BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Michigan Institute for Computational Discovery and Engineering - ECPv6.17.1//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-ORIGINAL-URL:https://micde.umich.edu
X-WR-CALDESC:Events for Michigan Institute for Computational Discovery and Engineering
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/Detroit
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20170312T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20171105T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20180311T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20181104T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20190310T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20191103T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20200308T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20201101T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20210314T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20211107T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20220313T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20221106T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20230312T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20231105T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20240310T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20241103T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20250309T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20251102T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20260308T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20261101T060000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20251024T143000
DTEND;TZID=America/Detroit:20251024T160000
DTSTAMP:20250926T201218Z
CREATED:20250926T143948Z
LAST-MODIFIED:20250926T201218Z
UID:10000836-1761316200-1761321600@micde.umich.edu
SUMMARY:Graduate Opportunities in Computational and Data Science Information Session
DESCRIPTION:The educational programs represented will be: \n\nPhD in Scientific Computing (MICDE)\nGraduate Certificate in Computational Discovery & Engineering (MICDE)\nGraduate Certificate in Computational Neuroscience (MICDE)\nGraduate Certificate in Data Science (MIDAS)\n\nThese programs are open to U-M graduate students with an interest in scientific computing or data science. If you have any questions about these programs or about the information session\, please reach out to MICDE (micde-contact@umich.edu) or MIDAS (midas-contact@umich.edu). \nPlease register to attend
URL:https://micde.umich.edu/event/graduate-opportunities-in-computational-and-data-science-2025-north/
LOCATION:1670 Bob and Betty Beyster Building\, 2260 Hayward Street\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Sessions
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2025/09/2025-Happening@UMich-graphic.png
GEO:42.2930138;-83.716372
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=1670 Bob and Betty Beyster Building 2260 Hayward Street Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=2260 Hayward Street:geo:-83.716372,42.2930138
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20251002T140000
DTEND;TZID=America/Detroit:20251002T150000
DTSTAMP:20251003T210107Z
CREATED:20250909T223056Z
LAST-MODIFIED:20251003T210107Z
UID:10000830-1759413600-1759417200@micde.umich.edu
SUMMARY:MICDE - MSE Seminar: Michael Herbst\, Swiss Federal Institute of Technology in Lausanne
DESCRIPTION:Bio: Michael Herbst obtained a PhD in Theoretical Chemistry from Heidelberg University in 2018\, after which he moved on to two postdoctoral research stays in Applied Mathematics with Éric Cancès (École des Ponts\, France) and Benjamin Stamm (RWTH Aachen\, Germany). Since March 2023\, he has been a tenure-track assistant professor in the Institute of Mathematics and the Institute of Materials at EPFL. His current research spans broadly in the field of materials simulations concerning numerical error control and uncertainty quantification of first-principle simulations\, as well as the propagation of such errors during inverse materials design or when training machine learning models. \nAlgorithmic differentiation (AD) for plane-wave DFT\nAbstract: Reliable algorithmic differentiation techniques offer great promise for the inverse design of materials and functionals\, as well as the propagating uncertainties from functionals to DFT quantities of interest. Over the past years\, considerable effort has been spent on equipping the density-functional toolkit (DFTK\, https://dftk.org) with algorithmic differentiation capabilities. Prof. Herbst will present some of the required algorithmic developments\, e.g. to efficiently compute such DFT derivatives in numerically challenging metallic systems. Furthermore\, he will highlight the conceptual difficulties associated with applying AD to plane-wave DFT and discuss our recent results\, which demonstrate the current state of AD in DFTK for error estimation\, inverse design\, and implementing new functionality. \nRead more
URL:https://micde.umich.edu/event/micde-seminar-michael-herbst/
LOCATION:1670 Bob and Betty Beyster Building\, 2260 Hayward Street\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Micde,Micde Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2025/09/Michael-F.-Herbst.png
GEO:42.2930138;-83.716372
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=1670 Bob and Betty Beyster Building 2260 Hayward Street Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=2260 Hayward Street:geo:-83.716372,42.2930138
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20231027T160000
DTEND;TZID=America/Detroit:20231027T170000
DTSTAMP:20231112T073101Z
CREATED:20230913T002456Z
LAST-MODIFIED:20231112T073101Z
UID:10000627-1698422400-1698426000@micde.umich.edu
SUMMARY:MICDE / ME Seminar: Erik Draeger\, Director of the High Performance Computing Innovation Center and RADIUSS project at Lawrence Livermore National Laboratory
