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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20201112T110000
DTEND;TZID=America/Detroit:20201112T120000
DTSTAMP:20260605T050322
CREATED:20230905T171255Z
LAST-MODIFIED:20230905T171255Z
UID:10000403-1605178800-1605182400@micde.umich.edu
SUMMARY:MICDE Seminar: Denise Kirschner\, Professor\, Microbiology and Immunology\, University of Michigan Medical School
DESCRIPTION:About Denise Kirschner: Dr. Kirschner received her Bachelors\, Masters and PhD in applied mathematics from Tulane University. She did graduate work also at Los Alamos National Labs and a postdoctoral fellowship at Vanderbilt University joint with the departments of Mathematics and Infectious Diseases. Over the past 25 years Dr. Kirschner has focused on questions related to models of host-pathogen interactions in infectious diseases. Her main focus has been to build models of persistent infections (e.g. Helicobacter pylori and Mycobacterium tuberculosis and HIV-1). Her goal is to understand the complex dynamics involved\, together with how perturbations to this interaction (via treatment with chemotherapies or immunotherapies) can lead to prolonged or permanent health. For the past 20 years\, her research focus has been on building multi-scale models to describe the host immune response to M. tuberculosis at multiple spatial and time scales and in multiple physiological compartments including lung\, lymph nodes and blood. \nTo date\, she have worked and collaborated with experimentalists generating data on TB with mouse\, non-human primate and human studies. Denise has over 150 publications in top journals describing this work that spans topics from methodological to biological advancement. Dr. Kirschner currently serves (and has for the past 17 years) as Editor-in-Chief of the Journal of Theoretical Biology. She serves as the founding co-director of The Center for Systems Biology at the University of Michigan\, an interdisciplinary center at the University of Michigan aimed to facilitate research and training between wet-lab and theoretical scientists. In 2016 she was elected as President-elect of the Society for Mathematical Biology and has served as its president from 2017-2020. Denise’s passion for mentoring students\, postdoctoral fellows and junior faculty has been a major focus of her career\, and her key mission is to promote both mathematics and family values in the scientific community.\n \nAPPROACHES FOR STUDYING MULTISCALE COMPUTATIONAL MODELS:  \nMycobacterium tuberculosis is a bacterium that infects 1/3 of the world today. While only 10% of infected individuals experience active tuberculosis disease\, if left untreated infection results in death. The remainder of individuals harbor the bacteria in a clinically latent infection\, and those individuals can experience reactivation of infection up to 10% per year. Our goal in a number of studies is to understand the role of the bacteria in initiating\, sustaining and inhibiting the immune response during infection. Granulomas are a hallmark of tuberculosis infection arising within lungs of infected humans. Understanding the immune response that leads to formation of granulomas can help us better design therapies to control or clear infection. We use a hybrid multi-scale approach that is fine grained for spatial details to help uncover these dynamics paired with a coarse grained spatial model that allows us to capture the entire host dynamics. We use a combination of statistic and mathematical and engineering approaches to predict optimal treatments. \n\nThe MICDE Fall 2020 and Winter 2021 Seminar Series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nWatch the full webinar here. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-denise-kirschner-professor-microbiology-and-immunology-university-of-michigan-medical-school/
LOCATION:Zoom Event
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2020/09/Denise-Kirschner.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20201110T100000
DTEND;TZID=America/Detroit:20201110T120000
DTSTAMP:20260605T050322
CREATED:20230905T171255Z
LAST-MODIFIED:20230905T171255Z
UID:10000385-1605002400-1605009600@micde.umich.edu
SUMMARY:Image Segmentation using Deep Learning with FastAI
DESCRIPTION:This workshop will demonstrate how to perform image segmentation using the FastAI [fast.ai] Python library\, which is built on the deep learning library PyTorch. Some familiarity with Python is expected\, but no previous experience with FastAI or PyTorch is needed. The workshop will be done online via BlueJeans. We will run the code using Google Colab\, which requires a Google account.
URL:https://micde.umich.edu/event/image-segmentation-using-deep-learning-with-fastai/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20201026T140000
DTEND;TZID=America/Detroit:20201026T153000
DTSTAMP:20260605T050322
CREATED:20230905T171255Z
LAST-MODIFIED:20230905T171255Z
UID:10000415-1603720800-1603726200@micde.umich.edu
SUMMARY: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:\n\nSection 1: The Basics of Stata – Interacting with Stata. (10/19 2-3:30)\nSection 2: Working with Data Sets – Importing\, opening\, and saving data sets. (10/21 2-3:30)\nSection 3: Data Management – The basics of maintaining and exploring a data set. (10/23 2-3:30)\nSection 4: Data Manipulation – Creating and modifying variables and other ways of manipulating your data. (10/26 2-3:30)\n\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.\n\nIt is strongly encouraged that you have a current version of Stata (version 16) available on your local computer\, though not required. You may access Stata through midesktop (https://midesktop.umich.edu/) if needed. If you have an older version of Stata\, some material may not work on your system.
URL:https://micde.umich.edu/event/stata-data-manipulation/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20201026T130000
DTEND;TZID=America/Detroit:20201026T160000
DTSTAMP:20260605T050322
CREATED:20230905T171255Z
LAST-MODIFIED:20230905T171255Z
UID:10000388-1603717200-1603728000@micde.umich.edu
SUMMARY:Data Visualization With 3D Graphics Using Unity3D and C#
DESCRIPTION:BlueJeans link will be shared with registered attendees 24 hours before start \nVideo game development is more accessible than ever before thanks to modern software tools\, with many options free to download. These tools are also used to program more “serious” applications that require interactive 3D graphics\, from mobile apps\, virtual and augmented reality\, computer vision and artificial intelligence\, and real-time CGI film production. \nUnity3D is a powerful and popular game engine for both hobbyist and professional projects\, able to compile a ‘game’ to almost any computer platform\, and free to download for non-commercial use. This workshop will show how you can use it to render data from research projects in a 3D interactive representation for user analysis and demonstration. \nIn this workshop\, we introduce the Unity3D workspace\, and prepare a demo that allows the user to load an example dataset and view it as a simple set of 3D representations. A basic familiarity with any computer programming language (C# 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 Unity3D (available for Windows\, Macintosh and Linux) pre-installed. Additional project files will be provided to registered users ahead of the workshop date.
