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DTSTART;TZID=America/Detroit:20220321T160000
DTEND;TZID=America/Detroit:20220321T170000
DTSTAMP:20260604T122626
CREATED:20210805T184953Z
LAST-MODIFIED:20230713T170841Z
UID:10000500-1647878400-1647882000@micde.umich.edu
SUMMARY:MICDE / MIDAS Seminar: Yun S. Song\, PhD\, Professor of Computer Science and Statistics\, University of California\, Berkeley
DESCRIPTION:ZOOM LINK\nBio: Professor Yun S. Song is a professor of EECS and Statistics working in mathematical and computational biology. He received his BS degrees in mathematics and physics from MIT\, and a PhD in physics from Stanford University.  Prof. Song’s research centers around computational and mathematical biology. He is generally interested in developing computational tools and statistical methods to facilitate the research of the broad biomedical community\, while also getting deeply involved in data analysis and interpretation.  Prof. Song is also interested in machine learning\, combinatorial optimization\, algorithms\, and Monte Carlo methods. \nRecent honors and awards include NIH Pathway to Independence Award K99/R00 (2006)\, Alfred P. Sloan Research Fellowship (2008)\, Packard Fellowship for Science and Engineering (2008)\, NSF CAREER Award (2009)\, Jim and Donna Gray Faculty Award for Excellence in Undergraduate Teaching (2013)\, Miller Research Professorship (2014)\, Math+X Simons Chair (2015)\, and Chan Zuckerberg Biohub Investigator Award (2017). \n\n  \nTalk Title: Mathematical and machine learning models for predicting protein synthesis and function\n  \nAbstract: Proteins are the workhorses of the cell and are involved in all aspects of cellular processes.  In spite of notable technological advances in protein biology and genomics over the past decade\, it remains an important challenge to unravel how protein synthesis and function are affected by genetic mutations.  In this talk\, I will describe our recent progress in tackling this challenge by leveraging new theoretical results on interacting particle systems and recent advances in natural language processing. \n\nThe MICDE Winter 2022 Seminar Series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nThis seminar is cohosted by the Michigan Institute for Computational Discovery (MICDE) and the Michigan Institute for Data Science (MIDAS). Dr. Song will be hosted by Dr. George Zhang\, Professor of Ecology and Evolutionary Biology. \nThis is a hybrid event and will be held in-person and broadcast online via Zoom. Note: You may register after the event has started. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-midas-seminar-yun-s-song-phd-professor-of-computer-science-and-statistics-university-of-california-berkeley/
LOCATION:West Hall 340
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2021/08/Yun-S.-Song.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20220317T140000
DTEND;TZID=America/Detroit:20220317T160000
DTSTAMP:20260604T122626
CREATED:20220112T185149Z
LAST-MODIFIED:20220112T185149Z
UID:10000560-1647525600-1647532800@micde.umich.edu
SUMMARY:Machine Learning on Great Lakes
DESCRIPTION:OVERVIEW\n\n\nThis workshop will go over methods and best practices for running machine learning applications on Great Lakes. We will briefly outline machine learning before stepping through a hands-on example problem to load a project and submit a job to the HPC cluster. Participants are expected to be familiar with Python\, the command line\, and basic Great Lakes functionality (logging in and navigating the directory structure). Participants must create a user account on Great Lakes prior to the workshop and are required to pre-register to gain access to a training account. \nINSTRUCTOR:\nMeghan Dailey\nMachine Learning Specialist\nInformation and Technology Services – Advanced Research Computing \nMeghan Dailey is a machine learning specialist in the Advanced Research Computing (ARC) department at the University of Michigan. She consults on several faculty and student machine learning applications and research studies\, specializing in natural language processing and convolutional neural networks. Before her position at the university\, Ms. Richey worked for a defense contractor as a software engineer to design and implement software solutions for DoD-funded artificial intelligence efforts. \nA Zoom link will be provided to the participants the day before the class. Registration is required.\n\n\nInstructor will be available at the Zoom link\, to be provided\, from 1:00-2:00 PM for computer setup assistance. \nPlease note\, this session will be recorded.   \nTo register and view more details\, please refer to the linked TTC page. \n\nIf you have questions about this workshop\, please send an email to the instructor at richeym@umich.edu
URL:https://micde.umich.edu/event/https-ttc-iss-lsa-umich-edu-ttc-sessions-machine-learning-for-great-lakes-2/
LOCATION:Your Desktop
CATEGORIES:Data Science,Great Lakes,High Performance Computing,Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20220317T100000
DTEND;TZID=America/Detroit:20220317T120000
DTSTAMP:20260604T122626
CREATED:20220113T170314Z
LAST-MODIFIED:20230217T195820Z
UID:10000561-1647511200-1647518400@micde.umich.edu
SUMMARY:Processing the CoreLogic Data on Great Lakes using PySpark
DESCRIPTION:OVERVIEW\nThis workshop provides an introduction to processing CoreLogic data using PySpark on the Great Lakes cluster. The CoreLogic dataset contains aggregated data from individual\, parcel-level real estate transactions and financial records. U-M has licensed access to Tax\, Deed\, and Foreclosure data at the parcel level for every county in the United States. We will demonstrate how to request access to the dataset\, and how to quickly get started with processing and running some basic analytics on the data with the user-friendly\, browser-based Open OnDemand tool and the PySpark language on the cluster. \nNote that a Great Lakes account is required for this workshop\, and you must have an account before the start of the workshop in order to participate in the exercises. See below for account request information. \nINSTRUCTORS:\n\nArmand Burks\nResearch Data Scientist Intermediate\nInformation and Technology Services – Advanced Research Computing \nArmand Burks\, Ph.D.\, is a research data scientist intermediate for Advanced Research Computing – Technology Services (ARC-TS)\, a division of Information and Technology Services (ITS). Armand helps researchers with establishing data workflows\, transforming data between different formats\, programming support\, optimizing/parallelizing code\, cloud computing with Hadoop\, and developing custom code (C++\, Java\, Python). He earned a B.S. in computer science from Alabama State University in 2008\, an M.S. in computer science and engineering from Michigan State University in 2010\, and a Ph.D. in computer science from Michigan State University in 2017. \n  \nJule Krüger\nProgram Manager\nCenter for Political Studies\, Institute for Social Research and Information and Technology Services – Advanced Research Computing \n\nJule Krüger\, Ph.D.\, is the ISR Program Manager for Big Data and Data Science\, based within the Center for Political Studies at the Institute for Social Research\, and a member of the Advanced Research Computing Consulting Services.  She has more than 10 years of experience in processing\, analyzing and interpreting data for social science research\, and automating workflows for scalable\, auditable and reproducible analysis. \nMATERIALS \nPrerequisites: Participants will need an active Great Lakes account and login in order to complete hands-on exercises. Some familiarity with PySpark is helpful. \nFor more information on The Great Lakes cluster\, click here https://arc.umich.edu/greatlakes/. \nClick here to fill out an account request form https://arc.umich.edu/login-request \nNote: 3 business days are needed for creation of accounts \nStudents should fill in “Workshop” in the “Advisor” section. \nCampus VPN access is required for off-campus access to Great Lakes but not from on campus. An SSH client\, and Duo will be required during the workshop in order to use Great Lakes.  If you do not have this software already\, please download and install the Cisco AnyConnect VPN software following these instructions: https://its.umich.edu/enterprise/wifi-networks/vpn/getting-started You will need this to be able to use the ssh client. You will need to use the ‘Campus All traffic’ profile in the Cisco client. \nRegister here \nA Zoom link will be provided to the participants the day before the class. Registration is required. \nPlease note\, this session will be recorded.   \n\nIf you have questions about this workshop\, please send an email to the instructors at julianek@umich.edu \n 
