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DTSTART;TZID=America/Detroit:20200225T113000
DTEND;TZID=America/Detroit:20200225T130000
DTSTAMP:20260603T211818
CREATED:20230905T171342Z
LAST-MODIFIED:20230905T171342Z
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SUMMARY:Complex Systems Seminar: David Goluskin\, Assistant Professor\, Mathematics and Statistics\, University of Victoria
DESCRIPTION:Bio: David Goluskin is an Assistant Professor in the Department of Mathematics and Statistics at the University of Victoria. Goluskin received his undergraduate degrees from the University of Colorado\, Boulder\, a master’s from Columbia University\, and a PhD in Applied Mathematics from Columbia University. His research is in the broad area of applied nonlinear dynamics and incorporates both computation and analysis. Much of Professor Goluskin’s work concerns fluid dynamics\, but he also studies simpler ordinary and partial differential equations. \nStudying dynamics using computational polynomial optimization\nMany complex systems are governed by nonlinear ODEs or PDEs that cannot be solved exactly. Various properties of such solutions can be inferred by constructing auxiliary functions that satisfying suitable inequalities. The most familiar example is the construction of Lyapunov functions to infer stability of particular states\, but similar approaches can produce many other types of mathematical statements\, including for systems with chaotic or otherwise complicated behavior. Such statements include estimates of time-averaged quantities and extreme transient behavior\, approximation of nonlinear stability properties\, and design of controls. In many cases\, the search for the auxiliary function that implies the strongest mathematical statement can be posed as a convex optimization problem. Such problems can be studied analytically or computationally\, but in most cases computation is needed to find solutions that are close to optimal. Of particular use are computational methods of polynomial optimization\, where the optimization constraints include polynomial inequalities. This talk will provide an overview of different ways in which auxiliary functions can be used to study nonlinear ODEs and PDEs\, as well as how polynomial optimization can be used to implement these methods computationally. Methods will be illustrated using applications to various complex systems.
URL:https://micde.umich.edu/event/complex-systems-seminar-david-goluskin-assistant-professor-mathematics-and-statistics-university-of-victoria/
LOCATION:Weiser Hall\, Room 747\, 500 Church St\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,Seminar
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200221T150000
DTEND;TZID=America/Detroit:20200221T160000
DTSTAMP:20260603T211818
CREATED:20230905T171342Z
LAST-MODIFIED:20230905T171342Z
UID:10000332-1582297200-1582300800@micde.umich.edu
SUMMARY:MICDE Seminar: Osman Basaran\, Professor\, Chemical Engineering\, Purdue University
DESCRIPTION:Bio: Professor Osman Basaran is a Burton and Kathryn Gedge Professor of Chemical Engineering at Purdue University. He received his undergraduate degree at Massachusetts Institute of Technology and a PhD from the University of Minnesota. Prof. Basaran’s research involves the use of a balanced approach based on computation\, theory\, and experiment to attack a number of fundamental issues that lie at the heart of such practical problems. \nHigh-accuracy simulation of free surface flows near finite-time pinch-off and coalescence singularities\nMotivated by applications such as ink jet printing\, drop-by-drop manufacturing\, sprays\, emulsions\, and chemical separations\, we study the dynamics of breakup and coalescence through high-accuracy simulation\, theory\, and experiment.  In this talk\, I will highlight our group’s work on accurately capturing the fluid dynamics that takes place in the vicinity of finite-time singularities. The free surface flow algorithms and solvers that we develop and use rely on a sharp interface representation of phase boundaries.  In the simulations\, we are able to analyze situations that involve disparate length scales that differ by up to seven orders of magnitude (commercial codes can handle about 2-3 orders and custom codes can capture at most 3-4 orders of magnitude disparity in length scales). The primary focus of the talk will be on simulations of the breakup of surfactant-covered filaments where I will pay special attention to the pinch-off singularity.  I will also summarize some of our recent work on the pre- and post-coalescence singularities that arise when two drops or bubbles are driven together and made to merge into one.  \nThis seminar is co-sponsored by the Applied & Interdisciplinary Mathematics program. Prof. Basaran is being hosted by Prof. Deegan (Physics). If you would like to meet with Prof. Basaran during his visit\, please send an email to micde-events@umich.edu. If you are an MICDE student or an AIM student and you’re interested in having lunch with Prof. Basaran during his visit\, please RSVP by Thursday\, February 20\, 2020.
URL:https://micde.umich.edu/event/micde-seminar-osman-basaran-purdue/
LOCATION:1084 East Hall\, 530 Church St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200131T153000
DTEND;TZID=America/Detroit:20200131T163000
DTSTAMP:20260603T211818
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SUMMARY:MICDE Seminar: Amir Salaree\, Postdoctoral Fellow\, Earth and Environmental Sciences\, University of Michigan
DESCRIPTION:Due to unforeseen circumstances the originally scheduled talk by Professor Brandon Johnson has been cancelled and replaced with the following seminar. \nTheoretical and Computational Contributions to the Modeling of Global Tsunamis\nThe distribution of tsunami amplitudes in the open ocean is controlled by source mechanism as well as bathymetry geometry and resolution\, with the latter controlling far-field tsunami features. However\, large detailed bathymetry grids result in long computer simulation times for tsunamis. It is therefore of interest to investigate the amount of physical detail in bathymetric grids that control the most important features in tsunami amplitudes\, to assess what constitutes sufficient level for grids in numerical simulations. By decomposing the Pacific bathymetry using a spherical harmonics approach one can create “smoothed” versions of the original field. Using these simplified bathymetries to simulate tsunamis from potential ruptures around the Pacific\, we can see that for large megathrust events (M0=1029 dyn-cm)\, only a resolution of ~1000 km (equivalent to l=40)\, or ~1% surface smoothness of the Pacific is needed in order to reproduce the main components of the true distribution of tsunami amplitudes. This would result in simpler simulations\, and faster computations in the context of tsunami warning algorithms. \nIn a separate context\, an overview of tsunami studies and a report on a study of a meteotsunami are presented. These scenarios are evidence for the fact that tsunami studies are interdisciplinary fields of research that require coordinated efforts by investigators from various backgrounds. \nMICDE is co-hosting this seminar with the Earth and Environmental Sciences department. 
URL:https://micde.umich.edu/event/micde-seminar-brandon-johnson-purdue/
LOCATION:RM1528\, 1100 North University Building
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200124T130000
DTEND;TZID=America/Detroit:20200124T140000
DTSTAMP:20260603T211818
CREATED:20230905T171341Z
LAST-MODIFIED:20230905T171341Z
UID:10000312-1579870800-1579874400@micde.umich.edu
SUMMARY:MICDE Seminar: Andrew Wetzel\, Assistant Professor\, Physics\, University of California\, Davis
DESCRIPTION:Bio: Professor Wetzel is an assistant professor in the physics department and in the astrophysics and cosmology group at the University of California\, Davis. He is a theoretical/computational astrophysicist and cosmologist. Using the world’s most powerful supercomputers\, he generates cosmological simulations to model the formation of cosmic structures\, including galaxies and their stars. He uses these simulations as theoretical laboratories to develop and test models of galaxy formation\, stellar dynamics\, and the nature of dark matter\, with emphasis on our own Milky Way galaxy. \nSimulating the Milky Way\nThe Gaia satellite mission\, together with a multitude of ground-based observational surveys\, now measure 6-D phase-space coordinates and multi-species elemental abundances for hundreds of millions of stars across the Milky Way. This new era of galactic archeology and near-field cosmology demands a new generation of simulations that achieve high dynamic range to resolve scales of individual stellar populations within a cosmological context. I will describe the new Latte suite of massively parallelized cosmological zoom-in simulations\, run on the nation’s most powerful supercomputers\, that model the formation of Milky Way-like galaxies at parsec-scale resolution\, using the FIRE (Feedback in Realistic Environments) model for star formation and feedback. First I will discuss the formation of the Milky Way disk\, including resolving for the first time the dynamics and lifetimes of giant molecular clouds and stars clusters at z = 0. These simulations also self-consistently resolve the formation of satellite dwarf galaxies around each Milky Way-like host. These low-mass galaxies have presented significant challenges to the cold dark matter model\, but I will show progress in addressing the “missing satellites” and “too-big-to-fail” problems. Finally\, I will discuss synthetic Milky Way surveys that we have created from the Latte simulations\, which are publicly available\, to provide theoretical modeling insight for the era of Gaia. \nProf. Wetzel is being hosted by Prof. Gnedin (Astronomy).  If you would like to meet with him during his visit\, please send an email to micde-events@umich.edu. If you are an MICDE graduate student and would like to join Prof. Wetzel for lunch please RSVP by Thursday\, January 23. 