URL:https://micde.umich.edu/event/data-visualization-with-3d-graphics-using-unity3d-and-c-3/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20201023T140000
DTEND;TZID=America/Detroit:20201023T153000
DTSTAMP:20260605T050322
CREATED:20230905T171255Z
LAST-MODIFIED:20230905T171255Z
UID:10000414-1603461600-1603467000@micde.umich.edu
SUMMARY: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:\n\nSection 1: The Basics of Stata – Interacting with Stata. (10/19 2-3:30)\nSection 2: Working with Data Sets – Importing\, opening\, and saving data sets. (10/21 2-3:30)\nSection 3: Data Management – The basics of maintaining and exploring a data set. (10/23 2-3:30)\nSection 4: Data Manipulation – Creating and modifying variables and other ways of manipulating your data. (10/26 2-3:30)\n\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.\n\nIt is strongly encouraged that you have a current version of Stata (version 16) available on your local computer\, though not required. You may access Stata through midesktop (https://midesktop.umich.edu/) if needed. If you have an older version of Stata\, some material may not work on your system.
URL:https://micde.umich.edu/event/stata-data-management/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20201021T140000
DTEND;TZID=America/Detroit:20201021T153000
DTSTAMP:20260605T050322
CREATED:20230905T171255Z
LAST-MODIFIED:20230905T171255Z
UID:10000413-1603288800-1603294200@micde.umich.edu
SUMMARY:Stata: Working with Data Sets
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:\n\nSection 1: The Basics of Stata – Interacting with Stata. (10/19 2-3:30)\nSection 2: Working with Data Sets – Importing\, opening\, and saving data sets. (10/21 2-3:30)\nSection 3: Data Management – The basics of maintaining and exploring a data set. (10/23 2-3:30)\nSection 4: Data Manipulation – Creating and modifying variables and other ways of manipulating your data. (10/26 2-3:30)\n\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.\n\nIt is strongly encouraged that you have a current version of Stata (version 16) available on your local computer\, though not required. You may access Stata through midesktop (https://midesktop.umich.edu/) if needed. If you have an older version of Stata\, some material may not work on your system.
URL:https://micde.umich.edu/event/stata-working-with-data-sets/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20201021T130000
DTEND;TZID=America/Detroit:20201021T170000
DTSTAMP:20260605T050322
CREATED:20230905T171256Z
LAST-MODIFIED:20230905T171256Z
UID:10000419-1603285200-1603299600@micde.umich.edu
SUMMARY:Mixed Models with R
DESCRIPTION:Mixed models are an extremely useful modeling tool for situations in which there is some dependency among observations in the data\, where the correlation typically arises from the observations being clustered in some way. For example\, it is quite common to have data in which we have repeated measurements for the units of observation\, or in which the units of observation are otherwise clustered (e.g. students within school\, cities within geographic region). While there are different ways to approach such a situation\, mixed models are a very common and powerful tool to do so.  In addition\, they have ties to other statistical approaches that further expand their applicability. \nThe goal of this workshop is primarily to provide a sense of when one would use mixed models and how to incorporate a variety of standard techniques.  It is very applied in nature\, and only assumes a basic understanding of standard regression models (and use of R for such models). \nLink: https://m-clark.github.io/mixed-models-with-R/
URL:https://micde.umich.edu/event/mixed-models-with-r-3/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20201020T150000
DTEND;TZID=America/Detroit:20201020T163000
DTSTAMP:20260605T050322
CREATED:20230905T171256Z
LAST-MODIFIED:20230905T171256Z
UID:10000421-1603206000-1603211400@micde.umich.edu
SUMMARY:QGIS-II
DESCRIPTION:This workshop will provide a hands-on exposure to geometrical operations on vector data in QGIS\, and will also cover a few basic operations that combine raster and vector data. The workshop will be especially useful for participants with some exposure to GIS (similar to the material covered in the previous workshop). \nThis workshop is virtual. The presenter will be in touch with more information after you register.
