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DTSTART;TZID=America/Detroit:20210301T130000
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SUMMARY:MICDE Seminar: Santo Fortunato\, Director of the Indiana University Network Science Institute (IUNI)\, Professor\, School of Informatics\, Computing\, and Engineering (SICE)\, Indiana University at Bloomington
DESCRIPTION:About Dr. Fortunato: Santo Fortunato is the Director of the Indiana University Network Science Institute (IUNI) and a faculty at Luddy School of Informatics\, Computing and Engineering. Previously he was professor of complex systems at the Department of Computer Science of Aalto University\, Finland. Prof. Fortunato got his PhD in Theoretical Particle Physics at the University of Bielefeld In Germany. He then moved to the field of complex systems\, via a postdoctoral appointment at Luddy School of Informatics\, Computing and Engineering of Indiana University. His current focus areas are network science\, especially community detection in graphs\, computational social science\, science of science\, climate change. His research has been published in leading journals\, including Nature\, Science\, PNAS\, Physical Review Letters\, Reviews of Modern Physics\, Physics Reports and has collected over 33\,000 citations (Google Scholar). His review article Community detection in graphs (Physics Reports 486\, 75-174\, 2010) is one of the best known and most cited papers in network science. He received the Young Scientist Award for Socio- and Econophysics 2011\, a prize given by the German Physical Society\, for his outstanding contributions to the physics of social systems. He is the Founding Chair of the International Conference on Computational Social Science (IC2S2) and Chair of Networks 2021\, the first merger of the NetSci and the Sunbelt conferences\, possibly the largest ever event in network science. \nCOMMUNITY DETECTION IN NETWORKS: Complex systems typically display a modular structure\, as modules are easier to assemble than the individual units of the system\, and more resilient to failures. In the network representation of complex systems\, modules\, or communities\, appear as subgraphs whose nodes have an appreciably larger probability to get connected to each other than to other nodes of the network. In this talk I will discuss three main issues in this area. I will address the limits of the most popular class of clustering algorithms\, those based on the optimization of a global quality function\, like modularity maximization. Testing algorithms is probably the single most important issue of network community detection\, as it implicitly involves the concept of community\, which is ill-defined. I will discuss the importance of using realistic benchmark graphs with built-in community structure. Finally\, I will introduce an increasingly popular post-processing technique that allows to “average” the results of stochastic clustering algorithms\, improving their quality: consensus clustering. \n\nWatch the full webinar recording. \nThe MICDE Winter 2021 Seminar Series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-santo-fortunato-director-of-the-indiana-university-network-science-institute-iuni-professor-school-of-informatics-computing-and-engineering-sice-indiana-university-at-blooming/
LOCATION:Zoom Event\, MI\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
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DTSTART;TZID=America/Detroit:20210311T140000
DTEND;TZID=America/Detroit:20210311T150000
DTSTAMP:20260607T002018
CREATED:20230905T171300Z
LAST-MODIFIED:20230905T171300Z
UID:10000457-1615471200-1615474800@micde.umich.edu
SUMMARY:MICDE Seminar: Warren B. Mori\, Professor\, Physics and Astronomy\, Electrical and Computer Engineering\, University of California\, Los Angeles
