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DTSTART;TZID=America/Detroit:20180126T140000
DTEND;TZID=America/Detroit:20180126T170000
DTSTAMP:20260606T194052
CREATED:20230905T171417Z
LAST-MODIFIED:20230905T171417Z
UID:10000122-1516975200-1516986000@micde.umich.edu
SUMMARY:Introduction to MATLAB
DESCRIPTION:This workshop introduces participants to MATLAB. Topics include indexing and slicing of vectors and matrices\, creation of script M-files and functions\, control flow operators and basic 2D and 3D visualization. The workshop is targeted to participants with little to no knowledge of MATLAB and/or participants that would like to review basic MATLAB concepts.
URL:https://micde.umich.edu/event/introduction-to-matlab-4-2/
LOCATION:Modern Languages Building (MLB)\, Room 2001B
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20180126T140000
DTEND;TZID=America/Detroit:20180126T170000
DTSTAMP:20260606T194052
CREATED:20230905T171417Z
LAST-MODIFIED:20230905T171417Z
UID:10000100-1516975200-1516986000@micde.umich.edu
SUMMARY:Introductory GIS
DESCRIPTION:This workshop will cover introductory GIS concepts\, tools\, and techniques. We will use ArcGIS to learn basics of GIS by solving 2-3 specific problems. We will use the graphical user interface of ArcGIS and no programming experience is required for this workshop. The workshop will also cover the basics of projections and spatial data. \nThe workshop is meant for students and researchers who want to have a quick and simple exposure to GIS concepts and tools.
URL:https://micde.umich.edu/event/introductory-gis-2/
LOCATION:Rackham Building\, Earl Lewis Room\, 3rd Floor East\, 915 E. Washington St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Workshops
GEO:42.2807892;-83.7381556
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20180125T163000
DTEND;TZID=America/Detroit:20180125T173000
DTSTAMP:20260606T194052
CREATED:20230905T171417Z
LAST-MODIFIED:20230905T171417Z
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SUMMARY:Graduate programs in computational science — INFO SESSIONS
DESCRIPTION:Students interested in computational science are invited to learn about graduate programs that will prepare them for success in computationally intensive fields. Pizza and pop will be provided. \nTwo sessions are scheduled:\n\nMonday\, Jan. 22\, 4:30 – 5:30 p.m.\, Johnson Rooms\, Lurie Engineering Center (North Campus)\nThursday\, Jan. 25\, 4:30 – 5:30 p.m.\, 2001 LSA Building (Central Campus)\n\nThe sessions will address:\n\n\nThe Ph.D. in Scientific Computing\, which is open to all Ph.D. students who will make extensive use of large-scale computation\, computational methods\, or algorithms for advanced computer architectures in their studies. It is a joint degree program\, with students earning a Ph.D. from their current departments\, “… and Scientific Computing” — for example\, “Ph.D. in Aerospace Engineering and Scientific Computing.” \n\n\nThe Graduate Certificate in Computational Discovery and Engineering\, which trains graduate students in computationally intensive research so they can excel in interdisciplinary HPC-focused research and product development environments. The certificate is open to all students currently pursuing Master’s or Ph.D. degrees at the University of Michigan. The practicum option for Master’s students through the Multidisciplinary Design Program will be explained.
URL:https://micde.umich.edu/event/graduate-studies-in-computational-data-sciences-info-session-central-campus-3/
LOCATION:MI
CATEGORIES:Featured Events
ATTACH;FMTTYPE=:
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20180125T090000
DTEND;TZID=America/Detroit:20180125T163000
DTSTAMP:20260606T194052
CREATED:20230905T171417Z
LAST-MODIFIED:20230905T171417Z
UID:10000074-1516870800-1516897800@micde.umich.edu
SUMMARY:Stata 1: Introduction to Stata
DESCRIPTION:Note: Topics are subject to change. \nTopics: \n\nBasics – Interfacing with Stata\, Do-files\, getting help.\nWorking with Data Sets – Importing\, opening\, and saving data files.\nData Management – Getting familiar with your data\, adding informative labels\, basic checks for issues.\nData Manipulation – Generating new variables\, working with subsets of data\, merging files\, reshaping files.\nProgramming – A basic and gentle introduction to some of the more advanced Stata programming.\nNote: This workshop does not cover any statistical modeling; see Stata 2: Statistical Modeling in Stata for those topics.\n\nTo register for CSCAR Workshops\, call the CSCAR front desk at (734) 764-7828 or come to the office in person with cash or check or a UM 6-digit department shortcode: \nOFFICE HOURS\n9:00 a.m. – 5:00 p.m.\, Monday through Friday\nClosed 12pm – 1:00 p.m. every Tuesday for staff meeting.\nVoice: (734) 764-7828 (4-STAT from a campus phone)\nFax: (734) 647-2440 \nADDRESS\nConsulting for Statistics\, Computing and Analytics Research (CSCAR)\nThe University of Michigan\n3550 Rackham\n915 E. Washington St.\nAnn Arbor\, MI 48109-1070
URL:https://micde.umich.edu/event/introduction-to-stata-3/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20180124T150000
DTEND;TZID=America/Detroit:20180124T160000
DTSTAMP:20260606T194052
CREATED:20230905T171417Z
LAST-MODIFIED:20260525T001342Z
UID:10000104-1516806000-1516809600@micde.umich.edu
SUMMARY:MICDE Seminar: Jesse Capecelatro\, Department of Mechanical Engineering\, University of Michigan
DESCRIPTION:Bio: Professor Capecelatro is interested in developing large-scale simulation capabilities for prediction and design of the complex multi-physics and multiphase flows relevant to energy and the environment. To achieve this\, his group develops robust and scalable numerical methods to leverage world-class supercomputing resources. His current research projects are focused on adjoint-based methods applied to turbulent combustion\, modeling strongly-coupled particle-laden flows\, and understanding interactions between electrostatics and turbulence in atmospheric clouds. \nPrior to joining the mechanical engineering department at the University of Michigan in 2016\, Dr. Capecelatro was a research scientist at the Center for Exascale Simulation of Plasma-coupled Combustion (XPACC) at the University of Illinois Urbana-Champaign. He received a B.S. in mechanical engineering from SUNY Binghamton in 2009\, and two years later completed a M.S. in mechanical engineering from the University of Colorado Boulder\, where he performed research in collaboration with the National Renewable Energy Laboratory on numerical modeling of fluidized bed reactors. In 2014 he received a Ph.D. from Cornell University under the guidance of Prof Olivier Desjardins\, where his thesis focused on high performance computing of turbulent multiphase flows. He spent the summer following his Ph.D. as a visiting postdoc at the Institut de Mécanique des Fluides de Toulouse and École Centrale Paris focusing on fundamental and numerical studies of particle-induced turbulence. \nTowards Accurate and Tractable Methods of Disperse Multiphase Flows in Extreme Environments\nThe complex and multiscale behavior associated with turbulent flows is further complicated by the presence of a disperse phase (i.e.\, solid particles\, liquid drops\, or gaseous bubbles). Strong coupling between the disperse phase and underlying turbulence plays important roles across engineering and science. For example\, liquid sprays are often used during rocket launches to suppress undesirable aeroacoustic loading on the fuselage and nearby equipment. Recent experiments have shown that water sound suppression systems might also be a viable option for jet noise reduction during take-off and landing of high-performance aircrafts. Within the energy sector\, turbulent suspensions of catalytic particles are used in a variety of energy conversion technologies\, yet the multiphase dynamics occurring in these reactors remain largely unknown. A key challenge in understanding and predicting turbulent multiphase flows is the fundamental importance of processes occurring on extremely small scales that ultimately influence the macroscopic behavior. This presentation will provide an overview of recent advancements in numerical modeling of particle-laden flows with several applications of ongoing research projects.