URL:https://micde.umich.edu/event/gis-ii/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20201020T150000
DTEND;TZID=America/Detroit:20201020T160000
DTSTAMP:20260605T050322
CREATED:20230905T171253Z
LAST-MODIFIED:20230905T171253Z
UID:10000402-1603206000-1603209600@micde.umich.edu
SUMMARY:MICDE Seminar: Grace Gu\, Assistant Professor\, Mechanical Engineering\, University of California- Berkeley
DESCRIPTION:About Grace Gu: Grace X. Gu is an Assistant Professor of Mechanical Engineering at the University of California\, Berkeley. She received her Ph.D. and MS in Mechanical Engineering from the Massachusetts Institute of Technology and her BS in Mechanical Engineering from the University of Michigan\, Ann Arbor. Her current research focuses on creating new materials with superior properties for mechanical\, biological\, and energy applications using multiphysics modeling\, artificial intelligence\, and high-throughput computing\, as well as developing intelligent additive manufacturing technologies to realize complex material designs previously impossible. Gu is the recipient of several awards\, including the 3M Non-Tenured Faculty Award\, MIT Tech Review Innovators Under 35\, Johnson & Johnson Women in STEM2D Scholars Award\, Royal Society of Chemistry Materials Horizons Outstanding Paper Prize\, and SME Outstanding Young Manufacturing Engineer Award. \n  \n\nMETAMATERIALS DESIGN AND MANUFACTURING: LEARNING FROM BIOLOGY AND ARTIFICIAL INTELLIGENCE\nAfter billions of years of evolution\, it is no surprise that biological materials are treated as an invaluable source of inspiration in the search for new materials. Additionally\, developments in computation spurred the fourth paradigm of materials discovery and design using artificial intelligence. Our research aims to advance design and manufacturing processes to create the next generation of high-performance engineering and biological materials by harnessing techniques integrating artificial intelligence\, multiphysics modeling\, and multiscale experimental characterization. This work combines computational methods and algorithms to investigate design principles and mechanisms embedded in materials with superior properties\, including bioinspired materials. Additionally\, we develop and implement deep learning algorithms to detect and resolve problems in current additive manufacturing technologies\, allowing for automated quality assessment and the creation of functional and reliable structural materials. These advances will find applications in robotic devices\, energy storage technologies\, orthopedic implants\, among many others. In the future\, this algorithmically driven approach will enable materials-by-design of complex architectures\, opening up new avenues of research on advanced materials with specific functions and desired properties. \n\nThe MICDE Fall 2020 and Winter 2021 Seminar Series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend. \nTo view the recording for this event\, please complete this form and a link will be sent to you. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-grace-gu-assistant-professor-mechanical-engineering-university-of-california-berkeley/
LOCATION:Zoom Event
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2020/09/Grace-Gu.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20201020T113000
DTEND;TZID=America/Detroit:20201020T130000
DTSTAMP:20260605T050322
CREATED:20230905T171253Z
LAST-MODIFIED:20230905T171253Z
UID:10000405-1603193400-1603198800@micde.umich.edu
SUMMARY:LSA Complex Systems / MICDE / MIDAS Seminar: Marissa Renardy\, Research Fellow\, Microbiology & Immunology\, University of Michigan
DESCRIPTION:Predicting the second wave of COVID-19 in Washtenaw County\, MI\nAbstract: In this work\, we study and predict the spread of COVID-19 in Washtenaw County\, MI through applying a discrete and stochastic network-based modeling framework. In this framework\, we construct contact networks based on synthetic population datasets specific for Washtenaw County that are derived from US Census datasets. We assign individuals to households\, workplaces\, schools\, and group quarters (such as prisons or long term care facilities). In addition\, we assign casual contacts to each individual at random. Using this framework\, we explicitly simulate Michigan-specific government-mandated workplace and school closures as well as social distancing measures. We perform sensitivity analyses to identify key model parameters and mechanisms contributing to the observed disease burden in the three months following the first observed cases of COVID-19 in Michigan. We then consider several scenarios for relaxing restrictions and reopening workplaces to predict what actions would be most prudent. In particular\, we consider the effects of 1) different timings for reopening\, and 2) different levels of workplace vs. casual contact re-engagement. Through simulations and sensitivity analyses\, we explore mechanisms driving the magnitude and timing of a second wave of infections upon re-opening. \nThis work is based on Dr. Renardy’s paper in press in the Journal of Theoretical Biology with coauthors:\nMarisa Eisenberg\, UM Complex Systems & Math (LSA) and Epidemiology (Public Health)\nDenise Kirschner\, UM Department of Microbiology & Immunology (Medical School) \nRegistration is not required for this event\, you may join the seminar via this link. \nThe recording of this webinar will be available for viewing soon! \nThis seminar is hosted by the LSA Center for the Study of Complex Systems\, and co-sponsored by the Michigan Institute for Computational Discovery & Engineering (MICDE) and the Michigan Institute for Data Science (MIDAS).
URL:https://micde.umich.edu/event/lsa-complex-systems-micde-midas-seminar-marissa-renardy-research-fellow-microbiology-immunology-university-of-michigan/
LOCATION:Zoom Event
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2020/09/Marissa-Renardy.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20201019T140000
DTEND;TZID=America/Detroit:20201019T153000
DTSTAMP:20260605T050322
CREATED:20230905T171253Z
LAST-MODIFIED:20230905T171253Z
UID:10000412-1603116000-1603121400@micde.umich.edu
SUMMARY: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:\n\nSection 1: The Basics of Stata – Interacting with Stata. (10/19 2-3:30)\nSection 2: Working with Data Sets – Importing\, opening\, and saving data sets. (10/21 2-3:30)\nSection 3: Data Management – The basics of maintaining and exploring a data set. (10/23 2-3:30)\nSection 4: Data Manipulation – Creating and modifying variables and other ways of manipulating your data. (10/26 2-3:30)\n\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.\n\nIt is strongly encouraged that you have a current version of Stata (version 16) available on your local computer\, though not required. You may access Stata through midesktop (https://midesktop.umich.edu/) if needed. If you have an older version of Stata\, some material may not work on your system.
URL:https://micde.umich.edu/event/stata-the-basics-of-stata/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20201016T090000
DTEND;TZID=America/Detroit:20201016T170000
DTSTAMP:20260605T050322
CREATED:20230905T171253Z
LAST-MODIFIED:20230905T171253Z
UID:10000400-1602838800-1602867600@micde.umich.edu
SUMMARY:Fundamentals of Accelerated Computing with CUDA C/C++
DESCRIPTION:The CUDA computing platform enables the acceleration of CPU-only applications to run on the world’s fastest massively parallel GPUs. Experience C/C++ application acceleration by: \n\nAccelerating CPU-only applications to run their latent parallelism on GPUs\nUtilizing essential CUDA memory management techniques to optimize accelerated applications\nExposing accelerated application potential for concurrency and exploiting it with CUDA streams\nLeveraging command line and visual profiling to guide and check your work\n\nUpon completion of this workshop\, you’ll be able to accelerate and optimize existing C/C++ CPU-only applications using the most essential CUDA tools and techniques. You’ll understand an iterative style of CUDA development that will allow you to ship accelerated applications fast. This workshop is presented by Kristopher Keipert of NVIDIA. \nThe workshop will use online tools\, so there is no need to install any software ahead of time. \nThis event is brought to you by the Michigan Institute for Computational Discovery and Engineering\, and Consulting for Statistics\, Computing & Analytics Research at the University of Michigan in partnership with NVIDIA. \nSpace is limited\, register today to save a seat!