URL:https://micde.umich.edu/event/micde-seminar-andrew-wetzel-uc-davis/
LOCATION:411 West Hall (1085 S. University)\, 1085 S. University Ave\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2019/12/Andrew-Wetzel.png
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20191028T160000
DTEND;TZID=America/Detroit:20191028T160000
DTSTAMP:20260603T211818
CREATED:20230905T171336Z
LAST-MODIFIED:20230905T171336Z
UID:10000297-1572278400-1572278400@micde.umich.edu
SUMMARY:Mid West Mechanics Seminar: Jacqueline H. Chen\, Senior Scientist\, Sandia National Laboratories
DESCRIPTION:Bio: Jacqueline H. Chen is a Senior Scientist at the Combustion Research Facility at Sandia National Laboratories. She has contributed broadly to research in turbulent combustion elucidating turbulence-chemistry interactions in combustion through direct numerical simulations. To achieve scalable performance of DNS on heterogeneous computer architectures she leads an interdisciplinary team of computer scientists\, applied mathematicians and computational scientists to develop an exascale direct numerical simulation capability for turbulent combustion with complex chemistry and multi- physics. She is a member of the National Academy of Engineering and a Fellow of the Combustion Institute and the Americal Physical Society. She received the Combustion Institute’s Bernard Lewis Gold Medal Award in 2018 and the Society of Women Engineers Achievement Award in 2018. \nTowards Exascale Simulation of Turbulent Combustion in Complex Flows Relevant to Efficient Clean Engines\nDirect numerical simulation (DNS) methodology and computing power have progressed to the point where it is feasible to perform DNS in mildly complex geometries representative of flow configurations encountered in practical combustors. These complex flows encompass effects of mean shear\, flow recirculation\, and wall boundary layers together with turbulent fluctuations which affect entrainment\, mixing and combustion. Recent DNS studies with complex flows relevant to efficient low emissions gas turbine and internal combustion engines will be presented. Through application co-design with computer scientists a data centric asynchronous programming system has been used to refactor the DNS code\, S3D\, resulting in improved time-to-solution and overall performance on heterogeneous architectures. The programming system also provides more efficient and effective composition of in situ analytics and machine learning techniques. \nContact Melissa McGeorge (mcgeorge@umich.edu) for more details.
URL:https://micde.umich.edu/event/mid-west-mechanics-seminar-jacqueline-h-chen-sandia-national-laboratories/
LOCATION:107 Gorguze Family Laboratory\, 2609 Draper Dr\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://micde.umich.edu/wp-content/uploads/2023/02/JacquelineChen.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190410T080000
DTEND;TZID=America/Detroit:20190410T170000
DTSTAMP:20260603T211818
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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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190111T150000
DTEND;TZID=America/Detroit:20190111T160000
DTSTAMP:20260603T211818
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:20260603T211818
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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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20181126T150000
DTEND;TZID=America/Detroit:20181126T160000
DTSTAMP:20260603T211818
CREATED:20230905T171421Z
LAST-MODIFIED:20230905T171421Z
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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:20260603T211818
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:20181023T113000
DTEND;TZID=America/Detroit:20181023T130000
DTSTAMP:20260603T211818
CREATED:20230905T171421Z
LAST-MODIFIED:20230905T171421Z
UID:10000166-1540294200-1540299600@micde.umich.edu
SUMMARY:Complex Systems Seminar: Giovanni Fantuzzi\, Aeronautics\, Imperial College London
DESCRIPTION:Bio: Giovanni Fantuzzi is an EPSRC Doctoral Prize Fellow in the Department of Aeronautics\, Imperial College London\, from which he received an MEng degree in 2014 and a PhD in 2018. During his PhD he developed optimization-based methods and software for studying stability and time-averaged properties of dynamical systems\, with applications to fluid flows. In 2015 he was awarded a Geophysical Fluid Dynamics Fellowship from Woods Hole Oceanographic Institution and was subsequently a Research Assistant at the University of Oxford\, where he worked on fast algorithms for structured semidefinite programmes and sum-of-squares optimization. His current research spans fluid dynamics and convex optimization\, and he is especially interested in scalable convex approaches to hydrodynamic analysis. \nBeyond numerical integration: studying nonlinear dynamics with polynomial optimization\nSystems characterized by complex nonlinear dynamics lie at the heart of 21st century technology. Examples are turbulent flows in the transport and aviation industries\, smart energy networks\, and models of cell dynamics used in synthetic biology. Quantitative analysis of such systems using direct numerical simulations sometimes requires prohibitively large computational resources even when one is interested only in some average properties\, such as mean power consumption\, because all time and length scales across which the system evolves must be resolved. In addition\, while numerical simulations offer detailed information starting from a specific initial state\, they cannot provide safety-critical performance or stability guarantees that hold for all possible initial states. In this talk\, I will describe an alternative approach to studying nonlinear systems with polynomial dynamics\, which combines ideas from Lyapunov’s stability theory with recent numerical tools for polynomial optimization. In particular\, I will present a range of examples that demonstrate how this optimization-based method enables the efficient algorithmic construction of stability certificates and the computation of rigorous bounds on performance-related system properties. Other applications\, including optimal control and disturbance amplification analysis\, will be discussed along with open problems and future research directions.
URL:https://micde.umich.edu/event/complex-systems-seminar-giovanni-fantuzzi-aeronautics-imperial-college-london/
LOCATION:Weiser Hall\, Room 747\, 500 Church St\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/02/GiovanniFantuzzi2018.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20180914T150000
DTEND;TZID=America/Detroit:20180914T160000
DTSTAMP:20260603T211818
CREATED:20230905T171420Z
LAST-MODIFIED:20230905T171420Z
UID:10000158-1536937200-1536940800@micde.umich.edu
SUMMARY:AIM Seminar: Robert Krasny\, Mathematics\, University of Michigan
DESCRIPTION:Two topics in computational fluid dynamics\n1. The Lamb dipole is a steady propagating solution of the inviscid fluid equations with opposite-signed vorticity in a circular disk. We compare finite-difference solutions of the Navier-Stokes equation (NSE) and the linear diffusion equation (LDE) using the Lamb dipole as the initial condition. We find some expected and some unexpected results; among the latter is that the maximum core vorticity decreases at the same rate for the NSE and LDE\, but at higher Reynolds numbers\, convection enhances the viscous cancellation of opposite-signed vorticity.\n(This is joint work with Ling Xu.) \n2. We discuss a new implementation of the vortex method for the incompressible Euler equations. The vorticity is carried by Lagrangian particles and the velocity is recovered by a regularized Biot-Savart integral. The new work employs remeshing and adaptive refinement to resolve small-scale features in the vorticity as well as a treecode for efficiency. The method is demonstrated for vortex dynamics on a rotating sphere (with Peter Bosler) and axisymmetrization of an elliptical vortex (with Ling Xu).