URL:https://micde.umich.edu/event/micde-seminar-jesse-capecelatro-department-of-mechanical-engineering-university-of-michigan/
LOCATION:185 EWR\, 1351 Beal Ave\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2017/09/Jesse-Capecelatro.png
GEO:42.2927609;-83.7132928
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20180123T100000
DTEND;TZID=America/Detroit:20180123T150000
DTSTAMP:20260606T194052
CREATED:20230905T171417Z
LAST-MODIFIED:20230905T171417Z
UID:10000123-1516701600-1516719600@micde.umich.edu
SUMMARY:Android Application Development: Why and How
DESCRIPTION:Mobile app development is one of the biggest new industries of the last decade. As of 2017\, Google has stated that over 2 billion devices around the world use the Android operating system\, alongside Apple’s 1 billion iOS mobile devices around the globe. The capabilities and adopted use of modern smartphones can provide an easy gateway to collect data or engage with participants for research purposes. It might seem a daunting task for newcomers to write a program for the computer in their pocket\, but modern tools and software make it more accessible than ever. We will present a brief overview of the differences between Android and iOS development requirements\, and provide demonstrations on how to program an app for your Android phone using a Windows PC environment and a sample of free software packages. \nA familiarity with programming languages and logic is assumed. Program code presented during the workshop may be written in languages including (but not limited to) Java and C#\, familiarity with syntax of these languages is recommended. It is not expected for attendees to program during the workshop\, but those who wish to do so are recommended to install the “Android Studio” IDE in advance.
URL:https://micde.umich.edu/event/android-application-development-why-and-how/
LOCATION:Rackham Building\, Earl Lewis Room\, 3rd Floor East\, 915 E. Washington St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Data Science,Workshops
GEO:42.2807892;-83.7381556
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Rackham Building Earl Lewis Room 3rd Floor East 915 E. Washington St. Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=915 E. Washington St.:geo:-83.7381556,42.2807892
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20180122T163000
DTEND;TZID=America/Detroit:20180122T173000
DTSTAMP:20260606T194052
CREATED:20230905T171417Z
LAST-MODIFIED:20230905T171417Z
UID:10000121-1516638600-1516642200@micde.umich.edu
SUMMARY:Graduate programs in computational science — INFO SESSIONS
DESCRIPTION:Students interested in computational science are invited to learn about graduate programs that will prepare them for success in computationally intensive fields. Pizza and pop will be provided. \nTwo sessions are scheduled:\n\nMonday\, Jan. 22\, 4:30 – 5:30 p.m.\, Johnson Rooms\, Lurie Engineering Center (North Campus)\nThursday\, Jan. 25\, 4:30 – 5:30 p.m.\, 2001 LSA Building (Central Campus)\n\nThe sessions will address:\n\n\nThe Ph.D. in Scientific Computing\, which is open to all Ph.D. students who will make extensive use of large-scale computation\, computational methods\, or algorithms for advanced computer architectures in their studies. It is a joint degree program\, with students earning a Ph.D. from their current departments\, “… and Scientific Computing” — for example\, “Ph.D. in Aerospace Engineering and Scientific Computing.” \n\n\nThe Graduate Certificate in Computational Discovery and Engineering\, which trains graduate students in computationally intensive research so they can excel in interdisciplinary HPC-focused research and product development environments. The certificate is open to all students currently pursuing Master’s or Ph.D. degrees at the University of Michigan. The practicum option for Master’s students through the Multidisciplinary Design Program will be explained.
URL:https://micde.umich.edu/event/graduate-studies-in-computational-data-sciences-info-session-north-campus-3/
LOCATION:Johnson Rooms\, Lurie Engineering Center\, 3rd Floor LEC 3213ABC\, 1221 Beal Ave.\, Ann Arbor\, MI\, United States
CATEGORIES:Featured Events
ATTACH;FMTTYPE=image/jpeg:https://micde.umich.edu/wp-content/uploads/2023/02/2016-06-14-11.13.52-scaled.jpg
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:20180119T140000
DTEND;TZID=America/Detroit:20180119T163000
DTSTAMP:20260606T194052
CREATED:20230905T171417Z
LAST-MODIFIED:20230905T171417Z
UID:10000124-1516370400-1516379400@micde.umich.edu
SUMMARY:Regular Expressions II
DESCRIPTION:Regular expressions are perfectly suited for people who like puzzles. Regular expressions are a sequence of characters used to define a search pattern. They are commonly used to do “find” and “find and replace” string operations. They are also used to validate strings like phone numbers\, passwords\, etc. in data entry. Regular expression capabilities can be found in a variety of programming languages and software like ArcGIS\, Java\, Javascript\, Matlab\, Perl\, PHP\, Python\, R\, Visual Basic\, etc. and some text editors. This workshop is part II of a two-part series and will cover more advanced topics like captured groups\, backreferences and assertions. The workshop will consist of hands-on example problems. Basic understanding of regular expressions is required. You should be able to understand expressions like “w{3\,}-d{1\,2}-d{4}“ and “des*ert?s?”. The tutorials will be conducted using Python. A basic programming background is helpful but not required for this workshop.