URL:https://micde.umich.edu/event/fundamentals-of-accelerated-computing-with-cuda-c-c/
LOCATION:Zoom Event
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20201016T090000
DTEND;TZID=America/Detroit:20201016T170000
DTSTAMP:20260605T050322
CREATED:20230905T171253Z
LAST-MODIFIED:20230905T171253Z
UID:10000014-1602838800-1602867600@micde.umich.edu
SUMMARY:Fundamentals of Accelerated Computing with CUDA C/C++
DESCRIPTION:The CUDA computing platform enables the acceleration of CPU-only applications to run on the world’s fastest massively parallel GPUs. Experience C/C++ application acceleration by: \n\nAccelerating CPU-only applications to run their latent parallelism on GPUs\nUtilizing essential CUDA memory management techniques to optimize accelerated applications\nExposing accelerated application potential for concurrency and exploiting it with CUDA streams\nLeveraging command line and visual profiling to guide and check your work\n\nUpon completion\, you’ll be able to accelerate and optimize existing C/C++ CPU-only applications using the most essential CUDA tools and techniques. You’ll understand an iterative style of CUDA development that will allow you to ship accelerated applications fast. \nThe workshop will use online tools\, so there is no need to install any software ahead of time.
URL:https://micde.umich.edu/event/fundamentals-of-accelerated-computing-with-cuda-c-c-2/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20201013T140000
DTEND;TZID=America/Detroit:20201013T170000
DTSTAMP:20260605T050322
CREATED:20230905T171253Z
LAST-MODIFIED:20230905T171253Z
UID:10000420-1602597600-1602608400@micde.umich.edu
SUMMARY:R Series II: Programming
DESCRIPTION:People using R for applied research are often not taught basic programming practices such as writing functions\, efficient iterative processing\, vectorization\, and other practices that would make their research far more efficient and reproducible.  Understandably\, focus is on basic data manipulation and getting model results.  Unfortunately\, this can mean the data isn’t as explored as it should be\, or other opportunities are lost (e.g. feature engineering)\, because of the presumed effort that would be required to deal with the data more fully.\n\nThis workshop will help you get more out of R so that you can take your efforts to the next level.\n\n\nPrereq: Some basic experience using R is required (R Series I: Data Wrangling).  You should know how to create and manipulate objects\, run basic analyses\, etc.  This could also be useful to anyone with programming experience in another language like Python.\n\n\n\nContent Basis: https://m-clark.github.io/data-processing-and-visualization/
URL:https://micde.umich.edu/event/r-series-ii-programming/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20201013T100000
DTEND;TZID=America/Detroit:20201013T120000
DTSTAMP:20260605T050322
CREATED:20230905T171254Z
LAST-MODIFIED:20230905T171254Z
UID:10000384-1602583200-1602590400@micde.umich.edu
SUMMARY:Introduction to Deep Neural Networks with Keras/TensorFlow
DESCRIPTION:Deep Neural Networks (DNNs) are used as a machine learning method for both regression and classification problems. Keras is a high-level\, Python interface running on top of multiple neural network libraries\, including the popular library TensorFlow. In this workshop\, participants will learn how to quickly use the Keras interface to perform nonlinear regression and classification with standard fully-connected DNNs\, as well as image classification using Convolutional Neural Networks (CNNs). We will also look at regularization techniques and how to deal with under- and over-fitting. All examples will use Python; some familiarity with Python is recommended. The workshop will be done online via BlueJeans. We will run the models using Google Colab\, which requires a Google account.
URL:https://micde.umich.edu/event/introduction-to-deep-neural-networks-with-keras-tensorflow-8/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20201009T093000
DTEND;TZID=America/Detroit:20201009T160000
DTSTAMP:20260605T050322
CREATED:20230905T171254Z
LAST-MODIFIED:20230905T171254Z
UID:10000357-1602235800-1602259200@micde.umich.edu
SUMMARY:Workshop on Resilient Cities through Computation
DESCRIPTION:On October 9\, 2020 the Michigan Institute for Computational Discovery and Engineering will host the Workshop on Resilient Cities through Computation. In addition to talks by experts who are driving new fronts in computing and natural hazards\, it will include hands-on workshop’s goal is to introduce the Simple Run-Time Infrastructure software toolkit (SRTI). \nKeynote Speaker:\n\nTerri McAllister\nCommunity Resilience Group Leader and Program Manager\nNational Institute of Standards and Technology \nMore information at micde.umich.edu/workshop-resilient-cities-2020. \nThis event is organized by MICDE’s Center for Scientific Software Infrastructure and with support from the department of Civil and Environmental Engineering.
URL:https://micde.umich.edu/event/2020-micde-symposium/
LOCATION:Zoom Event\, MI\, United States
CATEGORIES:Conference,Featured Events
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20201008T133000
DTEND;TZID=America/Detroit:20201008T160000
DTSTAMP:20260605T050322
CREATED:20230905T171254Z
LAST-MODIFIED:20230905T171254Z
UID:10000395-1602163800-1602172800@micde.umich.edu
SUMMARY:GIS with R
DESCRIPTION:This workshop will expose participants to GIS functionalities in R. We will cover vector and raster data representation\, vector geometric operations\, coordinate representation\, combined raster and vector operations in R. The workshop will be especially useful for participants with some exposure to both GIS and R. \nThis workshop is virtual. The presenter will be in touch with more information after you register.