URL:https://micde.umich.edu/event/aim-seminar-robert-krasny-mathematics-university-of-michigan/
LOCATION:1084 East Hall\, 530 Church St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Seminar
GEO:42.2757302;-83.7351764
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=1084 East Hall 530 Church St. Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=530 Church St.:geo:-83.7351764,42.2757302
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20180907T150000
DTEND;TZID=America/Detroit:20180907T160000
DTSTAMP:20260603T211818
CREATED:20230905T171421Z
LAST-MODIFIED:20230905T171421Z
UID:10000157-1536332400-1536336000@micde.umich.edu
SUMMARY:AIM Seminar: Alex Gorodetsky\, Aerospace Engineering\, University of Michigan
DESCRIPTION:Low-rank tensor approaches for adaptive function approximation: algorithms and examples\nIn this talk\, we present an adaptive method for approximating high-dimensional low-rank functions. Taking advantage of low-rank structure in approximation problems has been shown to prove advantageous for scaling numerical algorithms and computation to higher dimensions by mitigating the curse-of-dimensionality. The method we describe is an extension of the tensor-train cross approximation algorithm to the continuous case of multivariate functions that enables both global and local adaptivity. Our approach relies on a new adaptive algorithm for computing the CUR/skeleton decomposition of bivariate functions. We then extend this technique to the multidimensional case of the function-train decomposition. We demonstrate the benefits of our approach compared with the standard methodology that computes low-rank approximations by decomposing coefficients of tensor-product basis functions. We finish by demonstrating a wide range of applications that include machine learning\, uncertainty quantification\, stochastic optimal control\, and Bayesian filtering.
URL:https://micde.umich.edu/event/aim-seminar-alex-gorodetsky-aerospace-engineering-university-of-michigan/
LOCATION:1084 East Hall\, 530 Church St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Seminar
GEO:42.2757302;-83.7351764
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=1084 East Hall 530 Church St. Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=530 Church St.:geo:-83.7351764,42.2757302
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20180806T083000
DTEND;TZID=America/Detroit:20180806T163000
DTSTAMP:20260603T211818
CREATED:20230905T171419Z
LAST-MODIFIED:20260401T200727Z
UID:10000148-1533544200-1533573000@micde.umich.edu
SUMMARY:Single-Cell Data Analytics Symposium 2018
DESCRIPTION:Please join us for the second annual Single-cell Genomic Data Analytics Symposium. The day long symposium will highlight researchers from U-M and around the world whose work is on the leading edge of innovation and discovery. This symposium is organized by the Michigan Center for Single-Cell Genomic Data Analytics and sponsored by the Michigan Institute for Data Science. \n\n\n\n\n  \nFEATURED SPEAKERS\n\nPeter Kharchenko\, Assistant Professor of Biomedical Informatics Harvard Medical School\nJohn Marioni\, Research Group Leader\, European Bioinformatics Institute\nDana Pe’er\, Scientific Director\, GMTEC; Chair\, Computational and Systems Biology Program\, Memorial Loan Kettering Cancer Center\nChristina Kendziorski\, Professor\, Biostatistics and Medical Informatics\, University of Wisconsin
URL:https://micde.umich.edu/event/single-cell-data-analytics-symposium-2018/
LOCATION:Palmer Commons\, Great Lakes Central Room\, 100 Washtenaw Ave.\, Ann Arbor\, MI\, United States
CATEGORIES:Conference,Seminar
GEO:42.2807096;-83.7338753
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Palmer Commons Great Lakes Central Room 100 Washtenaw Ave. Ann Arbor MI United States;X-APPLE-RADIUS=500;X-TITLE=100 Washtenaw Ave.:geo:-83.7338753,42.2807096
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20180406T150000
DTEND;TZID=America/Detroit:20180406T160000
DTSTAMP:20260603T211818
CREATED:20230905T171419Z
LAST-MODIFIED:20230905T171419Z
UID:10000138-1523026800-1523030400@micde.umich.edu
SUMMARY:CEE/MICDE Seminar: Khachik Sargsyan\, Sandia National Laboratories
DESCRIPTION:Bio: Khachik Sargsyan is a Principal Member of Technical Staff at Sandia National Laboratories (SNL) in Livermore\, CA. Before staff and postdoctoral positions at SNL\, he received his Ph.D. in Applied and Interdisciplinary Mathematics from University of Michigan\, Ann Arbor\, in 2007. His Bachelors degree\, awarded in 2002\, is in Applied Math and Physics from Moscow Institute of Physics and Technology. Dr. Sargsyan’s research evolves around uncertainty quantification (UQ) and predictability analysis of physical and computational models. He has developed and applied methods for model reduction\, UQ and data assimilation\, targeting fundamental challenges such as structural errors\, intrinsic stochasticity\, high-dimensionality\, limited data\, discontinuities and rare events\, with applications in climate modeling\, chemical kinetics\, hardware architecture simulators and turbulent combustion. He is one of the lead developers of UQTk (www.sandia.gov/uqtoolkit)\, a lightweight C++/Python software toolkit for quantification of uncertainties in model predictions.\n \nDr. Sargsyan is being hosted by Prof. Ivanov (Civil and Env. Engineering). If you would like to meet him\, please send an email to Chase Dwelle at dwellem@umich.edu \nProbabilistic Methods for Uncertainty Quantification in Computational Models\nOver the last decade\, improved measurement capabilities and computational resources have led to significant algorithmic developments toward efficient uncertainty quantification (UQ) for computational models. Such models of physical systems often involve input parameters that exhibit certain degree of uncertainty. Estimation and propagation of these uncertainties are crucial for model validation\, computational/experimental design and decision making. ​This talk will focus on probabilistic methods with emphasis on Polynomial Chaos (PC) expansions as a means for functional representation of random variables. The talk will highlight the use of PC methods both for forward propagation of uncertainties and for inverse problems\, such as parameter estimation via Bayesian inference. I will list associated major challenges\, including the curse of dimensionality and model structural error estimation\, in the context of computationally expensive models of physical systems. Both fundamental and more recent methods will be introduced and demonstrated\, impacting a wide range of applications\, such as climate modeling\, turbulent combustion and chemical kinetics.
