT’s International Science and Technology Initiatives (MISTI). \nModeling power of mixed integer convex optimization problems and their effective solution with Julia and JuMP\nMore than 50 years of development have made mixed integer linear programming (MILP) an extremely successful tool. MILP’s modeling flexibility allows it describe a wide range of business\, engineering and scientific problems\, and\, while MILP is NP-hard\, many of these problems are routinely solved in practice thanks to state-of-the-art solvers that nearly double their machine-independent speeds every year. Inspired by this success\, the last decade has seen a surge of activity on the solution and application of mixed integer convex programming (MICP)\, which extends MILP’s versatility by allowing the use of convex constraints in addition to linear inequalities. In this talk we cover various recent developments concerning theory\, algorithms and computation for MICP. Solvers for MICP can be significantly more effective than those for more general non-convex optimization\, so one of the questions we cover in this talk is what classes of non-convex constraints can be modeled through MICP. We also cover the solution of MICP problems through polyhedral approximation algorithms that exploit the power of extended formulations. Finally\, we cover various topics concerning the modeling and computational solution of MICP problems using the Julia programming language and the JuMP modeling language for optimization. In Particular\, we show how mixed integer optimal control problems where the variables are polynomials can be easily modeled and solved by seamlessly combining several Julia packages and JuMP extensions with the Julia-written MICP solver Pajarito. \nThis seminar is co-sponsored by the department of Industrial and Operations Engineering. Prof. Vielma is being hosted by Prof. Shen (IOE). If you would like to meet with him during his visit\, please send an email to micde-events@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-juan-pablo-vielma-operations-research-mit/
LOCATION:1680 IOE\, 1205 BEAL AVE\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20181022T120000
DTEND;TZID=America/Detroit:20181022T130000
DTSTAMP:20260604T050047
CREATED:20230905T171421Z
LAST-MODIFIED:20230905T171421Z
UID:10000163-1540209600-1540213200@micde.umich.edu
SUMMARY:MICDE/Quantitative Biology Seminar: Padmini Rangamani\, Mechanical and Aerospace Engineering\, UC San Diego
DESCRIPTION:Bio: Padmini Rangamani is an associate professor in Mechanical Engineering at the University of California\, San Diego. She joined the department in July 2014. Earlier\, she was a UC Berkeley Chancellor’s Postdoctoral Fellow\, where she worked on lipid bilayer mechanics. She obtained her Ph.D. in biological sciences from the Icahn School of Medicine at Mount Sinai. She received her B.S. and M.S. in Chemical Engineering from Osmania University (Hyderabad\, India) and Georgia Institute of Technology respectively. She is the recipient of the ARO\, AFOSR\, and ONR Young Investigator Awards\, and a Sloan Research Fellowship for Computational and Molecular Evolutionary Biology. She is also the lead PI for a MURI award on Bioinspired low energy information processing from the AFOSR. \nGEOMETRIC PRINCIPLES OF SPATIO-TEMPORAL DYNAMICS OF SECOND MESSENGERS IN DENDRITIC SPINES\nThe ability of the brain to encode and store information depends on the plastic nature of the individual synapses. The increase and decrease in synaptic strength\, mediated through the structural plasticity of the spine\, are important for learning\, memory\, and cognitive function. Dendritic spines are small structures that contain the synapse. They come in a variety of shapes (stubby\, thin\, or mushroom-shaped) and a wide range of sizes that protrude from the dendrite. These spines are the regions where the postsynaptic biochemical machinery responds to the neurotransmitters. Spines are dynamic structures\, changing in size\, shape\, and number during development and aging. While spines and synapses have inspired neuromorphic engineering\, the biophysical events underlying synaptic and structural plasticity remain poorly understood. \nOur current focus is on understanding the biophysical events underlying structural plasticity. I will discuss two recent efforts from my group — first\, a systems biology approach to construct a mathematical model of biochemical signaling and actin-mediated transient spine expansion in response to calcium influx caused by NMDA receptor activation and second\, a series of spatial models to study the role of spine geometry and organelle location within the spine for calcium and cyclic AMP signaling. I will conclude with some new efforts in using reconstructions from electron microscopy to inform computational domains. I will conclude with how geometry and mechanics plays an important role in our understanding of fundamental biological phenomena and some general ideas on bio-inspired engineering. \nProf. Rangamani is being hosted by Prof. Garikipati (Mechanical Engineering). If you would like to meet with her please send an email to micde-events@umich.edu. If you are an MICDE student and would like to join Prof. Rangamani for lunch please fill out this form