URL:https://micde.umich.edu/event/processing-the-corelogic-data-on-great-lakes-using-pyspark/
LOCATION:Your Desktop
CATEGORIES:Great Lakes
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20220314T140000
DTEND;TZID=America/Detroit:20220314T150000
DTSTAMP:20260604T122626
CREATED:20220121T172527Z
LAST-MODIFIED:20230713T171008Z
UID:10000554-1647266400-1647270000@micde.umich.edu
SUMMARY:MICDE Seminar: Marta D`Elia\, Principal Member of the Technical Staff\, Sandia National Laboratories
DESCRIPTION:WATCH THE RECORDING HERE. \nBio: Marta D’Elia is a Principal Member of the Technical Staff at Sandia National Laboratories\, where she works since 2014. She’s currently part of the Data Science and Computing group at the California site. She obtained her master degree in Mathematical Engineering at Politecnico of Milano with Prof. Quarteroni and she obtained her Ph.D in Applied Mathematics at Emory University with Prof. Veneziani. There\, she worked on optimal control in CFD for cardiovascular applications. She was a postdoctoral fellow at Florida State University where she worked with Prof. Gunzburger on optimization and control for nonlocal and fractional models. She’s an associate editor of the SIAM Journal on Scientific Computing\, Advances in Continuous and Discrete Models\, Numerical Methods for PDEs\, and the Journal of Peridynamics and Nonlocal Models. Also\, she’s a co-founder of the One Nonlocal World project. Her interests include nonlocal modeling and simulation\, optimization and optimal control\, and scientific machine learning. \nScientific interests: \n\nModeling and Computational aspects of Nonlocal and Fractional equations\,\nScientific Machine Learning\,\nOptimization and Uncertainty Quantification.\n\nDATA-DRIVEN LEARNING OF NONLOCAL MODELS: BRIDGING SCALES WITH NONLOCALITY \nNonlocal models are characterized by integral operators that embed length scales in their definition. As such\, they are preferable to classical partial differential equation models in situations where the dynamics of a system is affected by the small scale behavior\, yet the small scales would require prohibitive computational cost to be treated explicitly. In this sense\, nonlocal models can be considered as coarse-grained\, homogenized models that\, without resolving the small scales\, are still able to accurately capture the system’s global behavior. However\, nonlocal models depend on “kernel functions” that are often hand tuned.\nWe propose to learn optimal kernel functions from high fidelity data by combining machine learning algorithms\, known physics\, and nonlocal theory. This combination guarantees that the resulting model is mathematically well-posed and physically consistent. Furthermore\, by learning the operator rather than a surrogate for the solution\, these models generalize well to settings that are different from the ones used during training. We apply this learning technique to find homogenized nonlocal models for subsurface solute transport solely on the basis of breakthrough curves.\nWe also apply the same kernel-learning technique to design new stable and resolution-independent deep neural networks\, referred to as Nonlocal Kernel Networks (NKN). Stability of NKNs is obtained by imposing constraints derived from the nonlocal vector calculus\, whereas deep training is performed by means of a shallow-to-deep initialization technique. We demonstrate the accuracy and stability of NKNs on PDE-learning and image-classification problems. \n\nThe MICDE Winter 2022 Seminar Series is open to all. University of Michigan faculty and students interested in computational modeling and machine learning are encouraged to attend. \nThis seminar is cohosted by the Michigan Institute for Computational Discovery (MICDE) and the Department of Mechanical Engineering. Dr. D`Elia will be hosted by Dr. Krishna Garikipati\, Professor of Mechanical Engineering\, and of Mathematics. \nThis is a virtual event and will be broadcasted online via Zoom. MICDE students and fellows\, please use this form to record your attendance. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-marta-delia-phd-principal-member-of-the-technical-staff-at-sandia-national-laboratories-california/
LOCATION:Zoom Event\, MI\, United States
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2022/01/Marta-DElia.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20220311T090000
DTEND;TZID=America/Detroit:20220311T120000
DTSTAMP:20260604T122626
CREATED:20220110T225518Z
LAST-MODIFIED:20220110T225518Z
UID:10000562-1646989200-1647000000@micde.umich.edu
SUMMARY:Advanced Research Computing on the Great Lakes Cluster
DESCRIPTION:OVERVIEW\n\n\nThis workshop will cover some more advanced topics in computing on the U-M Great Lakes Cluster. Topics to be covered include a review of common parallel programming models and basic use of Great Lakes; dependent and array scheduling; workflow scripting using bash; high-throughput computing using launcher; parallel processing in one or more of Python\, R\, and MATLAB; and profiling of parallel code using Allinea Performance Reports and Allinea MAP. \n\nTo register and view more details\, please refer to the linked TTC page.
URL:https://micde.umich.edu/event/advanced-research-computing-on-the-great-lakes-cluster-7-2-2-2-3-2-2/
LOCATION:Your Desktop
CATEGORIES:Great Lakes,High Performance Computing,Workshops
ORGANIZER;CN="Advanced Research Computing":MAILTO:arc-contact@umich.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20220310T130000
DTEND;TZID=America/Detroit:20220310T160000
DTSTAMP:20260604T122626
CREATED:20220110T224913Z
LAST-MODIFIED:20220110T224913Z
UID:10000563-1646917200-1646928000@micde.umich.edu
SUMMARY:Introduction to Research Computing on the Great Lakes Cluster
DESCRIPTION:OVERVIEW\nThis workshop will introduce you to high performance computing on the Great Lakes cluster.  After a brief overview of the components of the cluster and the resources available there\, the main body of the workshop will cover creating batch scripts and the options available to run jobs\, and hands-on experience in submitting\, tracking\, and interpreting the results of submitted jobs. By the end of the workshop\, every participant should have created a submission script\, submitted a job\, tracked its progress\, and collected its output. Additional tools including high-performance data transfer services and interactive use of the cluster will also be covered. \nTo register and view more details\, please refer to the linked TTC page.