URL:https://micde.umich.edu/event/cee-micde-seminar-khachik-sargsyan-sandia-national-laboratories/
LOCATION:1311 EECS\, 1301 Beal Ave.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2018/03/Khachik-Sargsyan.png
GEO:42.292322;-83.713272
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=1311 EECS 1301 Beal Ave. Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=1301 Beal Ave.:geo:-83.713272,42.292322
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20180406T150000
DTEND;TZID=America/Detroit:20180406T160000
DTSTAMP:20260603T211818
CREATED:20230905T171419Z
LAST-MODIFIED:20230905T171419Z
UID:10000139-1523026800-1523030400@micde.umich.edu
SUMMARY:AIM Seminar: Christoph Börgers\, Mathematics\, Tufts University
DESCRIPTION:Bio: Christoph Börgers is a Professor of Mathematics at Tufts University. He got his Ph.D. under Prof. Charles Peskin at the Courant Institute of Mathematical Sciences\, in 1985. Prof. Börgers was a professor in the University of Michigan department of Mathematics until 1996 when he moved to Tufts. His expertise is in mathematical neuroscience\, applied dynamical systems\, numerical analysis\, scientific computing\, and during the past decade\, most of his work has been in the area of Computational Neuroscience. \nRhythms in neuronal networks with recurrent excitation\nInteracting excitatory and inhibitory neuronal populations often generate oscillations in electrical fields in the brain. I will briefly review this mechanism and the reasons to believe that it is important in brain function. Most of the talk will be focused on the effects of recurrent excitation\, i.e.\, of the neurons of a local network in the brain exciting each other. Recurrent excitation can sustain activity in a network that would otherwise be quiescent; this is believed to be the basis of working memory. It can also lead to a runaway process\, with excitation generating more excitation etc.\, much as the presence of a quadratic term on the right-hand side of a differential equation can lead to blow-up in finite time; this may be related to epileptic seizures. For model problems\, we prove that abrupt transitions to runaway activity require recurrent excitation with fast kinetics\, while working memory activity is more robust with recurrent excitation with slow kinetics. \nProf. Börgers is being hosted by Prof. Robert Krasny (Mathematics).
URL:https://micde.umich.edu/event/aim-seminar-christoph-borgers-mathematics-tufts-university/
LOCATION:1084 East Hall\, 530 Church St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2018/03/Christoph-Borgers.png
GEO:42.2757302;-83.7351764
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=1084 East Hall 530 Church St. Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=530 Church St.:geo:-83.7351764,42.2757302
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20180116T160000
DTEND;TZID=America/Detroit:20180116T170000
DTSTAMP:20260603T211818
CREATED:20230905T171416Z
LAST-MODIFIED:20230905T171416Z
UID:10000098-1516118400-1516122000@micde.umich.edu
SUMMARY:MICDE Seminar: Theresa Windus\, Chemistry\, Iowa State University
DESCRIPTION:Bio: Theresa Windus is a professor of Chemistry at Iowa State University. She earned her Ph.D. from Iowa State University in 1993 and did post-doctoral research at Northwestern University. Theresa was also the Director of Computational Chemistry/Training at Ohio Supercomputer Center and the Computational Chemistry lead at the Wright Patterson Air Force Base Major Shared Resource Center. Most recently\, she was the manager of the Molecular Science Software Group and the Visualization and User Services group in the Molecular Science Computing Facility in the Environmental Molecular Sciences Laboratory of Pacific Northwest National Laboratory. \nThe challenges of the exascale from the view of a molecular chemist\nThis talk will focus on the challenges that computational chemistry faces in taking the equations that model the very small (molecules and the reactions they undergo) to efficient and scalable implementations on the very large computers of today andtomorrow. In particular\, how do we take advantage of the newest architectures while preparing for the next generation of computers? How do we increase programmer productivity while ensuring excellent performance\, efficiency and portability across multiple platforms? How do we take advantage of the work of mathematicians\, computer scientists and other computational scientists to enable our science\, while ensuring maintainability and usability of the software? How do we ensure that the algorithms that we develop are making wise use of the computational resources? How do help the next generation of computational chemists to be ready for the complex computing environments that they will face? While not claiming to have answers to all (or any!) of these questions\, we will explore some possible solutions and their implications as we go forward and face the current petascale and the future exascale challenges. These will be in the context of several Department of Energy funded computational chemistry Exascale Computing Projects (NWChemEx and GAMESS) and the NSF funded Molecular Sciences Software Institute. \nProf. Windus is being hosted by Prof. Geva (Chemistry). If you would like to meet with him Prof. Windus during her visit please email mcteja@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-theresa-windus-chemistry-iowa-state-university/
LOCATION:CHEM 1640\, 930 N University\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2017/09/Theresa-Windus.png
GEO:42.2780183;-83.7370191
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=CHEM 1640 930 N University Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=930 N University:geo:-83.7370191,42.2780183
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20171206T120000
DTEND;TZID=America/Detroit:20171206T130000
DTSTAMP:20260603T211818
CREATED:20230905T171416Z
LAST-MODIFIED:20230905T171416Z
UID:10000118-1512561600-1512565200@micde.umich.edu
SUMMARY:ME Faculty Candidate Seminar Series: Xun (Ryan) Huan\, Combustion Research Facility at Sandia National Laboratories
DESCRIPTION:Bio: Xun (Ryan) Huan is a postdoctoral researcher in the Combustion Research Facility at Sandia National Laboratories. He received a Ph.D. in Computational Science and Engineering from MIT Department of Aeronautics and Astronautics. He also has a master’s degree from MIT and a bachelor’s degree from the University of Toronto\, both in Aerospace Engineering. Xun’s research interests broadly revolve around uncertainty quantification\, decision-making under uncertainty\, data-driven modeling\, and optimization for engineering applications. Outside work\, he is an ice hockey player and a pilot. \nFinding the Most Informative Data Using Model-based Optimal Experimental Design\nExperimental data play a crucial role in developing and refining models of physical systems. However\, some experiments produce more useful data than others\, and well-chosen experiments can provide substantial resource savings. Optimal experimental design (OED) thus seeks to systematically quantify and maximize the value of experiments. We introduce general mathematical frameworks and algorithmic approaches for OED with nonlinear models. The formalism employs Bayesian statistics and an information-theoretic objective\, and rigorously defines the conditions under which batch experiments (experiments chosen simultaneously) and sequential experiments (forward-looking designs with data feedback) are truly optimal. Finding these optimal designs using conventional means is generally intractable. We develop practical numerical methods for OED by advancing computational techniques on several fronts\, including stochastic optimization\, polynomial chaos surrogate modeling\, approximate dynamic programming\, and transport maps. Using the overall algorithm\, we design combustion experiments for optimal learning of Arrhenius kinetic parameters\, and sequential sensor placement for contaminant source inversion.\n\n* Lunch won’t be provided but you are welcome to bring your own\n\n\n\nThis is a talk of potential interest to the MICDE community. The speakers in this seminar series are Faculty Candidates in the department of Mechanical Engineering for a Computational Science search that is being carried out with the active engagement of MICDE. We expect that the successful candidate will be a highly engaged affiliate of MICDE.