URL:https://micde.umich.edu/event/micde-quantitative-biology-seminar-padmini-rangamani-mechanical-and-aerospace-engineering-uc-san-diego/
LOCATION:335 West Hall\, 1085 S University\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20181016T083000
DTEND;TZID=America/Detroit:20181016T123000
DTSTAMP:20260604T050047
CREATED:20230905T171421Z
LAST-MODIFIED:20230905T171421Z
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SUMMARY:CNSECCS 2018 Symposium
DESCRIPTION:The Center for Network and Storage Enabled Collaborative Computation is hosting its second Symposium on October 15 and 16\, 2018\, exploring the themes the Center was founded on. The Center seeks to address the challenges of extracting scientific results collaboratively from large\, distributed or diverse data. \nFor more information please visit https://indico.cern.ch/event/692449/registrations/39788/ \n\n\n\nConfirmed speakers:\n\n\nStefan Robila\, Program Director\, Office of Advanced Cyberinfrastructure\, Research Core Program\, National Science Foundation\nSaul Youssef\, Research Associate Professor\, Boston University Department of Physics\nIlkay Altintas\, Director\, Center of Excellence in Workflows for Data Science\, San Diego Supercomputer Center\, University of California\, San Diego\nAllison Steiner\, Professor\, Department of Climate and Space Science and Engineering\, University of Michigan\nChris Miller\, Associate Professor\, Astronomy and Physics\, University of Michigan\nJesse Capecelatro\, Assistant Professor\, Mechanical Engineering\, University of Michigan\nAlberto Figueroa\, Professor\, Biomedical Engineering\, University of Michigan\nIvo Dinov\, Professor\, Computational Medicine and Bioinformatics\, School of Nursing; Associate Director\, Education and Training of the Michigan Institute for Data Science (MIDAS)\, University of Michigan\nShawn McKee\, Research Scientist\, Department of Physics\, U-M; Director\, Center for Network and Storage Enabled Collaborative Computational Science (CNSECCS)\n\n\n\n—\n\nMonday\, October 15\, 2018 @ 8:30 a.m. – 5:00 p.m.\nTuesday\, October 16\, 2018 @ 8:30 a.m. – 12:30 p.m.
URL:https://micde.umich.edu/event/cnseccs-2018-symposium/2018-10-16/
LOCATION:Space 2435 North Quad\, 105 S. State St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Conference,Featured Events
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20181015T083000
DTEND;TZID=America/Detroit:20181015T170000
DTSTAMP:20260604T050047
CREATED:20230905T171421Z
LAST-MODIFIED:20230905T171421Z
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SUMMARY:CNSECCS 2018 Symposium
DESCRIPTION:The Center for Network and Storage Enabled Collaborative Computation is hosting its second Symposium on October 15 and 16\, 2018\, exploring the themes the Center was founded on. The Center seeks to address the challenges of extracting scientific results collaboratively from large\, distributed or diverse data. \nFor more information please visit https://indico.cern.ch/event/692449/registrations/39788/ \n\n\n\nConfirmed speakers:\n\n\nStefan Robila\, Program Director\, Office of Advanced Cyberinfrastructure\, Research Core Program\, National Science Foundation\nSaul Youssef\, Research Associate Professor\, Boston University Department of Physics\nIlkay Altintas\, Director\, Center of Excellence in Workflows for Data Science\, San Diego Supercomputer Center\, University of California\, San Diego\nAllison Steiner\, Professor\, Department of Climate and Space Science and Engineering\, University of Michigan\nChris Miller\, Associate Professor\, Astronomy and Physics\, University of Michigan\nJesse Capecelatro\, Assistant Professor\, Mechanical Engineering\, University of Michigan\nAlberto Figueroa\, Professor\, Biomedical Engineering\, University of Michigan\nIvo Dinov\, Professor\, Computational Medicine and Bioinformatics\, School of Nursing; Associate Director\, Education and Training of the Michigan Institute for Data Science (MIDAS)\, University of Michigan\nShawn McKee\, Research Scientist\, Department of Physics\, U-M; Director\, Center for Network and Storage Enabled Collaborative Computational Science (CNSECCS)\n\n\n\n—\n\nMonday\, October 15\, 2018 @ 8:30 a.m. – 5:00 p.m.\nTuesday\, October 16\, 2018 @ 8:30 a.m. – 12:30 p.m.