URL:https://micde.umich.edu/event/introduction-to-research-computing-on-the-great-lakes-cluster-14-2-2/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20220309T100000
DTEND;TZID=America/Detroit:20220309T120000
DTSTAMP:20260604T122626
CREATED:20211217T182335Z
LAST-MODIFIED:20211217T182335Z
UID:10000543-1646820000-1646827200@micde.umich.edu
SUMMARY:Software Development For Research: Version Control Principles
DESCRIPTION:Software development and computer programming is increasingly a major part of scientific research. Projects can quickly grow\, and it can be difficult to manage changes\, especially if multiple programmers are editing the same project at once! This workshop will cover Git\, a commonly-used tool for managing coding projects with multiple users\, with features to make or remove edits\, and track information related to those changes. After completing the workshop attendees will have a good understanding of Git workflow and will know how to perform the most common Git operations via the command line. \nThis is part of a series of workshops focused on both technical and soft skills regarding software engineering from a research perspective. \nPlease register at least 48 hours in advance.
URL:https://micde.umich.edu/event/software-development-for-research-version-control-principles-2/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20220309T090000
DTEND;TZID=America/Detroit:20220309T120000
DTSTAMP:20260604T122626
CREATED:20220110T231814Z
LAST-MODIFIED:20220110T231814Z
UID:10000564-1646816400-1646827200@micde.umich.edu
SUMMARY:Introduction to the Linux Command Line
DESCRIPTION:OVERVIEW\nThis course will familiarize the student with the basics of accessing and interacting with Linux computers using the GNU/Linux operating system’s Bash shell\, also generically referred to as “the command line”. Topics include: a brief overview of Linux\, the Bash shell\, navigating the file system\, basic commands\, shell redirection\, permissions\, processes\, and the command environment. The workshop will also provide a quick introduction to nano a simple text editor that will be used in subsequent workshops to edit files. \n  \nTo register and view more details\, please refer to the linked TTC page
URL:https://micde.umich.edu/event/introduction-to-the-linux-command-line-36-2-2/
LOCATION:Your Desktop
CATEGORIES:Workshops
ORGANIZER;CN="Advanced Research Computing":MAILTO:arc-contact@umich.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20220225T150000
DTEND;TZID=America/Detroit:20220225T160000
DTSTAMP:20260604T122626
CREATED:20230714T154821Z
LAST-MODIFIED:20230714T154821Z
UID:10000604-1645801200-1645804800@micde.umich.edu
SUMMARY:MICDE / AIM Seminar: Blaise Bourdin\, PhD\, Professor of Mathematics & Statistics\, McMaster University
DESCRIPTION:Zoom Link \nBio: Blaise Bourdin is a professor in the department of mathematics and statistics at McMaster University (Hamilton\, ON\, Canada). Dr. Bourdin’s formal training is at the meeting point of solid mechanics\, scientific computing\, and applied mathematics. He borrows techniques for these areas to study problems in mechanical science with a specific focus on problems involving defect mechanics and optimal design. He has cultivated this multi-disciplinary training by revisiting “classical” problems with more advanced technical tools\, by skewing my theoretical work towards problems of particular relevance to engineering and science\, and by using investigative numerical simulations as a modeling tool in complex multi-scale problems. \nDr. Bourdin’s research focusses on modeling\, analysis\, and numerical implementations of problems arising in reservoir engineering\, defect mechanics\, optimal design\, and image processing. He is the recipient of multiple research grants from the National Science Foundation\, the Louisiana Board of Regents and industry\, totalling over $6M. He has written several high impact publications\, including three ESI highly cited papers in two disciplines (mathematics and engineering). He also maintains several open source software projects. \nVARIATIONAL AND PHASE-FIELD MODELS OF BRITTLE FRACTURE: PAST SUCCESSES AND CURRENT ISSUES\nIn this talk Dr. Bourdin will start with a modern interpretation of Griffith’s classical criterion as a variational principle for a free discontinuity energy and will recall some of the milestones in its analysis. Then he will introduce the phase-field approximation per se and describe its numerical implementation. He will illustrate how phase-field models have led to major breakthroughs in the predictive simulation of fracture in complex situations. He will show how this applies to current issues\, including crack nucleation in nominally brittle materials\, fracture of heterogeneous materials\, and inverse problems.\n\n\n\n  \nThe MICDE Winter 2022 Seminar Series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nThis seminar is cohosted by the Michigan Institute for Computational Discovery (MICDE) and the Applied & Interdisciplinary Mathematics program at the University of Michigan. Dr. Bourdin will be hosted by Dr. Selim Esedoglu\, Professor of Mathematics. \nThis is a hybrid event and will be held in-person and broadcasted online via Zoom. Join here.  \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-aim-seminar-blaise-bourdin-phd-professor-of-mathematics-statistics-mcmaster-university-2/
LOCATION:Zoom Event
CATEGORIES:Education,Featured Events,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/07/Blaise-Bourdin.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20220225T150000
DTEND;TZID=America/Detroit:20220225T160000
DTSTAMP:20260604T122626
CREATED:20210805T194316Z
LAST-MODIFIED:20230515T013050Z
UID:10000501-1645801200-1645804800@micde.umich.edu
SUMMARY:MICDE / AIM Seminar: Blaise Bourdin\, PhD\, Professor of Mathematics & Statistics\, McMaster University
DESCRIPTION:THE SEMINAR WILL ONLY BE OFFERED ONLINE!\nWATCH THE RECORDING HERE. \nBio: Blaise Bourdin is a professor in the department of mathematics and statistics at McMaster University (Hamilton\, ON\, Canada). Dr. Bourdin’s formal training is at the meeting point of solid mechanics\, scientific computing\, and applied mathematics. He borrows techniques for these areas to study problems in mechanical science with a specific focus on problems involving defect mechanics and optimal design. He has cultivated this multi-disciplinary training by revisiting “classical” problems with more advanced technical tools\, by skewing my theoretical work towards problems of particular relevance to engineering and science\, and by using investigative numerical simulations as a modeling tool in complex multi-scale problems. \nDr. Bourdin’s research focusses on modeling\, analysis\, and numerical implementations of problems arising in reservoir engineering\, defect mechanics\, optimal design\, and image processing. He is the recipient of multiple research grants from the National Science Foundation\, the Louisiana Board of Regents and industry\, totalling over $6M. He has written several high impact publications\, including three ESI highly cited papers in two disciplines (mathematics and engineering). He also maintains several open source software projects. \nVariational and phase-field models of brittle fracture: Past successes and current issues\nIn this talk Dr. Bourdin will start with a modern interpretation of Griffith’s classical criterion as a variational principle for a free discontinuity energy and will recall some of the milestones in its analysis. Then he will introduce the phase-field approximation per se and describe its numerical implementation. He will illustrate how phase-field models have led to major breakthroughs in the predictive simulation of fracture in complex situations. He will show how this applies to current issues\, including crack nucleation in nominally brittle materials\, fracture of heterogeneous materials\, and inverse problems.\n\n\n\n  \nThe MICDE Winter 2022 Seminar Series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nThis seminar is cohosted by the Michigan Institute for Computational Discovery (MICDE) and the Applied & Interdisciplinary Mathematics program at the University of Michigan. Dr. Bourdin will be hosted by Dr. Selim Esedoglu\, Professor of Mathematics. \nThis is a hybrid event and will be held in-person and broadcasted online via Zoom. Join here.  \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-aim-seminar-blaise-bourdin-phd-professor-of-mathematics-statistics-mcmaster-university/
LOCATION:Zoom Event\, MI\, United States
CATEGORIES:Featured Events,Seminar
ATTACH;FMTTYPE=image/jpeg:https://micde.umich.edu/wp-content/uploads/2023/02/Blaise-Bourdin.jpeg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20220225T100000
DTEND;TZID=America/Detroit:20220225T113000
DTSTAMP:20260604T122626
CREATED:20220105T185837Z
LAST-MODIFIED:20220105T185837Z
UID:10000546-1645783200-1645788600@micde.umich.edu
SUMMARY:Introduction to Stata: Data Manipulation
DESCRIPTION:This is a series of workshops designed to introduce participants to the Stata software. No prior experience with Stata is required. The sections are: \nSection 1: The Basics of Stata – Interacting with Stata and working with data sets. (2/21\, 10:00 -11:30)\nSection 2: Data Management – The basics of maintaining and exploring a data set. (2/23\, 10:00-11:30)\nSection 3: Data Manipulation – Creating and modifying variables and other ways of manipulating your data. (2/25\, 10:00 – 11:30) \nYou do not need to attend all sessions; however\, the sessions build on each other and it will be assumed you are familiar with the material in earlier sessions. The workshop materials can be found at https://cscar.github.io/workshop-stata-intro/ for review. \nIt is strongly encouraged that you have Stata available on your local computer\, though not required. You may access Stata through midesktop (https://midesktop.umich.edu/) if needed.