URL:https://micde.umich.edu/event/me-faculty-candidate-seminar-series-xun-ryan-huan/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://micde.umich.edu/wp-content/uploads/2023/02/XunRyanHuan-e1583777526832.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20171204T100000
DTEND;TZID=America/Detroit:20171204T110000
DTSTAMP:20260603T211818
CREATED:20230905T171416Z
LAST-MODIFIED:20230905T171416Z
UID:10000117-1512381600-1512385200@micde.umich.edu
SUMMARY:ME Faculty Candidate Seminar Series: Maziar Raissi\, Brown University
DESCRIPTION:Bio: Maziar Raissi is an Assistant Professor of Applied Mathematics (research) in the Division of Applied Mathematics at Brown University. He received his Ph.D. in Applied Mathematics & Statistics\, and Scientific Computations from University of Maryland — College Park in December 2016. Raissi’s expertise lies at the intersection of Probabilistic Machine Leaning\, Deep Learning\, and Data Drive Scientific Computing. \nHidden Physics Models: Machine Learning of Non-linear Partial Differential Equations\n\nA grand challenge with great opportunities is to develop a coherent framework that enables blending conservation laws\, physical principles\, and/or phenomenological behaviours expressed by differential equations with the vast data sets available in many fields of engineering\, science\, and technology. At the intersection of probabilistic machine learning\, deep learning\, and scientific computations\, this work is pursuing the overall vision to establish promising new directions for harnessing the long-standing developments of classical methods in applied mathematics and mathematical physics to design learning machines with the ability to operate in complex domains without requiring large quantities of data. To materialize this vision\, this work is exploring two complimentary directions: (1) designing data-efficient learning machines capable of leveraging the underlying laws of physics\, expressed by time dependent and non-linear differential equations\, to extract patterns from high-dimensional data generated from experiments\, and (2) designing novel numerical algorithms that can seamlessly blend equations and noisy multi-fidelity data\, infer latent quantities of interest (e.g.\, the solution to a differential equation)\, and naturally quantify uncertainty in computations. The latter is aligned in spirit with the emerging field of probabilistic numerics. \n\n\nThis is a talk of potential interest to the MICDE community. The speakers in this seminar series are Faculty Candidates in the department of Mechanical Engineering for a Computational Science search that is being carried out with the active engagement of MICDE. We expect that the successful candidate will be a highly engaged affiliate of MICDE.
URL:https://micde.umich.edu/event/me-faculty-candidate-seminar-series-maziar-raissi-brown-university/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://micde.umich.edu/wp-content/uploads/2023/02/MaziarRaissi.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20171201T083000
DTEND;TZID=America/Detroit:20171201T173000
DTSTAMP:20260603T211818
CREATED:20230905T171416Z
LAST-MODIFIED:20230905T171416Z
UID:10000105-1512117000-1512149400@micde.umich.edu
SUMMARY:2017 U-M Data Science Research Forum
DESCRIPTION:Forum Highlights \n\nOral and poster presentations on\n\nTheoretical foundations of data science\nData science methodology\nData science applications in any research domain\nSocial impact of data science research\n\n\n\n\nHow to engage industry workshop\n\nAdrian Fortino\, Partner (Mercury Fund)\nMike Psarouthakis\, Director (U-M Venture Center)\nKevyn Collins-Thompson\, Associate Professor\, U-M School of Information\nMike Cafarella\, Associate Professor\, U-M Computer Science Engineering\n\n\n\n\nKeynote by Chris Rozell\n\n\nNetworking Reception\n\nAll presentations will come from submissions in response to our call for abstracts\n Abstract Submission Deadline: October 23\, 2017\n We welcome submission from all U-M data science researchers (faculty\, staff\, trainees) \nPlease register for this event.  Please also see the call for abstracts for instruction\, and submit through the Abstract Submission Form. \nPreliminary Schedule
URL:https://micde.umich.edu/event/data-science-research-forum/
LOCATION:Michigan League\, 911 N. University\, Ann Arbor\, MI\, 48104\, United States
CATEGORIES:Conference,Data Science,Seminar
GEO:42.2796269;-83.7374973
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Michigan League 911 N. University Ann Arbor MI 48104 United States;X-APPLE-RADIUS=500;X-TITLE=911 N. University:geo:-83.7374973,42.2796269
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20171019T153000
DTEND;TZID=America/Detroit:20171019T163000
DTSTAMP:20260603T211818
CREATED:20230905T171415Z
LAST-MODIFIED:20230905T171415Z
UID:10000090-1508427000-1508430600@micde.umich.edu
SUMMARY:MICDE Seminar: Panos Papadopoulos\, Department of Mechanical Engineering\, University of California\, Berkeley
DESCRIPTION:Bio: Panos Papadopoulos is a Professor of Mechanical Engineering at the University of California\, Berkeley\, and director of the Computational Solid Mechanics Laboratory. After obtaining his Diploma in Civil Engineering from the Aristotle University\, Greece\, he moved to California to pursue his graduate studies. He obtained his M. Sc. and Ph.D. in Civil Engineering from UC Berkeley. His research involves experimental\, analytical and computational studies of several mechanics systems. Prof. Papadopoulus develops and applied the finite element method to problems in biomechanics\, dynamics of pseudo-rigid bodies\, mechanics of continues media\, plasticity\, materials science and contact mechanics. \nMultiscale Modeling in Continuum Mechanics: A connection to the Irving-Kirkwood procedure\nThis talk describes a method for extending the classical Irving-Kirkwood procedure used in statistical mechanics for extracting local fluxes to the problem of continuum-on-continuum multiscale modeling. Expressions for stress and heat flux derived here are contrasted to those obtained using the standard Hill-Mandel approach. The polar nature of the macroscopic solid and the role of multiscale invariance are also addressed in the context of this method. Applications are explored within the finite element-based homogenization of solids. \nProf. Papadopoulos is being hosted by Prof. Garikipati (Mechanical Engineering). If you would like to meet with him please send an email to mcteja@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-panos-papadopoulos-department-of-mechanical-engineering-university-of-california-berkeley/
LOCATION:Johnson Rooms\, Lurie Engineering Center\, 3rd Floor LEC 3213ABC\, 1221 Beal Ave.\, Ann Arbor\, MI\, United States
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2017/08/Panos-Papadopoulos.png
GEO:42.2914823;-83.7138452
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Johnson Rooms Lurie Engineering Center 3rd Floor LEC 3213ABC 1221 Beal Ave. Ann Arbor MI United States;X-APPLE-RADIUS=500;X-TITLE=1221 Beal Ave.:geo:-83.7138452,42.2914823
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20171019T120000
DTEND;TZID=America/Detroit:20171019T133000
DTSTAMP:20260603T211818
CREATED:20230905T171405Z
LAST-MODIFIED:20230905T171405Z
UID:10000115-1508414400-1508419800@micde.umich.edu
SUMMARY:Mechanical Engineering Seminar: Mark Owkes\, Department of Mechanical and Industrial Engineering\, Montana State University
DESCRIPTION:Bio: Mark Owkes is an Assistant Professor in the department of Mechanical and Industrial Engineering at Montana State University. He earned a BS in Mechanical Engineering from Clarkson University in 2008. He subsequently attained an MS in Mechanical Engineering from the University of Colorado at Boulder in 2011 under the direction of Prof. Olivier Desjardins. He continued his work under Prof. Desjardins at Cornell University where he earned his Ph.D. in May 2014. Mark’s research interests include the development of numerical methods for capturing gas-liquid interfaces in multiphase flow simulations. His simulations of primary atomization provide insight into the physical phenomena important in the break-up of a liquid jet into droplets. Notably\, he has developed both a level set and a volume-of-fluid interface capturing schemes and multiple approaches to compute the curvature of a gas-liquid interface which is important for accurate surface tension forces. \nGas-Liquid Flows: Numerical Methods through Simulations on Supercomputers\nGas-liquid flows exist within many engineering devices including fuel injectors\, wave energy extraction devices\, fire suppression systems\, and PEM fuel cells. Many of these flows are challenging to explore experimentally and computational fluid dynamics (CFD) simulations offer an alternative and useful approach to advance our understanding. For example\, the breakup of liquid fuel into droplets via atomization has a direct effect on combustion efficiency and pollutant formation\, yet a fundamental understanding of the complex process is absent. Laboratory experiments are inherently difficult to conduct because atomizing jets produce a large number of opaque droplets that hinder optical access to the breakup dynamics. With increasing computational resources and advancements in numerical methods\, computational fluid dynamics (CFD) has emerged as a promising tool to investigate the fundamental nature of atomization. In this presentation\, I will present an overview of difficulties arising due to the discontinuities that exist at the gas-liquid interface and recent advances in numerical methods that overcome these challenges. Then I will discuss efforts to improve the the usefulness of the very large data-sets that result from CFD simulations. Details on computing the curvature of a gas-liquid interface\, implementing contact line dynamics\, performing physics extraction\, and coupling gas-liquid flow calculations with uncertainty quantification we be discussed.