URL:https://micde.umich.edu/event/regular-expressions-ii/
LOCATION:Modern Languages Building (MLB)\, Room 2001B
CATEGORIES:Data Science,Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20180118T090000
DTEND;TZID=America/Detroit:20180118T163000
DTSTAMP:20260606T194052
CREATED:20230905T171415Z
LAST-MODIFIED:20230905T171415Z
UID:10000032-1516266000-1516293000@micde.umich.edu
SUMMARY:SPSS I Introduction to SPSS
DESCRIPTION:Note: Topic order is subject to change. \nThis workshop is designed to introduce participants to SPSS. It will cover the fundamentals of SPSS\, within-case transformations\, data management with multiple files\, and basic statistics and graphics. Useful for any scholar engaged in quantitative research. \nFundamentals \nThis portion introduces SPSS\, the menu and the help systems\, and the three main types of files used.  It then addresses defining variables\, attaching labels\, defining missing values\, and various ways to enter data into SPSS.  Finally\, it covers a brief introduction to obtaining frequency distributions\, descriptive statistics\, and cross tabulations of variables. \nWithin-Case Transformations \nThis portion introduces data management capabilities\, including recoding variables (manual and automatic)\, computing new variables using formulas\, and counting occurrences of values within subjects.  Attention then turns to temporary transformations\, conditional processing of transformations\, and repetitive transformations. \nData Management with Multiple Files \nThis portion begins with a discussion of subsetting data files by drawing samples\, selecting groups and excluding groups from analysis.  Then\, the two main methods of merging SPSS data files are covered: adding additional variables and adding additional cases. \nBasic Statistical Analysis \nThe portion includes a brief demonstration of a statistical analysis in SPSS. While not delving deep into statistical theory\, we will cover the basics of an analysis\, as well as discuss the graphing facilities in SPSS. \nRegistration\nTo register for CSCAR Workshops\, call the CSCAR front desk at (734) 764-7828 or come to the office in person with cash or check or a UM 6-digit department shortcode: \nOFFICE HOURS\n9:00 a.m. – 5:00 p.m.\, Monday through Friday\nClosed 12pm – 1:00 p.m. every Tuesday for staff meeting.\nVoice: (734) 764-7828 (4-STAT from a campus phone)\nFax: (734) 647-2440 \nADDRESS\nCenter for Statistical Consultation and Research (CSCAR)\nThe University of Michigan\n3550 Rackham\n915 E. Washington St.\nAnn Arbor\, MI 48109-1070 \n 
URL:https://micde.umich.edu/event/introduction-to-spss/
LOCATION:Modern Languages Building (MLB)\, Room 2001B
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20180116T160000
DTEND;TZID=America/Detroit:20180116T170000
DTSTAMP:20260606T194052
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:20171211T100000
DTEND;TZID=America/Detroit:20171211T110000
DTSTAMP:20260606T194052
CREATED:20230905T171416Z
LAST-MODIFIED:20230905T171416Z
UID:10000119-1512986400-1512990000@micde.umich.edu
SUMMARY:ME Faculty Candidate Seminar Series:  Xiu Yang\, Computational Mathematics Scientist\, Pacific Northwest National Laboratory
DESCRIPTION:Bio: Dr. Xiu Yang received his B.S. and M.Sc. in computational mathematics from Peking University\, Beijing\, China and Ph.D. in applied mathematics from Brown University\, Providence\, RI. He is currently a research scientist in computational mathematics group at Pacific Northwest National Laboratory\, Richland\, WA. His research interests include uncertainty quantification\, multi-scale modeling\, multi-fidelity data fusion and inverse problem.\n  \n Uncertainty Quantification for Complex Systems Using Limited Data\nRealistic analysis and design of complex engineering systems require not only a fine understanding of the underlying physics\, but also a significant recognition of uncertainties and their influences on the quantities of interest. Intrinsic variabilities and lack of knowledge about system parameters or governing physical models often considerably affect quantities of interest and decision-making processes. For complex systems\, the available data for quantifying uncertainties or analyzing sensitivities are usually limited because the cost of conducting a large number of experiments or running many large-scale simulations can be prohibitive. Efficient approaches of representing uncertainties using limited data are critical for such problems. I will talk about three methods for uncertainty quantification by constructing surrogate model of the quantity of interest. The first method is the adaptive functional ANOVA method\, which constructs the surrogate model hierarchically by analyzing the sensitivities of individual parameters. The second method is the sparse regression based on identification of low-dimensional structure\, which exploits low-dimensional structures in the parameter space and solves an optimization problem to construct the surrogate model. The third one is the multi-fidelity information fusion via Gaussian process regression\, which integrates limited high-fidelity data with a large number of low-fidelity data. I will demonstrate the efficiency of these methods in applications including perturbation of drag and lift in aerodynamics\, solvation energy computing in chemical biology\, stability analysis of power grid system and optimizing Li-O2 battery design. \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-xiu-yang-computational-mathematics-scientist-pacific-northwest-national-laboratory/
LOCATION:2150 H.H. Dow\, 2300 Hayward St\, Ann Arbor\, 48109\, United States
ATTACH;FMTTYPE=image/jpeg:https://micde.umich.edu/wp-content/uploads/2023/02/XiuYang.jpg
GEO:42.2929214;-83.7154247
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=2150 H.H. Dow 2300 Hayward St Ann Arbor 48109 United States;X-APPLE-RADIUS=500;X-TITLE=2300 Hayward St:geo:-83.7154247,42.2929214
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20171206T120000
DTEND;TZID=America/Detroit:20171206T130000
DTSTAMP:20260606T194052
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/
LOCATION:MI
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:20171205T150000
DTEND;TZID=America/Detroit:20171205T160000
DTSTAMP:20260606T194052
CREATED:20230905T171416Z
LAST-MODIFIED:20230905T171416Z
UID:10000093-1512486000-1512489600@micde.umich.edu
SUMMARY:MICDE Seminar: Tarek Zohdi\, Department of Mechanical Engineering\, University of California\, Berkeley