URL:https://micde.umich.edu/event/introduction-to-stata-data-manipulation-3/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20220224T140000
DTEND;TZID=America/Detroit:20220224T160000
DTSTAMP:20260604T122626
CREATED:20220131T212440Z
LAST-MODIFIED:20230217T195819Z
UID:10000555-1645711200-1645718400@micde.umich.edu
SUMMARY:Reading and discussion group: Spatial Analysis in Social Sciences
DESCRIPTION:This reading group moderated by consultants from CSCAR will focus on spatial analysis especially as practiced in social sciences. We will meet for 1.5 to 2 hours every month on the fourth Thursday and discuss one or two chapters from relevant graduate level textbooks. We will focus on the concepts and applications but will also try to discuss the technical details. The format is open-ended\, and the key objective is to support learning at different knowledge and skill levels. If there is interest\, we will also cover software implementation of techniques in R or Python. We will select reading material that is available via U-M library or freely accessible online. \nReadings – We will discuss the following chapters: \n\n(2) Chapter 3: Global and local indicators of spatial association (from Spatial Analysis using Big Data by Yoshiki Yamagata and Hajime Seya) \n\n(3) Chapter 3: Spatial autocorrelation and statistical inference (from Spatial Analysis for Social Science by David Darmofal) \n\nDigital versions of the above two books are available from the UM Library.
URL:https://micde.umich.edu/event/reading-and-discussion-group-spatial-analysis-in-social-sciences/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20220223T100000
DTEND;TZID=America/Detroit:20220223T120000
DTSTAMP:20260604T122626
CREATED:20211217T181828Z
LAST-MODIFIED:20211217T181828Z
UID:10000542-1645610400-1645617600@micde.umich.edu
SUMMARY:Software Development For Research: Best Practices for Coding Styles
DESCRIPTION:Software development and computer programming is increasingly a major part of scientific research. Having a consistent coding style and following basic best practices used in the industry can help make your code easier to read and manage\, both internally in your teams and for public code projects available to other researchers. This workshop will cover some general guidelines and suggestions to clean up your coding style. Attendees will learn helpful tips for computer coding and how to make their code readable to other collaborators. \nThis is part of a series of workshops focused on both technical and soft skills regarding software engineering from a research perspective. \nPlease register at least 48 hours in advance.
URL:https://micde.umich.edu/event/software-development-for-research-best-practices-for-coding-styles-3/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20220223T100000
DTEND;TZID=America/Detroit:20220223T113000
DTSTAMP:20260604T122626
CREATED:20220105T185308Z
LAST-MODIFIED:20220105T185308Z
UID:10000545-1645610400-1645615800@micde.umich.edu
SUMMARY:Introduction to Stata: Data Management
DESCRIPTION:This is a series of workshops designed to introduce participants to the Stata software. No prior experience with Stata is required. The sections are: \nSection 1: The Basics of Stata – Interacting with Stata and working with data sets. (2/21\, 10:00 -11:30)\nSection 2: Data Management – The basics of maintaining and exploring a data set. (2/23\, 10:00-11:30)\nSection 3: Data Manipulation – Creating and modifying variables and other ways of manipulating your data. (2/25\, 10:00 – 11:30) \nYou do not need to attend all sessions; however\, the sessions build on each other and it will be assumed you are familiar with the material in earlier sessions. The workshop materials can be found at https://cscar.github.io/workshop-stata-intro/ for review. \nIt is strongly encouraged that you have Stata available on your local computer\, though not required. You may access Stata through midesktop (https://midesktop.umich.edu/) if needed.
URL:https://micde.umich.edu/event/section-2-data-management/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20220221T100000
DTEND;TZID=America/Detroit:20220221T113000
DTSTAMP:20260604T122626
CREATED:20220105T184745Z
LAST-MODIFIED:20220105T184745Z
UID:10000544-1645437600-1645443000@micde.umich.edu
SUMMARY:Introduction to Stata: The Basics of Stata
DESCRIPTION:This is a series of workshops designed to introduce participants to the Stata software. No prior experience with Stata is required. The sections are: \nSection 1: The Basics of Stata – Interacting with Stata and working with data sets. (2/21\, 10:00 -11:30)\nSection 2: Data Management – The basics of maintaining and exploring a data set. (2/23\, 10:00-11:30)\nSection 3: Data Manipulation – Creating and modifying variables and other ways of manipulating your data. (2/25\, 10:00 – 11:30) \nYou do not need to attend all sessions; however\, the sessions build on each other and it will be assumed you are familiar with the material in earlier sessions. The workshop materials can be found at https://cscar.github.io/workshop-stata-intro/ for review. \nIt is strongly encouraged that you have Stata available on your local computer\, though not required. You may access Stata through midesktop (https://midesktop.umich.edu/) if needed.
URL:https://micde.umich.edu/event/introduction-to-stata-the-basics-of-stata-3/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20220127T140000
DTEND;TZID=America/Detroit:20220127T160000
DTSTAMP:20260604T122626
CREATED:20220105T190817Z
LAST-MODIFIED:20230217T195803Z
UID:10000551-1643292000-1643299200@micde.umich.edu
SUMMARY:Reading and discussion group: Spatial Analysis in Social Science
DESCRIPTION:This reading group moderated by consultants from CSCAR will focus on spatial analysis especially as practiced in social sciences. We will meet for 1.5 to 2 hours every month on the fourth Thursday and discuss one or two chapters from relevant graduate level textbooks. We will focus on the concepts and applications but will also try to discuss the technical details. The format is open-ended\, and the key objective is to support learning at different knowledge and skill levels. If there is interest\, we will also cover software implementation of techniques in R or Python. We will select reading material that is available via U-M library or freely accessible online. \nReadings – For the first meeting scheduled on Jan 27th\, we will discuss the following chapters: \n(1) Chapter 2: Defining neighbors via a spatial weight matrix (from Spatial Analysis for Social Science by David Darmofal) \n(2) Chapter 3: Global and local indicators of spatial association (from Spatial Analysis using Big Data by Yoshiki Yamagata and Hajime Seya) \n(3) Chapter 3: Spatial autocorrelation and statistical inference (from Spatial Analysis for Social Science by David Darmofal) \nDigital versions of the above two books are available from the UM Library.