URL:https://micde.umich.edu/event/mechanical-engineering-seminar-mark-owkes-department-of-mechanical-and-industrial-engineering-montana-state-university/
LOCATION:1012 EECS\, 1301 Beal Ave\, Ann Arbor\, MI\, 48104\, United States
CATEGORIES:Seminar
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DTSTART;TZID=America/Detroit:20171003T160000
DTEND;TZID=America/Detroit:20171003T170000
DTSTAMP:20260603T211818
CREATED:20230905T171439Z
LAST-MODIFIED:20230905T171439Z
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SUMMARY:MICDE Seminar: Margaret Cheung\, Department of Physics\, University of Houston
DESCRIPTION:Bio: Margaret Cheung is an Associate Professor of Physics at the University of Houston. She graduated from the National Taiwan University with a bachelor’s degree in chemistry and received her Ph.D. in physics from the University of California\, San Diego. She carried out theoretical biological physics and bioinformatics research as a Sloan Postdoctoral Fellow at the University of Maryland and started her lab at the University of Houston in 2006. Professor Cheung’s research is in the field of protein folding inside a cell\, calmodulin dependent calcium signaling\, and quantum efficiency in artificial photosynthetic materials. She is particularly interested in developing coarse-grained models for protein dynamics in crowded systems\, creating multi-physics models that bridge dynamics across wide temporal and spatial scales\, and designing computational algorithms that effectively integrate novel high-performance resources. These systems can then be applied for understanding of biological function and for developing therapeutic strategies. She is a fellow of the American Physical Society and a Senior Scientist at the Center for Theoretical Biological Physics at Rice University. \nMolecular Underpinning of Postsynaptic Calmodulin-dependent Calcium Signaling\nCalcium (Ca2+) is exquisitely utilized by a cell for transducing external stimuli through its gradient of extracellular (~1000 μM) and intracellular (~0.1 μM) concentration. A broad spectrum of Ca2+ signals are encoded by protein calmodulin (CaM) through specific binding with various targets regulating CaM-dependent Ca2+ signaling pathways in neurons. I will focus on binding between CaM and two specific targets\, Ca2+/CaM-dependent protein kinase II (CaMKII) and neurogranin (Ng)\, as they antagonistically regulate CaM-dependent Ca2+ signaling pathways in neurons. I will show the impact of bound calmodulin (CaM)-target compound structure on the affinity of calcium (Ca2+) by integrating coarse-grained models and all-atomistic simulations with non-equilibrium physics. We discovered the molecular underpinnings of lowered affinity of Ca2+ for CaM in the presence of Ng by showing that the N-terminal acidic region of Ng peptide pries open the β-sheet structure between the Ca2+ binding loops particularly at C-domain of CaM\, enabling Ca2+ release. In contrast\, CaMKII peptide increases Ca2+ affinity for the C-domain of CaM by stabilizing the two Ca2+ binding loops. Through distinctive structural differences in the bound complexes of apoCaM-Ng13-49 and holoCaM-CaMKII\, CaM’s affinity for Ca2+ is delineated by its progressive mechanism of target binding. I will discuss them in the context of evolution and in the crowded environment. \nProf. Cheung is being hosted by Prof. Geva (Chemistry)
URL:https://micde.umich.edu/event/micde-seminar-margaret-cheung-department-of-physics-university-of-houston/
LOCATION:CHEM 1640\, 930 N University\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20170317T110000
DTEND;TZID=America/Detroit:20170317T120000
DTSTAMP:20260603T211818
CREATED:20230905T171438Z
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SUMMARY:MICDE Seminar: Yongjie Jessica Zhang\, Mechanical Engineering and Biomedical Engineering\, Carnegie Mellon University
DESCRIPTION:Bio: Yongjie Jessica Zhang is a Professor in Mechanical Engineering at Carnegie Mellon University with a courtesy appointment in Biomedical Engineering. She received her B.Eng. in Automotive Engineering\, and M.Eng. in Engineering Mechanics from Tsinghua University\, China; and M.Eng. in Aerospace Engineering and Engineering Mechanics and Ph.D. in Computational Engineering and Sciences from Institute for Computational Engineering and Sciences (ICES)\, The University of Texas at Austin. After staying two years at ICES as a postdoctoral fellow\, she joined CMU in 2007 as an assistant professor\, and then was promoted to an associate professor in 2012 and a full professor in 2016. Her research interests include computational geometry\, mesh generation\, computer graphics\, visualization\, finite element method\, isogeometric analysis and their application in computational biomedicine\, material sciences and engineering. She has co-authored over 140 publications in peer-reviewed journals and conference proceedings\, and received the Autodesk Best Paper Award 1st Place in SIAM Conference on Solid and Physical Modeling 2015\, the Best Paper Award in CompIMAGE’16 conference and one of the 5 Most Highly Cited Papers Published in Computer-Aided Design during 2014-2016. She recently published a book entitled “Geometric Modeling and Mesh Generation from Scanned Images” with CRC Press\, Taylor & Francis Group. She is the recipient of Presidential Early Career Award for Scientists and Engineers\, NSF CAREER Award\, Office of Naval Research Young Investigator Award\, USACM Gallagher Young Investigator Award\, Clarence H. Adamson Career Faculty Fellow in Mechanical Engineering\, George Tallman Ladd Research Award\, and Donald L. & Rhonda Struminger Faculty Fellow. \nImage-Based Mesh Generation and Volumetric T-Spline Modeling for Isogeometric Analysis with Engineering Applications\nWith finite element method and scanning technology seeing increased use in many research areas\, there is an emerging need for high-fidelity geometric modeling and mesh generation of spatially realistic domains. This talk will highlight research in three areas: image-based mesh generation for complicated domains\, trivariate spline modeling for isogeometric analysis\, as well as biomedical\, material sciences and engineering applications. First Prof. Zhang will present advances and challenges in image-based geometric modeling and meshing along with a comprehensive computational framework\, which integrates image processing\, geometric modeling\, mesh generation and quality improvement with multi-scale analysis at molecular\, cellular\, tissue and organ scales. Different from other existing methods\, the presented framework supports five unique features: high-fidelity meshing for heterogeneous domains with topology ambiguity resolved; multiscale geometric modeling for biomolecular complexes; automatic all-hexahedral mesh generation with sharp feature preservation; robust quality improvement for non-manifold meshes; and guaranteed-quality meshing. These unique capabilities enable accurate\, stable\, and efficient mechanics calculation for many biomedicine\, materials science and engineering applications. As a new advancement of traditional finite element method\, isogeometric analysis (IGA) was proposed to integrate design and analysis. In the second part of this talk\, she will present her latest research on volumetric T-spline parameterization for IGA applications. For arbitrary-topology objects\, we first build a polycube whose topology is equivalent to the input geometry and it serves as the parametric domain for the following trivariate T-spline construction. Boolean operations\, geometry skeleton and centroidal Voronoi tessellation based surface segmentation are used to preserve surface features. A parametric mapping is then used to build a one-to-one correspondence between the input geometry and the polycube boundary. After that\, we choose the deformed octree subdivision of the polycube as the initial T-mesh\, and make it valid through pillowing\, quality improvement\, and applying templates or truncated subdivision schemes to handle extraordinary nodes. Weighted and truncated T-spline basis functions are derived to enable analysis-suitability\, including partition of unity and linear independence. The developed pipelines have been incorporated into commercial software such as Rhino and Abaqus. \nProf. Zhang is being hosted by Prof. Garikipati (Mechanical Engineering)
URL:https://micde.umich.edu/event/micde-seminar-yongjie-jessica-zhang-mechanical-engineering-and-biomedical-engineering-carnegie-mellon-university/