DESCRIPTION:Bio: Tarek I. Zohdi received his Ph.D. in 1997 in Computational and Applied Mathematics from the University of Texas at Austin and his Habilitation in General Mechanics from the Gottfried Leibniz University of Hannover in 2002. He is currently a Chancellor’s Professor of Mechanical Engineering\, Chair of the Computational and Data Science and Engineering Program at UC Berkeley and holder of the W. C. Hall Family Endowed Chair in Engineering. He also holds a Staff Scientist position at Lawrence Berkeley National Labs. His main research interests are in computational approaches for advanced manufacturing and nonconvex multiscale-multiphysics inverse problems\, in particular addressing the issue of how large numbers of micro-constituents interact to produce macroscale aggregate material behavior. He has published over 145 archival refereed journal papers and five books. In 2000\, he received the Zienkiewicz Prize and Medal\, which are awarded once every two years\, to one post-graduate researcher under the age of 35\, by The Institution of Civil Engineers in London\, to commemorate the work of Professor O. C. Zienkiewicz\, for research which contributes most to the field of numerical methods in engineering. In 2002\, he received the Best Paper of the Year 2001 Award in London\, at the Lord’s Cricket Grounds\, for a paper published in Engineering Computations\, pertaining to modeling and simulation of the propagation of failure in particulate aggregates of material. In 2003\, he received the Junior Achievement Award of the American Academy of Mechanics. The award is given once a year\, to one post-graduate researcher\, to recognize outstanding research during the first decade of a professional career. In 2008\, he was elected Fellow of the International Association for Computational Mechanics (IACM) and in 2009 he was elected Fellow of the United Stated Association for Computational Mechanics (USACM). He was elected President of the USACM in 2012\, and served from 2012 to 2014. He is an editor of Computational Mechanics\, Editor in Chief of Computational Particle Mechanics and serves on 12 editorial boards of international journals. For more information visit http://www.me.berkeley.edu/people/faculty/tarek-i-zohdi \nModeling and Simulation of Multistage Multiphysical Processes in Next-Generation Advanced Manufacturing and 3D Printing with New Multifunctional Materials\nWithin the last decade\, several industrialized countries have stressed the importance of advanced manufacturing to their economies. Many of these plans have highlighted the development of additive manufacturing techniques\, such as 3D printing\, which are still in their infancy. The objective is to develop superior products\, produced at lower overall operational costs. For these   goals to be realized\, a deep understanding of the essential ingredients comprising the materials involved in additive manufacturing is needed. The combination of rigorous material modeling theories\, coupled with the dramatic increase of computational power can potentially play a significant role in the analysis\, control\, and design of many emerging additive manufacturing processes. Specialized materials and the precise   design of their properties are key factors in the processes. Specifically\, particle-functionalized materials play a central role in this field\, in three main ways:   (1) to endow filament-based materials by adding particles to a heated binder   (2) to “functionalize” inks by adding particles to freely flowing solvents and (3) to directly deposit particles\, as dry powders\, onto surfaces and then to heat them with a laser\, e-beam or other external source\, in order to fuse them into place. The goal of these processes is primarily to build surface structures\, coatings\, etc.\, which are extremely difficult to construct using classical manufacturing methods. The objective of this presentation is to introduce the audience to basic techniques which can allow them to rapidly develop and analyze particulate-based materials needed in new additive manufacturing processes. This presentation is broken into two main parts: continuum and discrete element approaches. The materials associated with methods (1) and (2) are closely related types of continua (particles embedded in a continuous binder) and are treated using continuum approaches. The materials in method (3)\, which are of a discrete particulate character\, are analyzed using discrete element methods. \nProf. Zohdi is being hosted by Prof. Garikipati (Mechanical Engineering). If you would like to meet with him please email mcteja@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-tarek-zohdi-department-of-mechanical-engineering-university-of-california-berkeley/
LOCATION:1109 FXB\, 1320 Beal Ave.\, Ann Arbor\, MI\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20171204T100000
DTEND;TZID=America/Detroit:20171204T110000
DTSTAMP:20260606T194052
CREATED:20230905T171416Z
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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/
LOCATION:MI
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:20171201T180000
DTEND;TZID=America/Detroit:20171201T190000
DTSTAMP:20260606T194052
CREATED:20230905T171416Z
LAST-MODIFIED:20230905T171416Z
UID:10000114-1512151200-1512154800@micde.umich.edu
SUMMARY:SC2 Machine Learning Collaborative Workshop
DESCRIPTION:Machine Learning (ML) has found it’s way into much of today’s computational landscape and is a powerful tool to extract meaning from the large amounts of data generated by high performance computing. The Scientific Computing Student Club (SC2) has organized this workshop for students\, and all interested individuals\, with the goal of learning existing ML tools that can be easily integrate in research workflow.  Weekly meetings on Fridays @ 6:00 pm\, except November 24\, 2017. More information…
URL:https://micde.umich.edu/event/sc2-machine-learning-collaborative-workshop/2017-12-01/
LOCATION:1311 EECS\, 1301 Beal Ave.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20171201T083000
DTEND;TZID=America/Detroit:20171201T173000
DTSTAMP:20260606T194052
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
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20171129T153000
DTEND;TZID=America/Detroit:20171129T163000
DTSTAMP:20260606T194052
CREATED:20230905T171416Z
LAST-MODIFIED:20230905T171416Z
UID:10000116-1511969400-1511973000@micde.umich.edu
SUMMARY:MICDE 2017 Catalyst Grants Informational Session
DESCRIPTION:MICDE seeks proposals for innovative research projects in computational science that combine elements of mathematics\, computer science\, and cyberinfrastructure. Of interest is innovative computational research in any emerging area\, including but not limited to (a) applications such as neuroscience\, ecology\, environmental science\, evolutionary biology\, human-made complex systems\, urban infrastructure and energy\, (b) frameworks for scientific software\, exascale\, quantum\, or neuromorphic computing\, and (c) concepts such as computations to decisions. The aim of the Catalyst Grants program is to advance projects that have the potential to attract additional external funding. Priority will be given to high-impact projects with potential to eventually attract external funding. MICDE expects to fund 3-4 one-year projects at up to $100\,000 each. \nIn this informational session\, MICDE officials will clarify the program’s intent\, answer questions and facilitate team formation among attendees. \nPlease pre-register using this google form. You’ll need to be signed into your umich account. The session will be broadcasted via this bluejeans link. For more information go to https://live-umor-micde.pantheonsite.io/grants/catalyst-grants/
URL:https://micde.umich.edu/event/micde-2017-catalyst-grants-informational-session/
LOCATION:Space 2435 North Quad\, 105 S. State St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Info Session
GEO:42.2807324;-83.7400253
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20171124T180000
DTEND;TZID=America/Detroit:20171124T190000
DTSTAMP:20260606T194052
CREATED:20230905T171416Z
LAST-MODIFIED:20230905T171416Z
UID:10000622-1511546400-1511550000@micde.umich.edu