URL:https://micde.umich.edu/event/reading-and-discussion-group-spatial-analysis-in-social-science/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20220110T130000
DTEND;TZID=America/Detroit:20220110T160000
DTSTAMP:20260604T122626
CREATED:20211213T194126Z
LAST-MODIFIED:20230217T195800Z
UID:10000541-1641819600-1641830400@micde.umich.edu
SUMMARY:3D Visualization Software: Introduction to Unreal Engine and C++
DESCRIPTION:This is part of a series of workshops covering 3D game engines and animation software for research and data visualization. Registration to previous parts of this series is not required. \nUnreal Engine is a popular game engine among professional industries and game studios. It is also increasingly used for “serious” applications that require interactive 3D graphics and visualizations. Today\, Unreal Engine is available for free for creators not producing paid-for products. \nIn this workshop\, we’ll introduce the Unreal Engine workspace from a beginner’s perspective\, and prepare a simple data visualization with the interface\, including an introduction to its C++ workflow. Users will gain a basic understanding of the software\, and will be prepared to continue advanced training or to build simple examples in the software. \nA basic familiarity with any programming language (C++ will be used during the session) is recommended to get the most out of the workshop. Prior experience with any other 3D workspace for games\, animation\, visualization or science is encouraged. To take part\, users will be responsible to use their own laptop with Unreal Engine (available for Windows\, Macintosh and Linux\, but Windows is recommended) pre-installed. At this time\, Unreal Engine 4 is planned to be used\, pre-registered attendees will received a confirmation email about the version before the event. \nPlease register at least 48 hours in advance.
URL:https://micde.umich.edu/event/3d-visualization-software-introduction-to-unreal-engine-and-c/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20211208T160000
DTEND;TZID=America/Detroit:20211208T170000
DTSTAMP:20260604T122626
CREATED:20211129T204202Z
LAST-MODIFIED:20230713T171133Z
UID:10000540-1638979200-1638982800@micde.umich.edu
SUMMARY:James Stokes\, Research Fellow\, Flatiron Institute
DESCRIPTION:In person event (no zoom available)!! \n\nBio: Dr. James Stokes is a Research Fellow at the Flatiron Institute with a joint position at the Computational Center for Quantum Physics and the Center for Computational Mathematics.  He completed his Ph.D at the University of Pennsylvania\, focusing on quantum field theory. His recent research intersects machine learning\, quantum information and condensed matter physics. Previously\, James was a postdoctoral researcher in the Computer and Information Science Department at University of Pennsylvania from 2017 to 2018. James also worked as a quant in the finance industry before his postdoc and as a research scientist at a machine learning startup. \n  \nGeometry and numerics of variational quantum algorithms and classical counterparts\nStokes will review a family of variational algorithms which have been proposed as candidates to make use of near- to intermediate-term quantum computers\, placing particular emphasis on geometric and numeric features that are shared by classical variational stochastic approximation algorithms. Stokes will also discuss some applications of this hybrid quantum-classical approach to scientific and engineering problems beyond its traditional domain of application. \n  \n\nThis seminar is co-hosted by the Michigan Center for Applied & Interdisciplinary Mathematics (MCAIM) and the Michigan Institute for Computational Discovery and Engineering (MICDE) at the University of Michigan. Dr. Stokes will be hosted by Prof. Shravan Veerapaneni\, professor of mathematics. Questions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/james-stokes-flatiron-fall2021/
LOCATION:B844 East Hall\, 530 Church St\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2021/11/James-Stokes.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20211208T150000
DTEND;TZID=America/Detroit:20211208T160000
DTSTAMP:20260604T122626
CREATED:20210923T032752Z
LAST-MODIFIED:20230713T171305Z
UID:10000526-1638975600-1638979200@micde.umich.edu
SUMMARY:MICDE Seminar: Sarah Hormozi\, Associate Professor\, Cornell University
DESCRIPTION:WATCH THE RECORDING HERE. \n\nBio: Sarah Hormozi is an associate professor of Chemical and Biomolecular Engineering at Cornell University. Her expertise lies in complex fluid mechanics\, rheology\, and soft matter physics. Her research has been recognized by a number of awards\, including the National Science Foundation CAREER award and the ACS Petroleum Research Fund Doctoral New Investigator Award. She also serves on the advisory boards of Journals of Physical Review Fluids\, Non-Newtonian Fluid Mechanics\, The American Institute of Chemical Engineers\, and Physics of Fluids. \nSlurries of complex fluids\nSuspensions of non-Brownian particles in viscous fluids\, for which thermal fluctuations are negligible\, are relevant in industrial processes (e.g. waste disposal\, concrete\, drilling muds\, metalworking chip transport\, and food processing) and in natural phenomena (e.g. flows of slurries\, debris\, and lava). It is also relevant to mention that some biological and smart materials can be designed from various suspensions\, drawing attention to applications in physiology\, bio\nlocomotion\, shock absorbers\, and beyond. This countless number of suspensions has a wide range of nonlinear rheological behaviors\, such as shear thinning\, shear thickening\, shear banding\, yield stress\, and finite normal stress differences even when inertia is negligible.\nFor applications enumerated above\, even small increases in efficiency when processing slurries of complex fluids could make significant positive economic and environmental impacts. Obviously\, a thorough understanding of the rheology and fluid mechanics of these materials in natural and industrial settings is essential to improving the efficiency of production. However\, this is extremely challenging due to the complex rheology of the suspending fluids\, the interaction of fluid and particle phases\, and multiple-body and short-range interactions of particles. My presentation will introduce an array of experimental and modeling techniques that my research team uses to investigate the rheological properties and fluid dynamical behavior of complex suspensions. The goal is to establish a continuum framework and refine it through a series of microstructure investigations. I will discuss how our recent results can be used to address and resolve some of the industrial issues. Finally\, open questions will be disclosed\, which must be answered to build a firm foundation for a long-term contribution to the area of complex suspensions. \n\nThe MICDE Fall 2021 Seminar Series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nThis seminar is hosted by the Michigan Institute for Computational Discovery and Engineering (MICDE) at the University of Michigan. Dr. Hormozi will be hosted by Dr. Mariana Carrasco-Teja\, MICDE Associate Director and Assistant Research Scientist. Questions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-sarah-hormozi-ph-d-associate-professor-smith-school-of-chemical-and-biomolecular-engineering-cornell-university/
LOCATION:Zoom Event\, MI\, United States
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2021/09/Sarah-Hormozi.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20211203T150000
DTEND;TZID=America/Detroit:20211203T160000
DTSTAMP:20260604T122626
CREATED:20210923T031753Z
LAST-MODIFIED:20230713T171452Z
UID:10000525-1638543600-1638547200@micde.umich.edu
SUMMARY:MICDE / AIM: Youngsoo Choi\, Research Scientist\, Center for Applied Scientific Computing\, Lawrence Livermore National Laboratory