LOCATION:1200 EECS\, 1301 Beal Ave.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20170308T140000
DTEND;TZID=America/Detroit:20170308T150000
DTSTAMP:20260603T211818
CREATED:20230905T171438Z
LAST-MODIFIED:20230905T171438Z
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SUMMARY:SC2/MICDE Seminar: Eric Jankowski\, Materials Science and Engineering\, Boise State University
DESCRIPTION:Bio: Eric Jankowski is an assistant professor of Materials Science and Engineering at Boise State University. He earned his PhD in Chemical Engineering from the University of Michigan in 2012\, where he developed computational tools to study the self-assembly of nanoparticles. These tools leveraged graphics processors to accelerate computations and provided insight into systems of both theoretical and practical importance. Dr. Jankowski began focusing on renewable energy generation during his postdoctoral positions at the University of Colorado and the National Renewable Energy Laboratory. At these postdocs\, Dr. Jankowski applied techniques he developed during his thesis to understand factors that determine the ordering of molecules in organic solar cells. \nThis is a joint seminar of the Scientific Computing Student Club and MICDE\, sponsored in part by U-M Rackham Graduate School.   \n  \nCobbling together computational components to engineer inexpensive plastic solar panels\nIn order to meet projected global energy demands over the next 25 years\, the equivalent of building a 1GW power plant each day is needed. Existing clean power generation technologies can meet this demand in principle\, but their relatively large short-term costs have limited widespread adoption. In this work we explain manufacturing strategies for organic (plastic) solar panels that overcome economic barriers to adoption by optimizing the structure of the organic active layer responsible for generating electricity. We perform coarse-grained molecular dynamics simulations accelerated with graphics processing units to determine the thermodynamically stable morphologies for a variety of candidate ingredients. Using these morphologies we perform kinetic Monte Carlo charge transport simulations to determine which morphologies are better candidates for solar devices. The simulation pipeline developed here combines computational tools developed for solving unrelated problems\, and we discuss the evolving landscape of scientific computing education and how it overlaps with this work. \n 
URL:https://micde.umich.edu/event/sc2micde-seminar-eric-jankowski-material-science-and-engineering-boise-state-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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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20170307T160000
DTEND;TZID=America/Detroit:20170307T170000
DTSTAMP:20260603T211818
CREATED:20230905T171438Z
LAST-MODIFIED:20230905T171438Z
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SUMMARY:MICDE Seminar: Michael Eldred\, Computation\, Computers\, Information\, and Mathematics Center\, Sandia National Laboratories
DESCRIPTION:Bio: Michael Eldred is a Distinguished Member of the Technical Staff in the Optimization and Uncertainty Quantification Department within the Computation\, Computers\, Information\, and Mathematics Center at Sandia National Laboratories. He received his B.S. in Aerospace Engineering from Virginia Tech in 1989\, his M.S.E. and Ph.D. in Aerospace Engineering from the University of Michigan in 1990 and 1993. Mike led the DAKOTA project\, a “… toolkit that provides a flexible\, extensible interface between analysis codes and iterative systems analysis methods…”\, for 15 years (1994-2009) and now leads algorithm research and development activities related to DAKOTA. Mike’s research interests include uncertainty quantification\, design under uncertainty\, surrogate-based optimization\, and high-performance computing\, with application to stockpile stewardship and energy initiatives through the NNSA ASC\, DOE ASCR\, and DOE SciDAC programs. \nMike is an Associate Fellow of the American Institute of Aeronautics and Astronautics (AIAA) and a member of the Society for Industrial and Applied Mathematics (SIAM)\, the International Society for Structural and Multidisciplinary Optimization (ISSMO)\, and the United States Association for Computational Mechanics (USACM). He currently serves as a member of the AIAA Nondeterministic Approaches Technical Committee and on the editorial board for the International Journal for Uncertainty Quantification. A number of his publications are available on the DAKOTA web site. \nTitle: Multilevel-Multifidelity Approaches for Uncertainty Quantification and Design\nIn the simulation of complex physics\, multiple model forms of varying fidelity and resolution are commonly available. In computational fluid dynamics\, for example\, common model fidelities include potential flow\, inviscid Euler\, Reynolds-averaged Navier-Stokes\, and large eddy simulation\, which may be further augmented by subgrid-scale model selections and spatio-temporal discretization levels. In this presentation\, we focus on novel algorithms that simultaneously exploit multiple model forms and multiple resolutions\, both for uncertainty quantification (UQ) and for optimization under uncertainty (OUU). These hybrid methods exploit multifidelity methods across the model form hierarchy in combination with multilevel accelerators across an associated discretization hierarchy\, manifesting as multilevel control variate Monte Carlo and multilevel polynomial expansion methods in the UQ case and recursive trust-region and multigrid optimization in the OUU case. These techniques will be demonstrated for both model problems and engineered systems\, and will be placed within the broader context of algorithm research and development within the Dakota project at Sandia. \nDr. Eldred is being hosted by Prof. Duraisamy (Aerospace Engineering) 
URL:https://micde.umich.edu/event/micde-seminar-michael-eldredcomputation-computers-information-and-mathematics-center-sandia-national-laboratories/
LOCATION:1008 FXB\, 1320 Beal Ave\, Ann Arbor\, MI\, 48109
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20170214T150000
DTEND;TZID=America/Detroit:20170214T160000
DTSTAMP:20260603T211818
CREATED:20230905T171440Z
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SUMMARY:MICDE Seminar: Steven White\, Physics & Astronomy\, University of California Irvine
DESCRIPTION:Bio: Steven White did his bachelor’s degree at the University of California in San Diego and received his Ph.D. from Cornell University. Early in his career he was awarded a National Science Foundation fellowship\, and an IBM postdoctoral fellowship. He’s been named an American Physical Society fellow\, and a fellow of the American Association for the Advancement of Science\, and of the American Academy of Arts and Science\, among others. Professor White is most known for inventing the Density Matrix Renormalization Group (DMRG)\, a numerical variation technique for high accuracy calculations of the low energy physics of quantum many-body systems. In 2003 he won the American Physical Society Aneesur Rahman prize\, a recognition of outstanding achievement in computational physics research “…for his development\, application\, and dissemination of the DMRG method”. He has published over one hundred and seventy papers on this and related subjects. \nTensor Network methods for Electronic Structure\nOur conventional picture of wave functions living in an exponentially large Hilbert space is both impractical for solving many particle systems and conceptually lacking: in recent years we have come to understand that physical states of matter live in an infinitesimal corner of Hilbert space\, characterized primarily by low entanglement. Tensor networks are the natural language to express low entanglement wave functions\, giving an exponentially compressed description of ground states. The density matrix renormalization group (DMRG) and other tensor network algorithms have had tremendous success in simulating quantum lattice models.The key challenge in translating these methods to electronic structure is the need to represent continuum space in an efficient way. After an introduction to tensor networks\, I’ll present a new DMRG-based approach suitable for the electronic structure of long molecules. Our sliced-basis DMRG method produces near-exact ground states within its basis\, and has a computation time which is linear in the length of the molecule. We are implementing SBDMRG for chains of hydrogen atoms\, where we have been able to simulate up to 1000 atoms in a minimal basis. \nProf. White is being hosted by Prof. Emanuel Gull (Chemistry)