SUMMARY:SC2 Machine Learning Collaborative Workshop
DESCRIPTION:Machine Learning (ML) has found it’s way into much of today’s computational landscape and is a powerful tool to extract meaning from the large amounts of data generated by high performance computing. The Scientific Computing Student Club (SC2) has organized this workshop for students\, and all interested individuals\, with the goal of learning existing ML tools that can be easily integrate in research workflow.  Weekly meetings on Fridays @ 6:00 pm\, except November 24\, 2017. More information…
URL:https://micde.umich.edu/event/sc2-machine-learning-collaborative-workshop-2-7/
LOCATION:1311 EECS\, 1301 Beal Ave.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events
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GEO:42.292322;-83.713272
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20171121T133000
DTEND;TZID=America/Detroit:20171121T143000
DTSTAMP:20260606T194052
CREATED:20230905T171414Z
LAST-MODIFIED:20230905T171414Z
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SUMMARY:MICDE Seminar: Edward Maginn\, Department of Chemical and Biomolecular Engineering\, University of Notre Dame
DESCRIPTION:Bio: Edward Maginn received his BS in chemical engineering from Iowa State University and his PhD in chemical engineering from the University of California\, Berkeley. Prior to attending graduate school\, he worked as a process engineer for Procter and Gamble. He has been on the Notre Dame faculty since 1995 and currently holds the Dorini Family Chair of Energy Studies in the Department of Chemical and Biomolecular Engineering. He is also the chair of the department\, and was formerly the Associate Dean for Academic Programs in the Graduate School. He has won a number of awards\, including the Early Career Award from the Computational Molecular Science and Engineering Forum of the American Institute of Chemical Engineers\, the ASEE Dow Outstanding New Faculty Award\, the BP College of Engineering Outstanding Teacher Award and the NSF Career award. He is a Fellow of the American Association for the Advancement of Science and is a trustee of the CACHE Corporation. His research focuses on the development and use of atomistic molecular dynamics and Monte Carlo simulation methods to study the thermodynamic and transport properties of materials\, with special emphasis on ionic systems important in energy storage and use. \nUsing Molecular Modeling to Design New Fluids for Energy Storage and Carbon Capture\nLiquids that contain charged species\, such as electrolytes and ionic liquids\, have many important technological applications in fields such as energy storage\, separations\, and catalysis. By changing the structure of the molecules or employing mixtures\, the properties of these fluids can be altered significantly. The key questions are: How should I change the structure of the molecule or ion to get the properties I want? What type of additives should I use to improve performance? To answer these and related questions\, we use atomistic-level simulations to compute structural\, thermodynamic and transport properties of these systems. We are able to provide molecular-level explanations for experimental observations\, and we can predict properties of systems that may not yet have even been made in the laboratory. \nIn the first part of this talk\, I will describe molecular modeling research directed at improving the performance of electrolytes used in next generation “beyond lithium” batteries. Electrolytes are a critical component of batteries\, since they transport ions from the cathode to the anode during charging\, then in the reverse direction in releasing energy on discharge. Electrolytes play a leading role in a battery’s capacity for energy storage\, its lifetime and the safety of the battery. The electrolyte in a conventional lithium-ion battery consists of a lithium salt dissolved in an organic solvent. The electrolytes for next generation “beyond lithium” batteries will require new salt-solvent combinations.  Our simulations probe the way in which different electrolyte formulations\, charge carriers and additives impact the structure and dynamics of these liquids. \nIn the second half of the talk\, I will show how these same kinds of simulations can be used to develop new ionic liquids that can be used for CO2 separations / capture. Ionic liquids are pure salts that are liquid at ambient temperatures. Because they have essentially no vapor pressure and readily dissolve CO2\, people have been interested in using them for carbon capture. I will describe how our simulations have been successful in identifying new ionic liquids with properties tuned for use as conventional liquid absorbents or as supported ionic liquid membranes. \nThis is a joint seminar with the department of Chemical Engineering. Prof. Maginn is being hosted by Prof. Mayes (Chemical Engineering). If you are interested in meeting him during his visit please send an email to mcteja@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-edward-maginn-department-of-chemical-and-biomolecular-engineering-university-of-notre-dame/
LOCATION:MI
CATEGORIES:Featured Events,MICDE Seminar Series
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20171117T180000
DTEND;TZID=America/Detroit:20171117T190000
DTSTAMP:20260606T194052
CREATED:20230905T171415Z
LAST-MODIFIED:20230905T171415Z
UID:10000621-1510941600-1510945200@micde.umich.edu
SUMMARY:SC2 Machine Learning Collaborative Workshop
DESCRIPTION:Machine Learning (ML) has found it’s way into much of today’s computational landscape and is a powerful tool to extract meaning from the large amounts of data generated by high performance computing. The Scientific Computing Student Club (SC2) has organized this workshop for students\, and all interested individuals\, with the goal of learning existing ML tools that can be easily integrate in research workflow.  Weekly meetings on Fridays @ 6:00 pm\, except November 24\, 2017. More information…
URL:https://micde.umich.edu/event/sc2-machine-learning-collaborative-workshop-2-2/
LOCATION:1311 EECS\, 1301 Beal Ave.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events
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GEO:42.292322;-83.713272
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20171110T180000
DTEND;TZID=America/Detroit:20171110T190000
DTSTAMP:20260606T194052
CREATED:20230905T171415Z
LAST-MODIFIED:20230905T171415Z
UID:10000620-1510336800-1510340400@micde.umich.edu
SUMMARY:SC2 Machine Learning Collaborative Workshop
DESCRIPTION:Machine Learning (ML) has found it’s way into much of today’s computational landscape and is a powerful tool to extract meaning from the large amounts of data generated by high performance computing. The Scientific Computing Student Club (SC2) has organized this workshop for students\, and all interested individuals\, with the goal of learning existing ML tools that can be easily integrate in research workflow.  Weekly meetings on Fridays @ 6:00 pm\, except November 24\, 2017. More information…
URL:https://micde.umich.edu/event/sc2-machine-learning-collaborative-workshop-2-3/
LOCATION:1311 EECS\, 1301 Beal Ave.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events
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GEO:42.292322;-83.713272
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20171110T150000