URL:https://micde.umich.edu/event/gis-with-r/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20201007T100000
DTEND;TZID=America/Detroit:20201007T120000
DTSTAMP:20260605T050322
CREATED:20230905T171254Z
LAST-MODIFIED:20230905T171254Z
UID:10000393-1602064800-1602072000@micde.umich.edu
SUMMARY:SPSS: Basic Statistical Analysis
DESCRIPTION:Each section will go over one chapter from the materials at https://cscar.github.io/workshop-spss/ \nSection 1: Basics of SPSS (9/16\, 10am – 12pm) \nSection 2: Variables (9/23\, 10am – 12pm) \nSection 3: Data Management (9/30\, 10am – 12pm) \nSection 4: Basic Statistical Analysis (10/7\, 10am – 12pm) \nIt is strongly encouraged to have SPSS installed on your machine. If you are accessing SPSS through AppsAnywhere on Virtual Sites\, then you will need to set up a link to your Google Drive\, Box\, or Dropbox storage.
URL:https://micde.umich.edu/event/spss-basic-statistical-analysis/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20201002T093000
DTEND;TZID=America/Detroit:20201002T120000
DTSTAMP:20260605T050322
CREATED:20230905T171254Z
LAST-MODIFIED:20230905T171254Z
UID:10000418-1601631000-1601640000@micde.umich.edu
SUMMARY:Intermediate SQL
DESCRIPTION:This workshop is a continuation of the Intro to SQL class.  We’ll cover how to create a table schema\, how to insert data into tables and some more intermediate SQL syntax. Attendees should already know basic SQL syntax like JOIN\, WHERE\, BETWEEN\, GROUP BY\, HAVING etc. A web-based tool will be used for the tutorial.
URL:https://micde.umich.edu/event/intermediate-sql-2/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20201002T090000
DTEND;TZID=America/Detroit:20201002T100000
DTSTAMP:20260605T050322
CREATED:20230905T171254Z
LAST-MODIFIED:20230905T171254Z
UID:10000422-1601629200-1601632800@micde.umich.edu
SUMMARY:Neuroimaging Initiative webinar: Bayesian scalar-on-image neural networks with application to neuroimaging data
DESCRIPTION:About Dr. Kang: Jian Kang is a Professor in the Department of Biostatistics and is a faculty member of the Kidney Epidemiology and Cost Center (KECC) at the University of Michigan.  He received his PhD in Biostatistics from the University of Michigan in 2011. He was an Assistant Professor in the Department of Biostatistics and Bioinformatics and the Department of Radiology and Imaging Sciences at Emory University from 2011 – 2015. He was a core faculty member in the Center for Biomedical Imaging Statistics (CBIS) at Emory University.  His primary research interests are in developing statistical methods for large-scale complex biomedical data with application in precision medicine\, imaging\, epidemiology and genetics. \n\nBAYESIAN SCALAR-ON-IMAGE NEURAL NETWORKS WITH APPLICATION TO NEUROIMAGING DATA\nDeep neural networks have been adopted in the scalar-on-image regression which predicts the outcome variable using image predictors. However\, training DNN often requires a large sample size to achieve a good prediction accuracy and the model fitting results can be difficult to interpret. In this work\, we construct a novel single-layer Bayesian neural network (BNN) with spatially-varying coefficients (SVC) for the scalar-on-image regression. Our goal is to select interpretable image features and to achieve the high prediction accuracy with limited training samples. We assign the soft-thresholded Gaussian process (STGP) prior to the SVCs and develop an efficient posterior computation algorithm based on stochastic gradient Langevin Dynamics (SGLD). The BNN-STGP provides a large prior support for sparse\, piecewise-smooth and continuous SVCs\, enabling efficient posterior inference on image feature selection and automatically determining the network structures. We establish the posterior consistency of estimating the SVCs in the model and image feature selection consistency when the number of voxels/pixels grows much faster than the sample size. We compared our methods with state-of-the-art deep learning methods via extensive simulations and analyses of multiple real datasets including the task fMRI data from the ABCD study. \n\nConnect to the webinar via this link. Meeting ID: 923 3875 2870. Meeting Passcode: 149254
URL:https://micde.umich.edu/event/bayesian-scalar-on-image-neural-networks-with-application-to-neuroimaging-data/
LOCATION:Zoom Event
CATEGORIES:Webinar
ATTACH;FMTTYPE=image/jpeg:https://micde.umich.edu/wp-content/uploads/2023/02/Jian-Kang-Headshot.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200930T150000
DTEND;TZID=America/Detroit:20200930T160000
DTSTAMP:20260605T050322
CREATED:20230905T171254Z
LAST-MODIFIED:20230905T171254Z
UID:10000398-1601478000-1601481600@micde.umich.edu
SUMMARY:CoreLogic property data
DESCRIPTION:The University of Michigan library system has licensed a large data set containing real estate transactions\, deeds\, and property tax records for the United States.  The data were collected by the commercial vendor CoreLogic\, and our license allows UM researchers to use the data for research purposes.  These data are of potential interest to researchers in many fields\, as they capture spatial and temporal real estate market conditions\, taxing practices\, and the physical states of millions of residential structures in the US.\n\n \nIn this workshop\, participants will learn to create geographical subsets of the data\, seamlessly integrate it in workflow\, and see examples of research questions where the data can be useful. Participants should know Python and R.