DESCRIPTION:Zoom link | Meeting ID: 964 5038 3843 | Psswd: 010182 \n\nBio: Youngsoo is a computational math scientist in CASC under Computing directorate at LLNL. He is currently leading data-driven reduced order model development team for various physical simulations\, with whom he developed the open source codes\, libROM (https://www.librom.net) and LaghosROM (https://github.com/CEED/Laghos/tree/rom/rom). libROM is a library for reduced order models and LaghosROM implements reduced order models for Lagrangian hydrodynamics (https://authors.elsevier.com/c/1e3CuAQEIviQh). He has earned his undergraduate degree for Civil and Environmental Engineering from Cornell University with applied mathematics as minor and his PhD degree for Computational and Mathematical Engineering from Stanford University. He was a postdoc in Sandia National Laboratory and Stanford University prior to joining LLNL in 2017. \nPhysics-constrained data-driven methods for accurately accelerating simulations\nA data-driven model can be built to accurately accelerate computationally expensive physical simulations\, which is essential in multi-query problems\, such as inverse problem\, uncertainty quantification\, design optimization\, and optimal control. In this talk\, two types of data-driven model order reduction techniques will be discussed\, i.e.\, the black-box approach that incorporates only data and the physics-constrained approach that incorporates the first principle as well as data. The advantages and disadvantages of each method will be discussed. Several recent developments of generalizable and robust data-driven physics-constrained reduced order models will be demonstrated for various physical simulations as well. For example\, a hyper-reduced time-windowing reduced order model overcomes the difficulty of advection-dominated shock propagation phenomenon\, achieving a speed-up of O(20~100) with a relative error much less than 1% for Lagrangian hydrodynamics problems\, such as 3D Sedov blast problem\, 3D triple point problem\, 3D Taylor–Green vortex problem\, 2D Gresho vortex problem\, and 2D Rayleigh–Taylor instability problem. The nonlinear manifold reduced order model also overcomes the challenges posed by the problems with Kolmogorov’s width decaying slowly by representing the solution field with a compact neural network decoder\, i.e.\, nonlinear manifold. The space–time reduced order model accelerates a large-scale particle Boltzmann transport simulation by a factor of 2\,700 with a relative error less than 1%. Furthermore\, successful application of these reduced order models for mate-material lattice–structure design optimization problems will be presented. Finally\, the library for reduced order models\, i.e.\, libROM (https://www.librom.net)\, and its webpage and several YouTube tutorial videos will be introduced\, which is useful for education as well as research purpose. \n\n  \nThe MICDE Fall 2021 Seminar Series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nThis seminar is cohosted by the Michigan Institute for Computational Discovery (MICDE) and the Applied and Interdisciplinary Mathematics program at the University of Michigan. Dr. Choi will be hosted by Dr. Jesse Capecelatro\, Assistant Professor of Mechanical Engineering and Aerospace Engineering. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-aim-youngsoo-choi-llnl/
LOCATION:Zoom Event\, MI\, United States
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2021/09/Youngsoo-Choi.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20211129T110000
DTEND;TZID=America/Detroit:20211129T123000
DTSTAMP:20260604T122626
CREATED:20211104T152416Z
LAST-MODIFIED:20230217T195758Z
UID:10000539-1638183600-1638189000@micde.umich.edu
SUMMARY:Introduction to Google Earth Engine - II
DESCRIPTION:Google Earth Engine (GEE) combines a multi-petabyte catalog of satellite imagery and geospatial datasets with planetary-scale analysis capabilities. The instant availability of data\, massive compute power\, and well-developed API make it a very convenient and powerful platform for geospatial analysis. \nGEE provides native APIs in JavaScript and Python. However\, recently the user community has developed a package “rgee (https://github.com/r-spatial/rgee)” that allows R users to interact with GEE (via reticulate and Python) and utilize its functionalities. \nThis workshop will focus on using R (the “rgee” package) to interface with GEE and utilize its power for ultra-fast geospatial analysis. You should attend the first workshop on November 18\, if you are new to GEE. \nSome familiarity with remote sensing and GIS\, and exposure to raster and vector data analysis will be helpful.  You will need to register (free) at signup.earthengine.google.com with Google to use the Earth Engine. Please use your UM email account to register.
URL:https://micde.umich.edu/event/introduction-to-google-earth-engine-ii/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20211118T140000
DTEND;TZID=America/Detroit:20211118T153000
DTSTAMP:20260604T122626
CREATED:20211104T161931Z
LAST-MODIFIED:20230217T195758Z
UID:10000538-1637244000-1637249400@micde.umich.edu
SUMMARY:Introduction to Google Earth Engine - I
DESCRIPTION:Google Earth Engine (GEE) combines a multi-petabyte catalog of satellite imagery and geospatial datasets with planetary-scale analysis capabilities. The instant availability of data\, massive compute power\, and well-developed API make it a very convenient and powerful platform for geospatial analysis. \nGEE provides native APIs in JavaScript and Python. However\, recently the user community has developed a package “rgee (https://github.com/r-spatial/rgee)” that allows R users to interact with GEE (via reticulate and Python) and utilize its functionalities. \nThe two hands-on workshops will introduce GEE and show how to leverage its capacity for spatiotemporal analysis and visualization in R. The first workshop (November 18) is an introduction to GEE and we will primarily use JavaScript API to learn the basics of GEE. The second workshop (November 22) will focus on using R (the “rgee” package) to interface with GEE and utilize its power for ultra-fast geospatial analysis. \nSome familiarity with remote sensing and GIS\, and exposure to raster and vector data analysis will be helpful.  You will need to register (free) at signup.earthengine.google.com with Google to use the Earth Engine. Please use your UM email account to register.
URL:https://micde.umich.edu/event/introduction-to-google-earth-engine-i/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20211115T130000
DTEND;TZID=America/Detroit:20211115T160000
DTSTAMP:20260604T122626
CREATED:20210805T231101Z
LAST-MODIFIED:20230217T195732Z
UID:10000505-1636981200-1636992000@micde.umich.edu
SUMMARY:3D Visualization Software: Advanced Graphics Optimization with Unity3D and C# (Part 3)
DESCRIPTION:This is part of a series of workshops covering 3D game engines and animation software for research and data visualization. Registration to all parts of this series is not required\, but each workshop will expect a different level of experience\, which will be acquired if the viewer attends all events. \nModern 3D game engines and computer hardware can render convincing graphics\, rivaling that of pre-rendered 3D animations. But video games still require special optimization techniques and tricks. This relates directly to the perceived capabilities for data visualization and serious applications: we can generate and render thousands of interactive objects in a game engine. But what about millions? \nThis workshop will go over different techniques to render as many objects as possible at once in Unity3D\, with the context of visualizing data as a point-cloud. Examples will include (but not be limited to) GPU Instancing\, Unity’s Particle System\, and Compute Shaders. It is strongly recommended that attendees be familiar with Unity3D prior to this workshop to get the most out of the session. The examples shown will be provided to registered users to try with a installation of Unity3D (if trying on your own machine\, you will need to install Unity3D in advance). \nPlease register at least 48 hours in advance.