DTEND;TZID=America/Detroit:20171110T160000
DTSTAMP:20260606T194052
CREATED:20230905T171415Z
LAST-MODIFIED:20230905T171415Z
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SUMMARY:MICDE Seminar: Chris Rycroft\, Department of Applied Mathematics\, Harvard University
DESCRIPTION:Bio: Chris Rycroft is an Assistant Professor of Applied Mathematics in the School of Engineering and Applied Sciences at Harvard University. From 2010–2013\, he was a Morrey Assistant Professor in the UC Berkeley Mathematics Department\, and he was involved in the Bay Area Physical Sciences-Oncology where he collaborated with several experimental groups at Berkeley and UC San Francisco\, on using computational modeling to understand the role of mechanical forces between cells and their environment. Prof. Rycroft’s research focuses on mathematical modeling and scientific computation\, particularly for interdisciplinary applications in science and engineering. He works on a variety of problems\, and has collaborated in a number of fields including physics\, biology\, materials science\, and mechanical engineering. His current interests include questions that relate to the mechanics of materials\, numerical algorithms\, and geometry. Several of his recent projects relate to energy production and efficiency\, such as modeling bulk metallic glasses\, and developing high-throughput screening techniques to find advanced materials for carbon capture applications. He has also released several software libraries\, including Voro++ for three-dimensional computations of the Voronoi tessellation. \nThe reference map technique for simulating complex materials and multi-body interactions\nConventional computational methods often create a dilemma for fluid-structure interaction problems. Typically\, solids are simulated using a Lagrangian approach with grid that moves with the material\, whereas fluids are simulated using an Eulerian approach with a fixed spatial grid\, requiring some type of interfacial coupling between the two different perspectives. Here\, a fully Eulerian method for simulating structures immersed in a fluid will be presented. By introducing a reference map variable to model finite-deformation constitutive relations in the structures on the same grid as the fluid\, the interfacial coupling problem is highly simplified. The method is particularly well suited for simulating soft\, highly-deformable materials and many-body contact problems\, and several examples from engineering and biology will be presented. This is joint work with Ken Kamrin (MIT). \nThis is a joint seminar with the Interdisciplinary Applied Mathematics seminar series. \nProf. Rycroft is being hosted by Prof. Alben (Mathematics). If you would like to meet him please email Prof. Alben at alben@umich.edu or Dr. Mariana Carrasco-Teja at mcteja@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-chris-rycroft-department-of-applied-mathematics-harvard-university/
LOCATION:1084 East Hall\, 530 Church St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
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GEO:42.2757302;-83.7351764
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20171108T140000
DTEND;TZID=America/Detroit:20171108T150000
DTSTAMP:20260606T194052
CREATED:20230905T171415Z
LAST-MODIFIED:20230905T171415Z
UID:10000095-1510149600-1510153200@micde.umich.edu
SUMMARY:MICDE Seminar: Giulia Galli\, Department of Molecular Engineering\, University of Chicago
DESCRIPTION:Bio: Giulia Galli is the Liew Family Professor of Electronic Structure and Simulations in the Institute for Molecular Engineering at the University of Chicago. She also holds a Senior Scientist position at Argonne National Laboratory (ANL) and she is a Senior Fellow of the UChicago/ANL Computational Institute. Prior to joining U Chicago and ANL\, she was Professor of Chemistry and Physics at UC Davis (2005-2013) and the head of the Quantum Simulations group at the Lawrence Livermore National Laboratory (1998-2005).\nShe holds a Ph.D. in Physics from the International School of Advanced Studies (SISSA) in Trieste\, Italy. She is a Fellow of the American Physical Society (APS) and of the AAAS. She is the recipient of an award of excellence from the Department of Energy (2000) and of the Science and Technology Award from the Lawrence Livermore National Laboratory (2004). She is currently the director of MICCoM (Midwest Integrated Center for Computational Materials)\, established by DOE in 2015. Her research activity is focused on the development and use of theoretical and computational tools to understand and predict the properties and behavior of materials (solids\, liquids and nanostructures) from first principles. \nMaterials discovery and scientific design by computation: what does it take?\nSubstantial progress has been made in the last three decades in understanding and predicting the fundamental properties of materials and molecular systems from first principles\, employing electronic structure methods and atomistic simulations. Using specific examples\, I will discuss some predictions obtained for materials for energy conversion processes (photo-catalysis of water and solar cells) as well as some of the major challenges involved in enabling scientific discoveries by computation; in particular I will touch upon theoretical validation; and collection and verification of data generated by simulations. I will also discuss some of the theoretical and algorithmic advances required to broaden the scope of properties accessible by current ab initio simulations. \nProfessor Galli is being hosted by Prof. Siegel (Mechanical Engineering). If you would like to meet her during her visit please email mcteja@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-giulia-galli-department-of-molecular-engineering-university-of-chicago/
LOCATION:MI
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2017/09/Giulia-Galli.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20171103T180000
DTEND;TZID=America/Detroit:20171103T190000
DTSTAMP:20260606T194052
CREATED:20230905T171415Z
LAST-MODIFIED:20230905T171415Z
UID:10000619-1509732000-1509735600@micde.umich.edu
SUMMARY:SC2 Machine Learning Collaborative Workshop
DESCRIPTION:Machine Learning (ML) has found it’s way into much of today’s computational landscape and is a powerful tool to extract meaning from the large amounts of data generated by high performance computing. The Scientific Computing Student Club (SC2) has organized this workshop for students\, and all interested individuals\, with the goal of learning existing ML tools that can be easily integrate in research workflow.  Weekly meetings on Fridays @ 6:00 pm\, except November 24\, 2017. More information…
URL:https://micde.umich.edu/event/sc2-machine-learning-collaborative-workshop-2-4/
LOCATION:1311 EECS\, 1301 Beal Ave.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2022/04/SC2_simple.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:20171102T140000
DTEND;TZID=America/Detroit:20171102T150000
DTSTAMP:20260606T194052
CREATED:20230905T171415Z
LAST-MODIFIED:20260522T153005Z
UID:10000096-1509631200-1509634800@micde.umich.edu
SUMMARY:MICDE Seminar: Thomas Devereaux\, Photon Science\, Stanford University