DESCRIPTION:WATCH THE RECORDING HERE. \nBio: Warren B. Mori is a Distinguished Professor in the departments of Physics and Astronomy and of Electrical and Computer Engineering a UCLA. He received his BS from UC Berkeley in 1981\, and his M.S. and Ph.D. from UCLA in 1984 and 1987\, respectively. He has been at UCLA from 1981 until today. He served as the Director of the UCLA Institute for Digital Research and Education from 2006 until 2021. His current research interests are in advanced computing\, particle-in-cell simulations of plasmas\, basic plasma physics\, high intensity laser and beam plasma interactions\, plasma based accelerators and light sources\, nonlinear optics of plasmas\, inertial fusion science\, and high energy density science. He is the coauthor of more than 400 publications on a variety of topics in plasma and computational physics. He is a fellow of both APS (1997) and IEEE (2009) and is a current member of both societies. In 1987 he received the International Center for Theoretical Physics Medal for Excellence in Nonlinear Plasma Physics by a Young Researcher was a recipient of the Advanced Accelerator Concepts Prize in 2016 for\, “ his leadership and pioneering contributions in theory and particle-in-cell code simulations of plasma based particle acceleration.” In 2020 he received the APS James Clerk Maxwell prize for\, “leadership in and pioneering contributions to the theory and kinetic simulations of nonlinear processes in plasma-based acceleration and relativistically intense laser and beam plasma interactions. \nPLASMA BASED ACCELERATION AND THE ROLE OF HIGH FIDELITY SIMULATIONS IN ITS DEVELOPMENT\nParticle accelerators are critical components of high energy physics colliders and x-ray free electron lasers (XFELs)\, which are complex and expensive tools for scientific discovery. To reduce the size and cost of these tools there is active research aimed at finding new technologies for compact accelerators. One such possibility is the use of plasma waves which phase velocities near the speed of light that can be excited as wakefields behind intense lasers and particle beams as they traverse tenuous plasmas. These ideas are the basis for the field of plasma based acceleration (PBA). In this talk I will describe how PBA works\, and how high fidelity computer simulations have and are playing a critical role in its development. I will also describe the simulation methods and their associated algorithms. Last\, I will offer some perspectives for the future of plasma based acceleration and the simulation methods that will critical role in this future. Work supported by DOE and NSF.\n \n\nThis seminar is co-presented by the Michigan Institute for Computational Discovery & Engineering and the Michigan Institute for Plasma Science and Engineering. Dr. Mori will be hosted by Professor Alec Thomas\, Professor of Nuclear Engineering and Radiological Sciences\, Electrical Engineering and Computer Science\, and Physics. \nRegister for this event via Zoom to receive an email with the link and passcode to connect. Note: You may register after the event has started. \nThe MICDE Winter 2021 Seminar Series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-warren-mori-professor-physics-and-astronomy-electrical-and-computer-engineering-university-of-california-los-angeles/
LOCATION:Zoom Event\, MI\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
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DTSTART;TZID=America/Detroit:20210318T110000
DTEND;TZID=America/Detroit:20210318T120000
DTSTAMP:20260607T002018
CREATED:20230905T171300Z
LAST-MODIFIED:20230905T171300Z
UID:10000462-1616065200-1616068800@micde.umich.edu
SUMMARY:MICDE Seminar: Udo von Toussaint\, PD\, Group Leader at the Max-Planck-Institute for Plasmaphysics in Garching\, Divison Numerical Methods for Plasmaphysics
DESCRIPTION:WATCH THE RECORDING HERE. \nBio: Dr. Udo v. Toussaint earned his PhD in Physics at the University of Bayreuth in 2000. He then worked as a Postdoctoral Researcher at NASA Ames (RIACS)\, in Mountain View\, CA from 2000-2002.  Since 2003\, Dr. von Toussaint has been a Scientist at the Max-Planck Institute for Plasmaphysics in Garching. Dr. von Toussaint is also editor of the ‘Entropy’ journal. \nBesides plasma-wall interaction\, his research interests are focussed on the design of optimal analysis and measurement strategies (Bayesian experimental design) for computer- and physics experiments. This encompasses modern concepts of uncertainty quantification (UQ) of complex computer codes (e.g. Plasma-wall simulations) as well as active-learning systems\, which dynamically decide which action (e.g. measurement of a specific spectral line) might yield the most informative data based on the results from previous actions. This is addressed with Machine Learning techniques\, e.g. Hidden Markov Models (HMM)\, neutral networks or bayesian acyclic graphs and complemented by numerical methods like Markov Chain Monte Carlo (MCMC)\, sequential optimization or polynomial chaos expansion. \nA BAYESIAN APPROACH