URL:https://micde.umich.edu/event/corelogic-property-data/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200930T130000
DTEND;TZID=America/Detroit:20200930T160000
DTSTAMP:20260605T050322
CREATED:20230905T171254Z
LAST-MODIFIED:20230905T171254Z
UID:10000416-1601470800-1601481600@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. \nPRE-REQUISITES\nThis course assumes familiarity with the Linux command line as might be got from the CSCAR/ARC-TS workshop Introduction to the Linux Command Line. In particular\, participants should understand how files and folders work\, be able to create text files using the nano editor\, be able to create and remove files and folders\, and understand what input and output redirection are and how to use them. \nINSTRUCTORS\nDr. Charles J Antonelli\nResearch Computing Services\nLSA Technology Services \nCharles is a member of the LSA Technology Services Research team at the University of Michigan\, where he is responsible for high performance computing support and education\, and was an Advocate to the Departments of History and Communications. Prior to this\, he built a parallel data ingestion component of a novel earth science data assimilation system\, a secure packet vault\, and worked on the No. 5 ESS Switch at Bell Labs in the 80s. He has taught courses in operating systems\, distributed file systems\, C++ programming\, security\, and database application design. \nJohn Thiels\nResearch Computing Services\nLSA Technology Services \nMATERIALS\n\nLecture Notes\nGreat Lakes Slurm HPC cluster\nGreat Lakes User Guide\nTwo-page Cheat Sheet\nMPI Profiling with Allinea MAP\n\n\nCOURSE PREPARATION\nIn order to participate successfully in the workshop exercises\, you must have a user login\, a Slurm account\, and be enrolled in Duo. The user login allows you to log in to the cluster\, create\, compile\, and test applications\, and prepare jobs for submission. The Slurm account allows you to submit those jobs\, executing the applications in parallel on the cluster and charging their resource use to the account. Duo is required to help authenticate you to the cluster. \nUSER LOGIN\nIf you already have a Great Lakes user login\, you don’t need to do anything.  Otherwise\, go to the Great Lakes user login application page at: http://arc-ts.umich.edu/login-request/ . \nPlease note that obtaining a user account requires human processing\, so be sure to do this at least two business days before class begins. \nSLURM ACCOUNT\nWe create a Slurm account for the workshop so you can run jobs on the cluster during the workshop and for one day after for those who would like additional practice. The workshop job account is quite limited and is intended only to run examples to help you cement the details of job submission and management. If you already have an existing Slurm account\, you can use that\, though if there are any issues with that account\, we will ask you to use the workshop account. \nDUO AUTHENTICATION\nDuo two-factor authentication is required to log in to the cluster. When logging in\, you will need to type your UMICH (AKA Level 1) password as well as authenticate through Duo in order to access Great Lakes. \nIf you need to enroll in Duo\, follow the instructions at Enroll a Smartphone or Tablet in Duo. \nPlease enroll in Duo before you come to class. \n\nLAPTOP PREPARATION\nYou will need VPN software to access the U-M network.  If you do not have VPN software already installed\, please download and install the Cisco AnyConnect VPN software following these instructions.  You will need VPN to be able to use the ssh client to connect to Great Lakes. Please use the ‘Campus All traffic’ profile in the Cisco client. \nYou will need an ssh client to connect to the Great Lakes cluster. Mac OS X and Linux platforms have this built-in. Here are a couple of choices for Windows platforms: \n\nDownload and install U-M PuTTY/WinSCP from the Compute at the U website. This includes both the PuTTY ssh client and terminal emulator and a graphical file transfer tool in one installer.  This document describes how to download and use this software\, except please note you will be connecting to greatlakes.arc-ts.umich.edu instead of the cited host.  You must have administrative authority over your computer to install this software.\nDownload PuTTY directly from the developer. Download the putty.exe application listed under “Alternative binary files\,”\, then execute the application.  You do not need administrative authority over your computer to use this software.\n\nOur Great Lakes User Guide in Section 1.2 describes in more detail how to use PuTTY to connect to Great Lakes. \nPlease prepare and test your computer’s ability to make remote connections before class; we cannot stop to debug connection issues during the class. \n\nA Zoom link will be provided to the participants the day before the class. Registration is required.Please note this session will be recorded.
URL:https://micde.umich.edu/event/advanced-research-computing-on-the-great-lakes-cluster-4/
LOCATION:Your Desktop
CATEGORIES:Great Lakes,High Performance Computing,Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200930T100000
DTEND;TZID=America/Detroit:20200930T120000
DTSTAMP:20260605T050322
CREATED:20230905T171252Z
LAST-MODIFIED:20230905T171252Z
UID:10000392-1601460000-1601467200@micde.umich.edu
SUMMARY:SPSS: Data Management
DESCRIPTION:Each section will go over one chapter from the materials at https://cscar.github.io/workshop-spss/ \nSection 1: Basics of SPSS (9/16\, 10am – 12pm) \nSection 2: Variables (9/23\, 10am – 12pm) \nSection 3: Data Management (9/30\, 10am – 12pm) \nSection 4: Basic Statistical Analysis (10/7\, 10am – 12pm) \nIt is strongly encouraged to have SPSS installed on your machine. If you are accessing SPSS through AppsAnywhere on Virtual Sites\, then you will need to set up a link to your Google Drive\, Box\, or Dropbox storage.
URL:https://micde.umich.edu/event/spss-data-management/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200929T140000
DTEND;TZID=America/Detroit:20200929T163000
DTSTAMP:20260605T050322
CREATED:20230905T171252Z
LAST-MODIFIED:20230905T171252Z
UID:10000417-1601388000-1601397000@micde.umich.edu
SUMMARY:Intro to SQL
DESCRIPTION:Ever want to know how to communicate with a database? You need to know SQL\, a standard programming language for working with relational database management systems in data warehouses or just Microsoft Access. This workshop will cover the basic syntax of SQL. Material will focus mainly on how to query databases. A web-based tool will be used for the tutorial.