DESCRIPTION:Bio: Professor Devereaux received his Ph.D. in Physics from the University of Oregon in 1991\, M.S. from University of Oregon in 1988\, and B.S from New York University in 1986. Professor Devereaux is currently the Director of the Stanford Institute for Materials and Energy Sciences (SIMES)\, the Associate Lab Director (ALD) for Photon Science\, a professor in the Photon Science Faculty at SLAC National Accelerator Laboratory and Stanford University and a Senior Fellow of the Precourt Institute for Energy. SIMES is a joint institute between Stanford main campus and SLAC\, a national laboratory\, focusing on scientific foundations related to the energy challenge facing our society. Professor Devereaux was a Post-doctoral Fellow at the Max Planck Institut\, Stuttgart\, (1991-1993)\, a Post-doctoral Fellow at the University of California\, Davis\, CA\, (1993-1996)\, an Assistant Professor at The George Washington University\, Washington\, DC\, (1996-1999)\, and an Associate Professor (1999-2006) and Professor (2006-2007) at the University of Waterloo\, Waterloo\, ON\, Canada.\nHis main research interests lie in the areas of theoretical condensed matter physics and computational physics. His research effort focuses on using the tools of computational physics to understand quantum materials. Fortunately\, we are poised in an excellent position as the speed and cost of computers have allowed us to tackle heretofore unaddressed problems involving interacting systems. The goal of his research is to understand electron dynamics via a combination of analytical theory and numerical simulations to provide insight into materials of relevance to energy science. His group carries out numerical simulations on SIMES’ high-performance supercomputer\, the National Energy Research Scientific Computing Center (NERSC)\, and other US and Canadian computational facilities. The specific focus of the group is the development of numerical methods and theories of photon-based spectroscopies of strongly correlated materials.\nProfessor Devereaux’s awards include: U. S. Department of Education Fellowship (1989-1991); Junior Scholar Incentive Award\, George Washington University (1998); Research Fellowship of the Alexander von Humboldt Foundation (2002-2006); Premier’s Research Excellence Award\, Province of Ontario (2003); Scientist Research Fellowship\, Embassy of France (2005); and Fellow of the American Physics Society (2008). \nLight controlled topological phase transitions in multi-orbital and frustrated magnetic systems\nSpurred by recent progress in melting\, enhancement and induction of electronic order out of equilibrium\, a tantalizing prospect concerns instead accessing transient Floquet steady states via broad pump pulses\, to affect electronic properties. Here\, we consider a two-pronged approach to manipulate the topology of a band insulator\, as well as topological order in a Mott insulator. We first consider monolayer transition-metal dichalcogenides (TMDCs) [1]\, and show that their low-energy description as massive 2D relativistic fermions fails to hold for optical pumping. Instead\, the added complexity of a realistic materials description leads to a novel mechanism to optically induce topologically-protected chiral edge modes\, facilitating optically-switchable conduction channels that are insensitive to disorder. We develop a strategy to understand non-equilibrium Floquet-Bloch bands and topological transitions directly from ab initio calculations\, and illustrate for the example of WS2 that control of chiral edge modes can be dictated solely from symmetry principles and is not qualitatively sensitive to microscopic materials details. Second\, we extend these ideas to strongly correlated systems and show that pumping frustrated Mott insulators with circularly-polarized light can drive the effective spin system across a phase transition to a chiral spin liquid (CSL) [2]. We show that the transient time evolution of a Kagome lattice Hubbard model is well captured by an effective spin description\, where circular polarization promotes a staggered scalar spin chirality Si . (Sj x Sk) directly to the Hamiltonian level. We fingerprint the ensuing phase diagram and find a stable photo-induced CSL in proximity to the equilibrium ground state. The results presented suggest new avenues to marry dynamical symmetry breaking\, strong interactions\, and ab initio materials modelling\, to access elusive phase transitions that are not readily accessible in equilibrium. \nReferences:\n[1] M. Claassen et al\, Nature Comm. 7\, 13074 (2016).\n[2] M. Claassen et al\, arXiv:1611.07964\, to appear in Nature Communications. \nThis is a joint CM Theory seminar. Prof. Devereaux is being hosted by Prof. Gull (Physics). If you are interested in meeting with him during his visit please send an email to mcteja@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-thomas-devereaux-photon-science-stanford-university/
LOCATION:4448 East Hall\, 530 Church St\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20171027T180000
DTEND;TZID=America/Detroit:20171027T190000
DTSTAMP:20260606T194052
CREATED:20230905T171415Z
LAST-MODIFIED:20230905T171415Z
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SUMMARY:SC2 Machine Learning Collaborative Workshop
DESCRIPTION:Machine Learning (ML) has found it’s way into much of today’s computational landscape and is a powerful tool to extract meaning from the large amounts of data generated by high performance computing. The Scientific Computing Student Club (SC2) has organized this workshop for students\, and all interested individuals\, with the goal of learning existing ML tools that can be easily integrate in research workflow.  Weekly meetings on Fridays @ 6:00 pm\, except November 24\, 2017. More information…
URL:https://micde.umich.edu/event/sc2-machine-learning-collaborative-workshop-2-5/
LOCATION:1311 EECS\, 1301 Beal Ave.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20171025T150000
DTEND;TZID=America/Detroit:20171025T160000
DTSTAMP:20260606T194052
CREATED:20230905T171415Z
LAST-MODIFIED:20230905T171415Z
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SUMMARY:MICDE Seminar: Irina Tezaur\, Extreme Scales Data Science and Analytics Department\, Sandia National Laboratories
DESCRIPTION:Bio: Dr. Irina Tezaur (f.k.a. Dr. Irina Kalashnikova) is a Principal Member of Technical Staff (PMTS) in the Extreme Scales Data Science & Analytics Department (Org. 8759) at Sandia National Laboratories in Livermore\, CA. Prior to joining this group\, from October 2011 to September 2014\, she was SMTS in the Computational Mathematics Department (Org. 1442) at Sandia in Albuquerque\, NM. She received her Ph.D. in Computational and Mathematical Engineering (CME) from Stanford University in 2011. Her advisor at Stanford was Professor Charbel Farhat and I was a member of the Farhat Research Group (FRG). Her Bachelors and Masters degrees are in pure mathematics\, awarded by the University of Pennsylvania in 2006. Dr. Tezaur’s research interests are numerical solution to PDEs\, mixed/hybrid finite element methods\, stability and convergence properties of numerical methods\, Reduced Order Modeling (ROM) and simulation-based analysis of fluid-structure interaction that she currently applies to climate modeling. \nNext-generation modeling & simulation of large-scale ice sheets towards probabilistic sea-level change projections\nRecent observations show that both the Greenland and Antarctic ice sheets are losing mass at increasingly rapid rates [1]. In its fourth assessment report (AR4)\, the Intergovernmental Panel on Climate Change (IPCC) declined to include estimates of future sea-level change from dynamics of the polar ice sheets due to the inability of ice sheet models to mimic or explain observed dynamic behaviors\, such as the acceleration and thinning then occurring on several of Greenland’s large outlet glaciers [2]. In recent years\, there has been a push to develop “next generation” land-ice models and codes for integration into global Earth System Models (ESMs). Unlike their predecessors\, these codes: (1) are able to perform realistic\, high-resolution\, continental scale simulations\, (2) are robust\, efficient and scalable on next-generation hybrid systems (multi-core\, many-core\, GPU\, Intel Xeon Phi)\, and (3) possess built-in advanced analysis capabilities (e.g.