URL:https://micde.umich.edu/event/cnseccs-2018-symposium-2/
LOCATION:Space 2435 North Quad\, 105 S. State St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Conference,Featured Events
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20181009T160000
DTEND;TZID=America/Detroit:20181009T170000
DTSTAMP:20260604T050047
CREATED:20230905T171421Z
LAST-MODIFIED:20230905T171421Z
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SUMMARY:MICDE Seminar: Nandini Ananth\, Department of Chemistry and Chemical Biology\, Cornell University
DESCRIPTION:Bio: Nandini Ananth is an associate professor in the department of Chemistry and Chemical Biology at Cornell University. She received her bachelor’s degree in Chemistry from Stella Maris College in Chennai\, India\, and a Masters in chemistry from the Indian Institute of Technology Madras.  Nandini moved to the United States in the fall of 2003 to pursue doctoral research at the University of California\, Berkeley in William Miller’s group\, working on developing semiclassical methods to model quantum dynamical behavior in complex chemical reactions. Upon graduation\, she accepted a position as postdoctoral scholar in Thomas Miller’s group at the California Institute of Technology\, Pasadena\, where her research focused on developing path-integral methods for the simulation of electronically nonadiabatic processes in the condensed phase. She joined the faculty of the department of Chemistry and Chemical Biology at Cornell University in the Fall of 2012\, and during her time here has received the Cottrell Scholar Award\, NSF CAREER Award\, NSF EAGER Award\, Sloan Research Fellowship\, and Army Research Office’s Young Investigator Award. \nCharge Transfer Dynamics\, Excited State Energetics\, and Organic Photovoltaics\nDesigning molecular materials for use as organic photovoltaics\, molecular electronics\, and photocatalysts is a multifaceted challenge requiring a detailed understanding of both the excited state energetics and the dynamics of charge and energy transfer. We address the dynamic challenge by developing new methods based on the path integral formulation of quantum mechanics that are uniquely suited to the simulation of photo-initiated excited state dynamics in the condensed phase. We then tackle the characterization of the excited state manifold in molecular systems using a combination of high-level electronic structure methods to accurately calculate excited state energies\, normal mode analysis to quantify vibronic couplings\, and novel orbital analyses to uncover structure-spectrum correlations.\nIn this talk\, we focus on one target application: designing chromophores that exhibit ultrafast Singlet Fission (SF)\, a phenomenon that has the potential to significantly increase organic solar cell efficiency. We investigate SF in non-bonded and covalently bonded pentacene dimers: we uncover two distinct mechanistic pathways for ultrafast SF and we identify molecular geometries and bonding motifs that can be modified to enhance efficiency in each case. Finally\, we combine the insights obtained from our theoretical investigations to generate a priori design principles for next-generation SF chromophores\, and working with experimental collaborators\, we verify them. \nProf. Ananth is being hosted by Prof. Geva (Chemistry). If you would like to meet her during her visit please send an email to micde-events@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-nandini-ananth-department-of-chemistry-and-chemical-biology-cornell/
LOCATION:CHEM 1300\, 930 N University Ave\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20181005T150000
DTEND;TZID=America/Detroit:20181005T160000
DTSTAMP:20260604T050047
CREATED:20230905T171420Z
LAST-MODIFIED:20230905T171420Z
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SUMMARY:MICDE Seminar: Pavel Bochev\, Center for Computing Research\, Sandia National Laboratories