URL:https://micde.umich.edu/event/3d-visualization-software-advanced-graphics-optimization-with-unity3d-and-c-part-3/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20211108T130000
DTEND;TZID=America/Detroit:20211108T160000
DTSTAMP:20260604T122626
CREATED:20210805T230234Z
LAST-MODIFIED:20230217T195731Z
UID:10000504-1636376400-1636387200@micde.umich.edu
SUMMARY:3D Visualization Software: Introduction to Blender3D and Python
DESCRIPTION:This is part of a series of workshops covering 3D game engines and animation software for research and data visualization. Registration to all parts of this series is not required\, but each workshop will expect a different level of experience\, which will be acquired if the viewer attends all events. \nBlender3D is a popular free and open-source alternative to industry-standard software\, to create high-quality 3D models and export 3D animations. In recent years\, it’s received financial backing from important industry leaders\, and is more advanced than ever. In addition to film and video games\, Blender3D can be used to create models for 3D printing\, virtual and augmented reality\, and even data visualization\, thanks in part to its open-source nature\, support for a variety of industry-standard file formats\, and support for Python scripting to automate tasks and customize tools. \nIn this workshop\, we’ll introduce the Blender interface and use Blender and Python to programmitcally generate a large 3D mesh from a dataset. Users will become familiar with the basic functions of the software\, and will become comfortable to learn more and use it for high-quality data visualizations. \nA basic familiarity with any computer programming language (Python will be used during the session) is recommended to get the most out of the workshop. To take part\, users will be responsible to use their own laptop with Blender3D (available for Windows\, Macintosh and Linux) pre-installed. Additional project files will be provided to registered users ahead of the workshop date. \nPlease register at least 48 hours in advance.
URL:https://micde.umich.edu/event/3d-visualization-software-introduction-to-blender3d-and-python/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20211104T140000
DTEND;TZID=America/Detroit:20211104T160000
DTSTAMP:20260604T122626
CREATED:20210819T173139Z
LAST-MODIFIED:20230217T195740Z
UID:10000517-1636034400-1636041600@micde.umich.edu
SUMMARY:Improving the performance of scientific software\, or "Do I really need to learn C++?"
DESCRIPTION:This is a continuation of the workshop “Introduction to performance analysis of scientific software“.  Now\, we know how to measure overall performance of our software and can make a good guess of the main performance bottleneck.  How can we improve the performance?  Do we really need to rewrite the whole program in a different language?  In this workshop\, we will observe and discuss various methods of performance improvement\, such as using optimized libraries\, multi-language development\, and choosing appropriate algorithms.  In the end\, you will know how to leverage the power of better algorithms and closer-to-metal languages to improve the performance of your software without a total rewrite or hardware upgrades. \nIt is recommended to attend “Introduction to performance analysis of scientific software” workshop prior to this one.  Participants are expected to know the basics of programming in some (any!) programming language. Some familiarity with the Unix command line and Python language would be helpful\, but is not required. If you wish to follow hands-on demonstrations\, you will need to use your own computer and have a UMich account.
URL:https://micde.umich.edu/event/improving-the-performance-of-scientific-software-or-do-i-really-need-to-learn-c/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20211104T120000
DTEND;TZID=America/Detroit:20211104T130000
DTSTAMP:20260604T122626
CREATED:20210923T030754Z
LAST-MODIFIED:20230713T171653Z
UID:10000524-1636027200-1636030800@micde.umich.edu
SUMMARY:MICDE / SPH: Laura Matrajt\, Staff Scientist\, Vaccine and Infectious Disease Division\, Fred Hutch
DESCRIPTION:Bio: Dr. Matrajt is a Staff Scientist in the Vaccine and Infectious Disease Division at the Fred Hutch research center in Seattle. She is an applied mathematician passionate about utilizing quantitative tools (mathematical and computer models\, statistics\, optimization theory) to understand complex biological processes. Her research lies at the interface of applied mathematics\, biology and public health policy. Dr. Matrajt uses a wide range of tools from applied mathematics including dynamical systems\, differential equations\, stochastic processes\, operations research and optimization theory to forward our understanding of infectious disease dynamics. \nDr. Matrajt was born and raised in Mexico City\, Mexico. She attended UNAM\, where she studied Mathematics as an undergraduate. Dr. Matrajt moved to Seattle\, WA\, where she completed a PhD in the Applied Mathematics Department at the University of Washington\, where she graduated in 2011. \nOptimizing COVID-19 vaccine allocation\nVaccines have proven to be our best tool to control the current COVID-19 pandemic. However\, due to limited vaccine supply\, vaccine prioritization has been\, and continues to be\, unavoidable. In this talk\, I will discuss two projects that used mathematical modeling combined with a fast optimization algorithm to determine the optimal use of these precious resources. In the first one\, we determined who should be vaccinated first\, and showed that the optimal use of COVID-19 vaccine depends on vaccine efficacy and vaccination coverage. In the second project we considered who should be vaccinated and how many doses they should get\, and found that optimal allocation strategies with one or two doses of vaccine depend on the efficacy after the first dose\, the background viral transmission and the amount of vaccine available. \n\nWATCH THE RECORDING HERE. \n\nThe MICDE Fall 2021 Seminar Series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nThis seminar is cohosted by the Michigan Institute for Computational Discovery (MICDE) and the department of Epidemiology within the School of Public Health at the University of Michigan. Dr. Matrajt will be hosted by Dr. Rafael Meza\, Professor of Epidemiology and Global Public Health. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-sph-laura-matrajt-ph-d-scientist-vaccine-and-infectious-disease-division-fred-hutchinson-cancer-research-center/
LOCATION:Zoom Event\, MI\, United States
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2021/09/Laura-Matrajt.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20211029T130000
DTEND;TZID=America/Detroit:20211029T143000
DTSTAMP:20260604T122626
CREATED:20210923T203358Z
LAST-MODIFIED:20210923T203358Z
UID:10000531-1635512400-1635517800@micde.umich.edu
SUMMARY:Introduction to Stata: Data Manipulation
DESCRIPTION:This is a series of workshops designed to introduce participants to the Stata software. No prior experience with Stata is required. The sections are: \nSection 1: The Basics of Stata – Interacting with Stata and working with data sets. (10/25\, 1-2:30) \nSection 2: Data Management – The basics of maintaining and exploring a data set. (10/27\, 1-2:30) \nSection 3: Data Manipulation – Creating and modifying variables and other ways of manipulating your data. (10/29\, 1-2:30) \nYou do not need to attend all sessions; however\, the sessions build on each other and it will be assumed you are familiar with the material in earlier sessions. The workshop materials can be found at https://cscar.github.io/workshop-stata-intro/ for review. \nIt is strongly encouraged that you have Stata available on your local computer\, though not required. You may access Stata through midesktop (https://midesktop.umich.edu/) if needed.