DESCRIPTION:Bio: Dr. Erik Draeger is the Director of the High Performance Computing Innovation Center and RADIUSS project at Lawrence Livermore National Laboratory as well as the Scientific Computing group leader at the Center for Applied Scientific Computing. He is also the Deputy Director of Application Development for the Exascale Computing Project\, jointly overseeing a portfolio of 22 Office of Science applications\, 4 NNSA applications\, and 7 co-design projects. Erik earned a Bachelor’s degree in Physics from the University of California\, Berkeley in 1995 and received a PhD in theoretical condensed matter physics from the University of Illinois\, Urbana-Champaign in 2001. He has over a decade of experience developing scientific applications to achieve maximum scalability and time to solution on next-generation architectures. He has been a finalist for the Gordon Bell Prize six times since 2005 and won the prize in 2006. \nSupercomputing at the exascale and beyond: future trends and challenges\nFor the past seven years\, the U.S. Department of Energy’s Exascale Computing Project (ECP) has funded a comprehensive push to refactor 24 application projects to efficiently utilize exascale computing hardware to solve a varied set of complex science and engineering problems. Ambitious performance and capability goals were set for each application that demanded end-to-end rethinking of traditional approaches. Through detailed performance analysis\, integration with optimized co-design frameworks and software libraries\, and the use of programming abstractions to manage data placement and kernel execution\, ECP applications recently demonstrated substantial capability and performance improvements on newly-available exascale machines. Despite significant diversity in the methods and algorithms underlying the ECP application portfolio\, several common themes emerged in how to best adapt computational workloads to heterogeneous architectures. In this talk\, an overview of best practices and lessons learned on effectively utilizing exascale hardware from the perspective of ECP applications will be presented. Strategies for developing portable\, performant code will be discussed and examples of reexamining traditional algorithms and methods will be described. Armed with this knowledge\, researchers can go beyond simply surviving an uncertain and turbulent computing future to instead leading a wave of scientific and computational innovation as traditional approaches are reexamined and new approaches adopted. \n  \n\n  \nThe MICDE Fall 2023 Seminar Series is open to all. University of Michigan faculty and students interested in predicting and explaining the properties of materials using computer simulation are encouraged to attend. \nThis seminar is cohosted by the Michigan Institute for Computational Discovery & Engineering (MICDE) and the Department of Mechanical Engineering (ME). Dr. Draeger will be hosted by Dr. Vikram Gavini\, Professor of Mechanical Engineering. \nThis is an in-person event. \nGraduate Certificate in Computational Discovery and Engineering\, and MICDE fellows\, please use this form to record your attendance. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-me-seminar-erik-draeger-director-hpc-innovation-center-llnl-deputy-director-doe-exascale-computing-project/
LOCATION:1670 Bob and Betty Beyster Building\, 2260 Hayward Street\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,Micde,Micde Seminar,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/09/Erik-Draeger.png
GEO:42.2930138;-83.716372
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=1670 Bob and Betty Beyster Building 2260 Hayward Street Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=2260 Hayward Street:geo:-83.716372,42.2930138
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20181001T160000
DTEND;TZID=America/Detroit:20181001T170000
DTSTAMP:20230905T171420Z
CREATED:20230905T171420Z
LAST-MODIFIED:20230905T171420Z
UID:10000156-1538409600-1538413200@micde.umich.edu
SUMMARY:MICDE Seminar: Sanjay Padhi\, AWS Research and Technical Computing
DESCRIPTION:Bio: Dr. Sanjay Padhi\, leads the AWS Research Initiatives including AWS’s federal initiatives with the National Science Foundation. He is a physicist and Adjunct Professor at Brown University. Dr. Padhi has more than 15 years of experience in large-scale distributed computing\, Data Analytics and Machine Learning. He is the co-creator of the Workload Management System currently used for all the data processing and simulations by CMS\, one of the largest experiments in the world at CERN\, consisting of more than 180 institutions across 40 countries. He also co-founded the ZEUS Computing Grid project at Deutsches Elektronen-Synchrotron (DESY)\, Germany before joining CERN. Sanjay obtained his Ph.D from McGill University in High Energy Physics\, co-author of more than 900 publications and is also currently appointed by the Dean of Faculty as an Adjunct Professor of Physics at Brown University. \nPredictive Analytics using Amazon Web Services\nOne of the most explored features of Big Data is predictive analytics. Predictive analytics is a set of techniques that are fundamental to large organizations like Amazon. Methods such as Machine Learning are used in many aspects of life\, including health care\, education\, financial modeling\, and marketing. Analytics on Big Data has given rise to various “smart” projects\, such as Connected Intersections\, Smart Cities\, and Smart Health. This talk will provide a range of such studies using predictive analytics including detailed overview of methods such as Machine Learning (ML) and Deep Learning using AWS. Fully managed Artificial Intelligence (AI) services to help researchers build\, train and deploy ML models in various domains including Computer Vision and Natural Language Processing (NLP) will also be outlined. Supervised and unsupervised based learning frameworks and its implications in the fields of Scientific Computing\, Medical Imaging\, Cancer detection\, Diabetic Retinopathy\, and Voice-enabled solutions to improve management of chronic disease will be discussed. The AWS Research Initiative with funding agencies such as the National Science Foundation (NSF) in the domains related to the foundation and innovative tracks\, as well as AWS Research Credit program will also be outlined. \nIf you would like to meet Dr. Sanjay Padhi on October 1\, please send a request to micde-events@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-sanjay-padhi-aws-research-and-technical-computing/
LOCATION:1670 Bob and Betty Beyster Building\, 2260 Hayward Street\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2018/08/Sanjay-Padhi.png
GEO:42.2930138;-83.716372
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=1670 Bob and Betty Beyster Building 2260 Hayward Street Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=2260 Hayward Street:geo:-83.716372,42.2930138
END:VEVENT
END:VCALENDAR