URL:https://micde.umich.edu/event/intro-to-sql-7/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200929T140000
DTEND;TZID=America/Detroit:20200929T150000
DTSTAMP:20260605T050322
CREATED:20230905T171252Z
LAST-MODIFIED:20230905T171252Z
UID:10000409-1601388000-1601391600@micde.umich.edu
SUMMARY:MICDE / Mechanical Engineering Seminar: Sophia Haussener\, Associate Professor\, Laboratory of Renewable Energy Science and Engineering\, EPFL\, Lausanne\, Switzerland
DESCRIPTION:View webinar recording. \nBio: Sophia Haussener is an Associate Professor heading the Laboratory of Renewable Energy Science and Engineering at the Ecole Polytechnique Fédérale de Lausanne (EPFL). Her current research is focused on providing design guidelines for thermal\, thermochemical\, and photoelectrochemical energy conversion reactors through multi-physics modelling. Her research interests include: thermal sciences\, fluid dynamics\, charge transfer\, electro-magnetism\, and thermo/electro/photochemistry in complex multi-phase media on multiple scales. She received her MSc (2007) and PhD (2010) in Mechanical Engineering from ETH Zurich. Between 2011 and 2012\, she was a postdoctoral researcher at the Joint Center of Artificial Photosynthesis (JCAP) and the Energy Environmental Technology Division of the Lawrence Berkeley National Laboratory (LBNL). She has published over 70 articles in peer-reviewed journals and conference proceedings\, and 2 books. She has been awarded the ETH medal (2011)\, the Dimitris N. Chorafas Foundation award (2011)\, the ABB Forschungspreis (2012)\, the Prix Zonta (2015)\, the Global Change Award (2017)\, and the Viskanta Award (2019)\, and is a recipient of a Starting Grant of the Swiss National Science Foundation (2014). She is a deputy leader in the Swiss Competence Center for Energy Research (SCCER) on energy storage and acts as a Member of the Scientific Advisory Council of the Helmholtz Zentrum. \nModelling\, experimentation and scaling of photo-electrochemical fuel processing devices\nThe development of a sustainable energy economy based on renewable\, carbon-neutral energy is a necessary and urgent task. Photo-electrochemical approaches for solar fuels and materials are interesting\, provided they can be efficiently\, stably\, scalably\, and sustainably implemented. The functionality of such devices relies on complicated and coupled multi-physics processes\, occurring at multiple temporal and spatial scales. Device modelling can actively and efficiently support the choice of the most promising – in terms of efficiency\, cost\, robustness\, scalability\, and practicability – conceptual design pathways\, material choices\, and operating approaches. \nFirst\, I focus on cost competitive photo-electrochemical (PEC) devices identified through quasi-transient techno-economic modelling [1]. I will describe the conceptual idea of thermal integration in the context of PEC [2]\, provide results of maximum theoretical efficiency calculations to quantify the benefits\, and review the modelling framework that enabled the design of a feasible device [3]. I will illustrate how we have used our models to design and implement a PEC device with a solar-to-fuel efficiency of 17%\, and discuss ongoing approaches to scale up by our lab in order to bridge the gap between research and practical applications. \nSecond\, I will discuss detailed multi-dimensional mesoscale models that allow to assess the transport in complex (photo)electrodes. Specifically\, we use direct pore-level simulations for the coupled transport characterization of mesostructured (photo)electrodes utilizing nano-tomography techniques to obtain the exact mesostructure that is utilized in direct numerical simulations [4]. I will extend these investigations to ordered structures for the assessment of the transport in mesostructured electrodes for the electorchemical reduction of CO2 and discuss the effect of the mass transport on selectivity and activity [5]. I will then present possibilities to simplify these involved multi-dimensional numerical models into rapid screening models based on semi-analytical correlations. I will discuss analysis results for a large range of semiconductor materials [6\,7]. I will end with an outlook on research challenges and gaps in the field of (photo)electrochemical water and CO2 splitting. \n\nThis seminar is co-hosted by the Michigan Institute for Computational Discovery & Engineering\, and the Mechanical Engineering department within the University of Michigan College of Engineering. Dr. Haussener will be hosted by Rohini Bala Chandran\, Assistant Professor of Mechanical Engineering. \nThe MICDE Fall 2020 and Winter 2021 Seminar Series is open to the general public. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend.  \nQuestions? Email MICDE-events@umich.edu \n\nReferences: \n[1] M. Dumortier\, S. Tembhurne\, S. Haussener\, Energy Environ. Sci. \, 8:3614–3628\, 2015\n[2] S. Tembhurne\, F. Nandjou\, S. Haussener\, Nature Energy\, 10.1038/s41560-019-0373-7\, 2019\n[3] S. Tembhurne\, S. Haussener\, Journal of The Electrochemical Society \, 163:H1008-H1018\, 2016\n[4] S. Suter\, M. Catoni\, Y. Gaudy\, S. Pokrant\, S. Haussener\, Linking Morphology and Multi-Physical Transport in\nStructured Photoelectrodes\, Sustainable Energy & Fuels \, doi: 10.1039/C8SE00215K\, 2018.\n[5] S. Suter\, S. Haussener\, Energy Environmental Science \, doi: 10.1039/C9EE00656G\, 2019.\n[6] Y. Gaudy\, S. Haussener\, Rapid Performance Optimization Method for Photoelectrodes\, Journal of Physical Chemistry\nC\, doi: 10.1021/acs.jpcc.9b04102\, 2019.\n[7] Y. Gaudy\, Z. Gacevic\, Haussener\, Theoretical maximum photogeneration efficiency and performance characterization\nof InxGa1-xN/Si tandem water-splitting photoelectrodes\, APL Materials\, accepted\, 2020.