\, sensitivity analysis\, optimization\, uncertainty quantification). This talk will give an overview of the Albany/FELIX (Finite Elements for Land Ice eXperiments) [3] next-generation land-ice dynamical core (dycore) that is under development at Sandia National Laboratories as a part of a Department of Energy (DOE) SciDAC-funded project aimed at providing probabilistic sea-level projections from extreme-scale ice sheet and earth system models. This dycore is currently being integrated in to the DOE’s Acelerated Climate Model for Energy (ACME)\, which will be used to calculate anticipated 21st sea-level change projections\, including uncertainty bounds. It is widely accepted that land-ice behaves like a very viscous\, shear-thinning\, non-Newtonian fluid\, similar to lava flow. Typically\, ice sheets are modeled using a quasi-static model in which a steady momentum-balance system for the ice velocities is coupled to dynamic equations for the ice thickness and temperature. The Albany/FELIX dycore is based on the so-called “First-Order Stokes” equations for the ice momentum balance [4]\, an attractive alternative to the more expensive “Full Stokes” model because of its reduced computational cost. Following an overview of our land-ice model and project\, I will describe some of the algorithms and software we have developed as a part of this project that have contributed to our dycore’s robustness and scalability. These include: robust automatic-differentiation-based nonlinear solvers\, scalable algebraic-multigrid-based iterative linear solvers [5]\, adaptive mesh refinement capabilities\, and stable semi-implicit First-Order Stokes-thickness coupling methods. I will also discuss some of the advanced analysis capabilities in Albany/FELIX\, namely a large-scale inversion approach we have developed for obtaining optimal ice initial conditions [6]\, our workflow towards quantifying uncertainties in land-ice models\, and performance-portability of the Albany/FELIX code to new and emerging architectures using the Kokkos library [7]. I will show results which demonstrate that the Albany/FELIX dycore is scalable\, fast and robust for production-scale land-ice problems on state-of-the-art HPC machines. I will also discuss results from a recent validation study in which Albany/FELIX was used to simulate the Greenland ice sheet during the period 1991-2013 with realistic climate forcing\, and the simulation data were compared with observational data collected by NASA satellites [8]. \nThis work was done in collaboration with Irina Demeshko\, Mike Eldred\, Matt Hoffman\, John Jakeman\, Mauro Perego\, Steve Price\, Andy Salinger\, Ray Tuminaro and Jerry Watkins. \nDr. Tezaur is being hosted by Prof. Garikipati (Mechanical Engineering). If you would like to meet her please email mcteja@umich.edu \n[1] I. Velicogna. Increasing rates of ice mass loss from the Greenland and Antarctic ice sheets revealed by GRACE. Geophysical Research Letters\, 36 (19) L19503\, 2009.\n[2] S. Solomon\, D. Qin\, M. Manning\, Z. Chen\, M. Marquis\, K. Averyt\, M. Tignor\, H. Miller. Climate change 2007: The physical science basis\, Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change\, Cambridge Univ. Press\, Cambridge\, UK\, 2007.\n[3] I. Tezaur\, M. Perego\, A. Salinger\, R. Tuminaro\, S. Price. Albany/FELIX: A Parallel\, Scalable and Robust Finite Element Higher-Order Stokes Ice Sheet Solver Built for Advanced Analysis\, Geosci. Model Develop. 8 (2015) 1-24.\n[4] J.K. Dukowicz\, S.F. Price\, W. Lipscomb. Consistent approximations and boundary conditions for ice-sheet dynamics from a principle of least action. J. Glaciol.\, 56 (197) (2010) 480-496.\n[5] R. Tuminaro\, M. Perego\, I. Tezaur\, A. Salinger\, S. Price. A matrix dependent/algebraic multigrid approach for extruded meshes with applications to ice sheet modeling\, SIAM J. Sci. Comput. 38 (5) (2016) C504-C532.\n[6] M. Perego\, S. Price\, G. Stadler. Optimal initial conditions for coupling ice sheet models to earth system models\, J. Geophys. Res.\, 119 (2014) 1894-1917.\n[7] H.C. Edwards\, C.R. Trott\, D. Sunderland. Kokkos: Enabling manycore performance portability through polymorphic memory access patterns. J. Par. and Distr. Comput.\, 74 (12) 3202–3216\, 2014.\n[8] S. Price\, M. Hoffman\, J. Bonin\, T. Neumann\, I. Howat\, J. Guerber\, I. Tezaur\, J. Saba\, J. Lanaerts\, D. Chambers\, W. Lipscomb\, M. Perego\, A. Salinger\, R. Tuminaro. An ice sheet model validation framework for the Greenland ice sheet\, Geosci. Model Dev. 10 (2017) 255-270
URL:https://micde.umich.edu/event/micde-seminar-irina-tezaur-extreme-scales-data-science-analytics-department-sandia-national-laboratories/
LOCATION:1006 H.H. Dow\, 2300 Hayward St\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20171020T180000
DTEND;TZID=America/Detroit:20171020T190000
DTSTAMP:20260606T194052
CREATED:20230905T171415Z
LAST-MODIFIED:20230905T171415Z
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SUMMARY:SC2 Machine Learning Collaborative Workshop
DESCRIPTION:Machine Learning (ML) has found it’s way into much of today’s computational landscape and is a powerful tool to extract meaning from the large amounts of data generated by high performance computing. The Scientific Computing Student Club (SC2) has organized this workshop for students\, and all interested individuals\, with the goal of learning existing ML tools that can be easily integrate in research workflow.  Weekly meetings on Fridays @ 6:00 pm\, except November 24\, 2017. More information…
URL:https://micde.umich.edu/event/sc2-machine-learning-collaborative-workshop-2-6/
LOCATION:1311 EECS\, 1301 Beal Ave.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events
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GEO:42.292322;-83.713272
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DTSTART;TZID=America/Detroit:20171019T153000
DTEND;TZID=America/Detroit:20171019T163000
DTSTAMP:20260606T194052
CREATED:20230905T171415Z
LAST-MODIFIED:20230905T171415Z
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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
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20171019T120000
DTEND;TZID=America/Detroit:20171019T133000
DTSTAMP:20260606T194052
CREATED:20230905T171405Z
LAST-MODIFIED:20230905T171405Z
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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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