DESCRIPTION:Bio: Pavel Bochev is a Distinguished Member of the Technical Staff at Sandia National Laboratories in Albuquerque where he works in the Center for Computing Research. He joined Sandia in 2000 after six years of teaching and research at the University of Texas at Arlington. \n\nPavel’s research interests include compatible discretizations for partial differential equations\, optimization and control problems\, and the development of new\, property preserving heterogeneous numerical methods for complex applications relevant to the mission of the US Department of Energy and the National Nuclear Security Administration.\n\nPavel’s thesis was awarded the SIAM Student paper prize in 1994. In 2012 he was elected a Fellow of the Society for Industrial and Applied Mathematics. Pavel is a recipient of 2014 US Department of Energy’s E. O. Lawrence Medal in the category of “Computer\, information and knowledge sciences”. This award honors U.S. scientists and engineers\, at mid-career\, for exceptional contributions in research and development supporting the Department of Energy and its mission to advance the national\, economic and energy security of the United States. In 2017 Pavel was awarded the Thomas J.R. Hughes Medal by the U.S. Association for Computational Mechanics for his contributions to the field of numerical partial differential equations.\n\nPavel has authored and co-authored over 100 research papers\, two books and several book chapters\, and has given numerous plenary and invited lectures in the US and abroad. He served two terms as Editor-in-Chief of the SIAM Journal on Numerical Analysis and is currently member of the editorial board of SINUM. \nCompatible Mesh-Free Methods\nParticle and mesh-free methods offer significant computational advantages in settings where quality mesh generation required for many compatible PDE discretizations may be expensive or even intractable. At the same time\, the lack of underlying geometric grid structure makes it more difficult to construct mesh-free methods mirroring the discrete vector calculus properties of mesh-based compatible and mimetic discretization methods. In this talk we survey ongoing efforts at Sandia National Laboratories to develop new classes of locally and globally compatible meshfree methods that attempt to recover some of the key properties of mimetic discretization methods. \nWe will present two examples of recently developed “mimetic”-like meshfree methods. The first one is motivated by classical staggered discretization methods. We use the local connectivity graph of a discretization particle to define locally compatible discrete operators. In particular\, the edge-to-vertex connectivity matrix of the local graph provides a topological gradient\, whereas a generalized moving least-squares (GMLS) reconstruction from the edge midpoints defines a divergence operator. The second method can be viewed as a meshfree analogue of a finite volume type scheme. In this method\, the metric information that would be normally provided by the mesh\, such as cell volumes and face areas\, is reconstructed algebraically\, without a mesh. This reconstruction process effectively creates virtual cells having virtual faces and ensures a local conservation property matching that of mesh-based finite volumes. In contrast to similar recent efforts our approach does not involve a solution of a global optimization problem to find the virtual cell volumes and faces areas. Instead\, we determine the necessary metric information by solving a graph Laplacian problem that can be effectively preconditioned by algebraic multigrid. \nSeveral numerical examples will illustrate the mimetic properties of the new meshfree schemes. The talk will also review some of the ongoing work to build a modern software toolkit for mesh-free and particle discretizations that leverages Sandia’s Trillinos library and performance tools such as Kokkos. \nThis is a joint seminar with the Applied and Interdisciplinary Mathematics program. Dr. Bochev is being hosted by Prof. Robert Krasny (Mathematics). If you would like to meet with him\, please send an email to micde-events@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-pavel-bochev-center-for-computing-research-sandia-national-laboratories/
LOCATION:1084 East Hall\, 530 Church St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
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