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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20240918T120000
DTEND;TZID=America/Detroit:20240918T130000
DTSTAMP:20241011T124420Z
CREATED:20240910T182150Z
LAST-MODIFIED:20241011T124420Z
UID:10000747-1726660800-1726664400@micde.umich.edu
SUMMARY:Data Science/Computational Social Science/MICDE Seminar: Yian Ma\, Assistant Professor\, UC San Diego
DESCRIPTION:Bio:  Yian Ma is an assistant professor at the Halıcıoğlu Data Science Institute\, UC San Diego\, where he serves as the vice chair for the graduate programs. Prior to UCSD\, he spent a year as a visiting faculty at Google Research. Before that\, he was a post-doctoral fellow at UC Berkeley\, hosted by Mike Jordan. Yian completed his Ph.D. at the University of Washington. His current research primarily revolves around scalable inference methods for credible machine learning\, with application to time series data and sequential decision-making tasks. He has received the Facebook research award\, the Stein fellowship\, and the best paper awards at the Neurips and ICML workshops. \nMCMC\, variational inference\, and reverse diffusion Monte Carlo\nProf. Ma will introduce some recent progress toward understanding the scalability of Markov chain Monte Carlo (MCMC) methods and their comparative advantage with respect to variational inference. I will fact-check the folklore that “variational inference is fast but biased\, MCMC is unbiased but slow”. I will then discuss a combination of the two via reverse diffusion\, which holds promise of solving some of the multi-modal problems. This talk will be motivated by the need for Bayesian computation in reinforcement learning problems and the differential privacy requirements we face. \nRSVP HERE \n\n  \nThe MICDE Winter 2025 Seminar Series is open to all. University of Michigan faculty and students. \nThis is an in-person event. \nGraduate Certificate in Computational Discovery and Engineering\, please use this form to record your attendance. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/data-science-computational-social-science-micde-seminar-yian-ma-assistant-professor-uc-san-diego/
LOCATION:438 West Hall\, 1085 UNIVERSITY AVE\, Ann Arbor\, 48109\, United States
CATEGORIES:Data Science,Featured Events,Micde Seminar,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2024/09/Yian-Ma.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20240419T110000
DTEND;TZID=America/Detroit:20240419T120000
DTSTAMP:20240412T140752Z
CREATED:20240412T011911Z
LAST-MODIFIED:20240412T140752Z
UID:10000680-1713524400-1713528000@micde.umich.edu
SUMMARY:MICDE Fellowships Information Session
DESCRIPTION:Applications for the $4\,500 2024-2025 MICDE Graduate Fellowships will open May 1\, 2024. Please join this Zoom session to learn more about the fellowships and how to submit a great application! \nThese fellowships are sponsored by the Michigan Institute for Computational Discovery & Engineering. For more information\, see https://live-umor-micde.pantheonsite.io/academic-programs/fellowships/.
URL:https://micde.umich.edu/event/livestream-virtualmicde-fellowships-information-session/
LOCATION:Zoom Event
CATEGORIES:Aerospace Engineering,Ai In Science And Engineering,Astronomy,big data,Biomedical Engineering,Biosciences,Biostatistics,Chemical Engineering,Chemistry,Civil and Environmental Engineering,Climate and Space Sciences and Engineering,College Of Engineering,Complex Systems,Computation,Computational Modeling,Computational Science,Computational Social Science,computer science,Data Science,Earth And Environmental Sciences,Ecology,Ecology And Evolutionary Biology,Economics,Education,Electrical And Computer Engineering,Electrical Engineering and Computer Science,Engineering,Engineering Academic Calendar,Epidemiology,Evolutionary Biology,Fellowship,Free,Funding,Generative Ai,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,Health Data,High Performance Computing,Industrial and Operations Engineering,Interdisciplinary,Kinesiology,Life Science,Lsaresearch,Machine Learning,Materials Science,Mathematics,Mechanical Engineering,Medicine,Micde,Natural Language Processing,Natural Sciences,Naval Architecture and Marine Engineering,Neuroscience,Nuclear Engineering and Radiological Sciences,parallel computing,Pharmacy,Physics,Politics,Prospective Graduate Students,Psychology,Public Health,Public Policy,Rackham,Research,Robotics,Scholarship,Science,Scientific Computing,Sciml,Sociology,Statistics,Virtual,Webcast,Workshops
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2024/04/Fellowships-2024-info-session.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20231114T080000
DTEND;TZID=America/Detroit:20231114T190000
DTSTAMP:20231020T163041Z
CREATED:20231020T163041Z
LAST-MODIFIED:20231020T163041Z
UID:10000660-1699948800-1699988400@micde.umich.edu
SUMMARY:Conference / Symposium:U-M Data Science & AI Summit 2023