TO ARTIFICIAL NEURAL NETWORKS:  Artificial Neural networks (ANN) are famous for their advantageous flexibility for problems when there is insufficient knowledge to set up a proper model. On the other hand\, this flexibility can cause overfitting and can hamper the generalization and stability of ANNs. Many approaches to regularize ANNs have been suggested (e.g. L1- or L2-norm based regularization) but most of them are based on ad hoc arguments. Employing the principle of transformation invariance\, a general prior for feed-forward networks can be derived. This regularization prior not only favours cell and layer pruning but enable also a consistent Bayesian approach: Relying on Occam’s razor we demonstrate (as a proof of concept) how an ANN can be applied even in the >absence< of available training data. The relation to the concept of automatic relevance detection will be discussed. \n\nThe MICDE Winter 2021 Seminar Series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nDr. von Toussaint will be hosted by Professor Xun Huan\, Assistant Professor of Mechanical Engineering. \nRegister for this event via Zoom to receive an email with the link and passcode to connect. Note: You may register after the event has started. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-udo-von-toussaint-pd-group-leader-at-the-max-planck-institute-for-plasmaphysics-in-garching-divison-numerical-methods-for-plasmaphysics/
LOCATION:Zoom Event\, MI\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
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DTSTART;TZID=America/Detroit:20210319T150000
DTEND;TZID=America/Detroit:20210319T160000
DTSTAMP:20260607T002018
CREATED:20230905T171444Z
LAST-MODIFIED:20230905T171444Z
UID:10000464-1616166000-1616169600@micde.umich.edu
SUMMARY:AIM/MICDE Seminar: Daniel Lecoanet\, Postdoctoral Fellow\, Princeton Center for Theoretical Science\, Astrophysical Sciences\, Princeton University
DESCRIPTION:Bio: Dr. Lecoanet earned a Bachelor of Science degree in Mathematics from the University of Wisconsin at Madison\, a Master’s degree in Applied Mathematics from the University of Cambridge\, and a PhD in Physics from the University of California\, Berkeley. He currently holds a joint postdoc position at the Princeton Center for Theoretical Science and as a Lyman Spitzer\, Jr. fellow at the Department of Astrophysical Sciences. Dr. Lecoanet works primarily on Astrophysical and Geophysical Fluid Dynamics. He is a core developer for Dedalus. \nPROBING THE CORES OF MASSIVE STARS THROUGH THEIR SURFACE: Stars are opaque\, which makes it difficult to study their interiors. Recent space-based telescopes have led to the new field of asteroseismology: by measuring global oscillation modes of a star\, you can infer its interior properties. Massive stars have convection in their cores which can generate waves\, which might be detectable at the surface. In the first part of this talk\, I will describe a heuristic way of estimating wave generation by convection\, and compare it to high-resolution numerical simulations in Cartesian geometry. To make quantitative predictions to compare with observations\, one must run simulations in spherical geometry. In the second part of my talk\, I will present a new spectral algorithm for solving nearly arbitrary\, tensorial PDEs in spherical coordinates. The challenge is to devise bases which respect regularity conditions at r=0\, which depend on the rank of the tensor. The algorithm can be easily applied to the problem of wave generation by convection in stars\, as well as a wide range of other problems in stellar astrophysics\, core geophysics\, and planetary sciences. \n\nThis seminar is co-presented by Applied and Interdisciplinary Mathematics program\, and the Michigan Institute for Computational Discovery & Engineering. Dr. Lecoanet will be hosted by Professor Charlie Doering\, the Nicholas D. Kazarinoff Collegiate Professor of Complex Systems\, Mathematics and Physics\, and Director of the Center for the Study of Complex Systems. \nRegister for this event to receive Zoom login information. \nThe MICDE Winter 2021 Seminar Series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-daniel-lecoanet-postdoctoral-fellow-princeton-center-for-theoretical-science-astrophysical-sciences-princeton-university/
LOCATION:Zoom Event\, MI\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
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