URL:https://micde.umich.edu/event/micde-seminar-steven-white-physics-astronomy-university-of-california-irvine/
LOCATION:340 West Hall\, 1085 South University 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:20170203T100000
DTEND;TZID=America/Detroit:20170203T110000
DTSTAMP:20260603T211818
CREATED:20230905T171440Z
LAST-MODIFIED:20230905T171440Z
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SUMMARY:MICDE Seminar: Anna Krylov\, Chemistry\, University of Southern California
DESCRIPTION:Bio: Anna Krylov is a Gabilan Distinguished Professor in Science and Engineering\, Chemistry at the University of Southern California. She received her M.Sc. in Chemistry from Moscow State University and later her Ph.D. from The Hebrew University of Jerusalem. Upon completing her Ph.D. in 1996 (summa cum laude)\, she joined the group of Prof. Martin Head-Gordon at the University of California\, Berkeley as a postdoctoral research associate\, where she first became involved with electronic structure method development. In 1998\, she joined Department of Chemistry at USC. Currently\, Prof. Krylov leads a research group focused on theoretical modeling of open shell and electronically excited species. She is the head of the Center for Computational Studies of Electronic Structure and Spectroscopy of Open-Shell and Electronically Excited Species\, iOpenShell\, supported by the National Science Foundation (2005–2011) and the University of Southern California. She is developing robust black-box methods aiming to describe complicated multi-configurational wave functions in a single-reference formalism\, such as coupled-cluster and equation-of-motion (or linear response) approaches. She has developed the spin-flip approach\, which extends coupled-cluster and density functional methods to diradicals\, triradicals\, and bond-breaking. Using computational chemistry tools\, and in collaboration with numerous experimental groups\, Krylov is also investigating the role that radicals and electronically excited species play in such diverse areas as combustion\, gas- and condensed-phase chemistry\, solar energy applications\, bioimaging\, and ionization-induced processes in biology. She has co-authored more than 120 publications and has delivered more than 130 invited lectures. (Source https://en.wikipedia.org/wiki/Anna_Krylov) \nFission of entangled spins: Electronic structure perspective\nSinglet fission (SF)\, a process in which one singlet excited state is converted into two triplet states\, is of interest in the context of organic photovoltaic technology. Owing to its technological significance\, the mechanism of SF has been vigorously investigated. Yet\, the design principles for materials capable of efficient SF remain elusive. The main challenge faced by theory is a complex and intricate electronic structure of the process\, which involves non-adiabatic transitions between strongly correlated states. This lecture will discuss electronic structure of the relevant states\, the nature of non-adiabatic couplings\, and the connection between electronic factors and rates\, emphasizing the methodological aspects of the problem. The utility of theory will be illustrated by examples. Recent experimental and theoretical studies of SF in covalently linked tetracene dimers shed light on the effect of the linkers on the electronic factors and SF rates\, illuminating the role of through-space and through-bond interactions between the chromophores. The results highlight the importance of integrative approaches that evaluate the overall rate\, rather than focus on specific electronic factors\, such as energies or couplings.
URL:https://micde.umich.edu/event/micde-seminar-anna-krylov-chemistry-university-of-southern-california/
LOCATION:CHEM 1640\, 930 N University\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20170202T163000
DTEND;TZID=America/Detroit:20170202T173000
DTSTAMP:20260603T211818
CREATED:20230905T171439Z
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SUMMARY:[SC2] Launch of 2017 Visualization Challenge + Presentation: Simple Data Management with Signac
DESCRIPTION:Simon Adorf (PhD Candidate\, Chem. Eng.) will give a presentation about “Simple Data Management with Signac“. \nABSTRACT: We will give a brief introduction to the signac data management framework for agile computational workflows\, followed by presenting interactive examples using jupyter notebooks hosted online. The signac framework aids in the management of large and heterogeneous data spaces. It provides a simple and robust data model to create a well-defined indexable storage layout for data and metadata. This makes it easier to operate on large data spaces\, streamlines post-processing and analysis and makes data collectively accessible. \nEveryone is encouraged to bring a laptop in order to be able to follow along. \n+ \nThe Scientific Computing Student Club\, partnered with MICDE\, the U-M 3D Lab and NVIDIA\, will officially launch the 2017 NVIDIA Visualization Challenge aimed for students to use the latest visualization tools and technology to show their research data in creative ways. The first prize will include sponsorship to show their work at the Supercomputing ’17 Visualization Showcase\, and more. Join us at the meeting to learn more. \nSponsored by \n 
URL:https://micde.umich.edu/event/sc2-launching-of-2017-visualization-challenge-presentation-simple-data-management-with-signac/
LOCATION:1311 EECS\, 1301 Beal Ave.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20170127T120000
DTEND;TZID=America/Detroit:20170127T130000
DTSTAMP:20260603T211818
CREATED:20230905T171439Z
LAST-MODIFIED:20230905T171439Z
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SUMMARY:MICDE Seminar: Vipin Kumar\, Computer Science and Engineering\, University of Minnesota
DESCRIPTION:Bio: Vipin Kumar is a Regents Professor and holds William Norris Chair in the department of Computer Science and Engineering  at the University of Minnesota.  His research interests include data mining\, high-performance computing\, and their applications in Climate/Ecosystems and health care. He is currently leading an NSF Expedition project on understanding climate change using data driven approaches.  He has authored over 300 research articles\, and co-edited or coauthored 10 books including the widely used text book “Introduction to Parallel Computing”\, and “Introduction to Data Mining”.  Kumar co-founded SIAM International Conference on Data Mining and served as a founding co-editor-in-chief of Journal of Statistical Analysis and Data Mining (an official journal of the American Statistical Association).  Kumar is a Fellow of the ACM\, IEEE and AAAS.  He received the Distinguished Alumnus Award from the Indian Institute of Technology (IIT) Roorkee (2013) and the Distinguished Alumnus Award from the Computer Science Department\, University of Maryland College Park (2009).  Kumar’s foundational research in data mining and high performance computing has been honored by the ACM SIGKDD 2012 Innovation Award\, which is the highest award for technical excellence in the field of Knowledge Discovery and Data Mining (KDD)\, and the 2016 IEEE Computer Society Sidney Fernbach Award\, one of IEEE Computer Society’s highest awards. \nBig Data in Climate: Opportunities and Challenges for Machine Learning and Data Mining\nThis talk will present an overview of research being done in a large interdisciplinary project on the development of novel data mining and machine learning approaches for analyzing massive amount of climate and ecosystem data now available from satellite and ground-based sensors\, and physics-based climate model simulations. These information-rich data sets offer huge potential for monitoring\, understanding\, and predicting the behavior of the Earth’s ecosystem and for advancing the science of global change. This talk will discuss challenges in analyzing such data sets and some of our research results in mapping the dynamics of surface water globally as well as detecting deforestation and fires in tropical forests using data from Earth observing satellites. \nResearch funded by the NSF Expeditions in Computing Program and  NASA \nPizza lunch will be provided
URL:https://micde.umich.edu/event/micde-seminar-vipin-kumar-computer-science-and-engineering-university-of-minnesota/
LOCATION:1008 EECS\, 1301 Beal Ave.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
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END:VEVENT
END:VCALENDAR