URL:https://micde.umich.edu/event/micde-mechanical-engineering-seminar-sophia-haussener-associate-professor-laboratory-of-renewable-energy-science-and-engineering-swiss-federal-institute-of-technology-lausanne/
LOCATION:Zoom Event
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2020/09/Sophia-Haussener.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200929T080000
DTEND;TZID=America/Detroit:20200929T170000
DTSTAMP:20260605T050322
CREATED:20230905T171252Z
LAST-MODIFIED:20230905T171252Z
UID:10000010-1601366400-1601398800@micde.umich.edu
SUMMARY:The 2020 MICDE Annual Symposium
DESCRIPTION:On September 29\, 2020 the Michigan Institute for Computational Discovery and Engineering will host its 2020 Annual Symposium. In addition to talks by external experts who are driving new fronts in computing\, the Symposium will showcase some of the game-changing research supported by our Catalyst Grants program\, and the workshop on Resilient Cities through Computation organized by MICDE’s Center for Scientific Software Infrastructure and with support from the department of Civil and Environmental Engineering. \nKeynote Speakers\n\nEwa Deelman\nResearch Professor and Research Director\nInformation Sciences Institute\nUniversity of Southern California \n\nIan Foster \nProfessor\, Computer Science\nUniversity of Chicago\nDirector\, Data Science and Learning Division\nArgonne National Laboratory \nA poster competition will be held\, open to post-docs and graduate students. \nMore information will be posted here as it becomes available. Also see https://live-umor-micde.pantheonsite.io/symposium20/
URL:https://micde.umich.edu/event/2020-micde-annual-symposium/
LOCATION:MI
CATEGORIES:Conference,Featured Events
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200928T170000
DTEND;TZID=America/Detroit:20200928T210000
DTSTAMP:20260605T050322
CREATED:20230905T171252Z
LAST-MODIFIED:20230905T171252Z
UID:10000011-1601312400-1601326800@micde.umich.edu
SUMMARY:Student Hackathon: creating a hybrid simulation system using the Simple Run Time Infrastructure Software
DESCRIPTION:The hackathon’s goal is to introduce the Simple Run-Time Infrastructure software toolkit (SRTI) to the participants\, and provide a template project consisting of multiple simulators\, each with a specialized purpose\, relating to a natural-disaster scenario. \nThis is a free event and all students from any school/institution are welcome. You need basic coding skills to participate. \nThe first\, second and third place winners will received monetary prizes of $1000\, $600 and $400. \nThe hacakthon is part of the 2020 MICDE Symposium and is sponsored by MICDE and the Civil and Environmental Engineering department. \nFor more information https://live-umor-micde.pantheonsite.io/symposium20/
URL:https://micde.umich.edu/event/student-hackathon-creating-a-hybrid-simulation-system-using-the-simple-run-time-infrastructure-software/
LOCATION:MI
CATEGORIES:Featured Events,Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200924T140000
DTEND;TZID=America/Detroit:20200924T170000
DTSTAMP:20260605T050322
CREATED:20230905T171252Z
LAST-MODIFIED:20230905T171252Z
UID:10000410-1600956000-1600966800@micde.umich.edu
SUMMARY:R I: Data Wrangling
DESCRIPTION:This workshop will delve into common data processing and exploration techniques using R. The main focus will be on constructing and manipulating R data objects\, and using packages that enhance and facilitate operations that typically arise when dealing with data\, including faster I/O\, variable creation and manipulation\, and grouped operations\, especially as a prelude to visualization. \nLink: https://m-clark.github.io/data-processing-and-visualization/
URL:https://micde.umich.edu/event/r-i-data-wrangling-2/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200923T140000
DTEND;TZID=America/Detroit:20200923T170000
DTSTAMP:20260605T050322
CREATED:20230905T171252Z
LAST-MODIFIED:20230905T171252Z
UID:10000399-1600869600-1600880400@micde.umich.edu
SUMMARY:Using GPUs with Python
DESCRIPTION:Python is the Lingua Franca of Data today and is being increasingly used in scientific computations. This workshop introduces Python GPU tools for porting and writing code that runs on GPUs. The primary tools\, Numba and CuPy\, are presented with examples. This workshop is presented by Kristopher Keipert of NVIDIA. \nThis event is open to students\, faculty\, and staff within the University of Michigan community. A Jupyter notebook is used along with a set of lecture slides. The workshop will use online tools\, so there is no need to install any software ahead of time. \n  \nThis event is brought to you by the Michigan Institute for Computational Discovery and Engineering\, and Consulting for Statistics\, Computing & Analytics Research at the University of Michigan in partnership with NVIDIA. \nRegistration for this event has closed.
URL:https://micde.umich.edu/event/using-gpus-with-python-workshop-by-nvidia/
LOCATION:Zoom Event
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200923T140000
DTEND;TZID=America/Detroit:20200923T170000
DTSTAMP:20260605T050322
CREATED:20230905T171252Z
LAST-MODIFIED:20230905T171252Z
UID:10000013-1600869600-1600880400@micde.umich.edu
SUMMARY:Using GPUs with Python
DESCRIPTION:Python is the Lingua Franca of Data today and is being increasingly used in scientific computations. This workshop introduces Python GPU tools for porting and writing code that runs on GPUs. The primary tools\, Numba and CuPy\, are presented with examples. A Jupyter notebook is used along with a set of lecture slides. \nThe workshop will use online tools\, so there is no need to install any software ahead of time.
URL:https://micde.umich.edu/event/using-gpus-with-python/
LOCATION:Your Desktop
CATEGORIES:Workshops
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/02/NVIDIA-Workshops-Twitter-Events-Images-2.png
END:VEVENT
END:VCALENDAR