URL:https://micde.umich.edu/event/introduction-to-stata-data-manipulation-2/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20211028T160000
DTEND;TZID=America/Detroit:20211028T170000
DTSTAMP:20260604T122626
CREATED:20211021T140003Z
LAST-MODIFIED:20230217T195900Z
UID:10000547-1635436800-1635440400@micde.umich.edu
SUMMARY:PhD Seminar: Christiana Mavroyiakoumou and Vishwas Goel
DESCRIPTION:Register via Zoom to immediately receive login information. Note: You may register and join after the event has started. \n\nThe Ph.D. in Scientific Computing program is intended for students who will make extensive use of large-scale computation\, computational methods\, or algorithms for advanced computer architectures in their doctoral studies. This seminar series showcases the breadth of research covered by the program.  \nFeatured Speakers:\n\nCHRISTIANA MAVROYIAKOUMOU\, PhD Candidate\, Applied and Interdisciplinary Mathematics\, and Scientific Computing\nBio: Christiana Mavroyiakoumou is a 5th year PhD candidate in Applied and Interdisciplinary Mathematics\, working on extensible membrane flutter in inviscid flow using theoretical and computational tools. Her advisor is Professor Silas Alben at the Department of Mathematics. \nDYNAMICS OF TETHERED MEMBRANES IN INVISCID FLOW: We study the dynamics of membranes (with stretching stiffness but zero bending stiffness) that shed vortex wakes in inviscid flows. Previous studies have focused on membranes with fixed ends\, where only static deflection occurs. Here we consider instead membranes held by tethers with hinged ends\, and find that a variety of unsteady large-amplitude motions\, both periodic and chaotic\, may occur. We characterize the dynamics over ranges of the key parameters: membrane mass density\, stretching stiffness\, pretension\, and tether length. We find the region of instability and the small-amplitude behavior in a linearized model by solving a nonlinear eigenvalue problem. We also derive asymptotic scaling laws by considering a simplified model: an infinite periodic membrane. We find qualitative similarities among all three models in terms of the oscillation frequencies and membrane shapes at small and large values of the parameters. \nVISHWAS GOEL\, PhD Candidate\, MATERIALS SCIENCE AND ENGINEERING\, and Scientific Computing\nBio: I am a 4th Ph.D. student in the Department of Materials Science and Engineering. My research is focused on multi-scale modeling of electrochemical processes such as energy storage\, energy conversion\, and corrosion. \nMODELING BASED OPTIMIZATION OF HOLE ARCHITECTURE FOR ENABLING FAST CHARGING IN LI-ION BATTERIES: For the widespread adoption of electric vehicles\, we need Li-ion batteries (LIBs) that are energy and power dense. However\, we cannot realize both these properties even in state-of-the-art commercial Li-ion batteries. This inability is caused by the electrode design used in LIBs. In such a design\, to increase the energy density\, one needs to increase the active material loading (either in terms of active material mass fraction or the electrode thickness). However\, such a design proves to be highly tortuous for the transport of Li-ions in the electrolyte\, which causes the electrode to exhibit poor fast charging performance. \nIn our previous work [1]\, we demonstrated that the rate performance of the energy-dense electrodes can be improved by employing 3D architectures such as highly ordered laser-patterned electrodes (HOLE). The architecture alleviates the electrolyte mass transport limitations by providing rapid mass transport via laser-ablated channels through the electrode thickness. In this study\, we investigate how the geometric parameters of the HOLE design\, such as inter-channel spacing and channel radius\, affect the fast-charging performance of the HOLE graphite anodes with > 3 mAh/cm2 loading. We conduct this analysis using a fully parameterized continuum scale model based on the porous electrode theory. Our results show that for a constant volume retained (after the laser ablation)\, the smaller and closer channels exhibit better 4C charging performance than the larger and farther channels. \n1. K.-H. Chen et al.\, J. Power Sources\, 471\, 228475 (2020) doi.org/10.1016/j.jpowsour.2020.228475 \n\n  \nThis event is part of MICDE’s Fall 2021 seminar series featuring Ph.D. students in the Scientific Computing program. This 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 \n 
URL:https://micde.umich.edu/event/phd-seminar-christiana-mavroyiakoumou-and-vishwas-goel-2/
LOCATION:Zoom Event\, MI\, United States
CATEGORIES:Featured Events,Seminar
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20211028T150000
DTEND;TZID=America/Detroit:20211028T163000
DTSTAMP:20260604T122626
CREATED:20210901T153513Z
LAST-MODIFIED:20230217T195741Z
UID:10000521-1635433200-1635438600@micde.umich.edu
SUMMARY:GIS and Spatial Analysis Fundamentals – IV (Map visualization)
DESCRIPTION:This is the fourth workshop about the fundamentals of GIS and spatial analysis this semester. Each workshop covers one or two key elements and is self-contained. The focus is on conceptual details that can provide sufficient preparation for applications\, but we will also touch upon the technical aspects. Most workshops will have at least one hands-on exercise. Typically\, each workshop is divided into one hour of lecture-style presentation and half an hour of hands-on exercises. Unless mentioned otherwise\, we will use R and/or QGIS. \n  \nThis workshop will focus on basic cartography principles for map-making and explore the functionalities of R and QGIS for making production-quality single- and bi-variate static and dynamic choropleth map. We will also explore the functionalities of leaflet\, a powerful JavaScript library\, to create web maps and add extra information via elements such as pop-ups. \n  \nParticipants should have some familiarity with R\, but exposure to QGIS is not required.
URL:https://micde.umich.edu/event/gis-and-spatial-analysis-fundamentals-iv-map-visualization/
LOCATION:Your Desktop
CATEGORIES:Workshops
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20211027T130000
DTEND;TZID=America/Detroit:20211027T143000
DTSTAMP:20260604T122626
CREATED:20210923T202754Z
LAST-MODIFIED:20210923T202754Z
UID:10000528-1635339600-1635345000@micde.umich.edu
SUMMARY:Introduction to Stata: Data Management
DESCRIPTION:This is a series of workshops designed to introduce participants to the Stata software. No prior experience with Stata is required. The sections are: \nSection 1: The Basics of Stata – Interacting with Stata and working with data sets. (10/25\, 1-2:30) \nSection 2: Data Management – The basics of maintaining and exploring a data set. (10/27\, 1-2:30) \nSection 3: Data Manipulation – Creating and modifying variables and other ways of manipulating your data. (10/29\, 1-2:30) \nYou do not need to attend all sessions; however\, the sessions build on each other and it will be assumed you are familiar with the material in earlier sessions. The workshop materials can be found at https://cscar.github.io/workshop-stata-intro/ for review. \nIt is strongly encouraged that you have Stata available on your local computer\, though not required. You may access Stata through midesktop (https://midesktop.umich.edu/) if needed.
URL:https://micde.umich.edu/event/introduction-to-stata-data-management-2/
LOCATION:Your Desktop
CATEGORIES:Workshops
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