DESCRIPTION:The U-M Data Science and AI Summit is the largest annual data science and AI event on campus. This event brings together the U-M data science and AI research community and their external collaborators to build research vision and collaboration. It also showcases the breadth and depth of U-M data science and AI research\, from theory and methodology development to the transformative use of data and AI to address scientific and societal challenges in all domains. The event is free for all attendees (U-M faculty\, staff\, and trainees\, as well as industry\, government and community members).\nTo view full Summit schedule\, please visit the event webpage at https://midas.umich.edu/midas-summit-2023/.\nKeynotes:\nSuresh Venkatasubramanian\, Director\, Center for Technological Responsibility\, Reimagination\, and Redesign\, Data Science Institute at Brown University; Professor of Data Science and Computer Science\, Brown University – Key player for the White House Blueprint of an AI Bill of Rights\nJulianne Dalcanton\, Director\, Center for Computational Astrophysics\, Flatiron Institute – The origina and evolution of galaxies\nEmre Kiciman\, Senior Principal Researcher\, Microsoft Research – A New Frontier at the Intersection of Causality and LLMs\nSummit Sessions:\nA panel discussion on: Federal priorities and opportunities in data science and AI\nPanelists:\n– Laura Biven\, Data Science Technical Lead\, Office of Data Science Strategy\, National Institutes of Health\n– Michael Molnar\, Director\, Advanced Manufacturing National Program Office\, National Institute of Standards and Technology\n– Hector Muñoz-Avila\, Program Director and Cluster Lead\, the Information Integration and Informatics Program\, National Science Foundation\n– Alvaro Velasquez\, Program Manager\, Information Innovation Office\, Defense Advanced Research Projects Agency\nResearch vision talks by University of Michigan faculty researchers\nThe Propelling Original Data Science grant awardees showcase\nPoster session\, lightning talks\, and awards\nUniversity of Michigan data science and AI organizations showcase
URL:https://micde.umich.edu/event/conference-symposiumu-m-data-science-ai-summit-2023-2/
LOCATION:Rackham Graduate School (Horace H.)
CATEGORIES:Ai In Science And Engineering,Applications,Artificial Intelligence,big data,Biostatistics,Climate and Space Sciences and Engineering,Computational Modeling,Computational Science,Computational Social Science,computing,Data Curation,Data Science,data visualization,Deep Learning,Electrical And Computer Engineering,Electrical Engineering and Computer Science,Engineering,Faculty,Free,Graduate,Graduate Students,Industrial and Operations Engineering,Information and Technology,Interdisciplinary,Lecture,Machine Learning,Michigan Engineering,Midas,Natural Language Processing,Networking,Science,Social Impact,symposium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20231113T080000
DTEND;TZID=America/Detroit:20231113T190000
DTSTAMP:20231020T163040Z
CREATED:20231020T163040Z
LAST-MODIFIED:20231020T163040Z
UID:10000659-1699862400-1699902000@micde.umich.edu
SUMMARY:Conference / Symposium:U-M Data Science & AI Summit 2023
DESCRIPTION:The U-M Data Science and AI Summit is the largest annual data science and AI event on campus. This event brings together the U-M data science and AI research community and their external collaborators to build research vision and collaboration. It also showcases the breadth and depth of U-M data science and AI research\, from theory and methodology development to the transformative use of data and AI to address scientific and societal challenges in all domains. The event is free for all attendees (U-M faculty\, staff\, and trainees\, as well as industry\, government and community members).\nTo view full Summit schedule\, please visit the event webpage at https://midas.umich.edu/midas-summit-2023/.\nKeynotes:\nSuresh Venkatasubramanian\, Director\, Center for Technological Responsibility\, Reimagination\, and Redesign\, Data Science Institute at Brown University; Professor of Data Science and Computer Science\, Brown University – Key player for the White House Blueprint of an AI Bill of Rights\nJulianne Dalcanton\, Director\, Center for Computational Astrophysics\, Flatiron Institute – The origina and evolution of galaxies\nEmre Kiciman\, Senior Principal Researcher\, Microsoft Research – A New Frontier at the Intersection of Causality and LLMs\nSummit Sessions:\nA panel discussion on: Federal priorities and opportunities in data science and AI\nPanelists:\n– Laura Biven\, Data Science Technical Lead\, Office of Data Science Strategy\, National Institutes of Health\n– Michael Molnar\, Director\, Advanced Manufacturing National Program Office\, National Institute of Standards and Technology\n– Hector Muñoz-Avila\, Program Director and Cluster Lead\, the Information Integration and Informatics Program\, National Science Foundation\n– Alvaro Velasquez\, Program Manager\, Information Innovation Office\, Defense Advanced Research Projects Agency\nResearch vision talks by University of Michigan faculty researchers\nThe Propelling Original Data Science grant awardees showcase\nPoster session\, lightning talks\, and awards\nUniversity of Michigan data science and AI organizations showcase
URL:https://micde.umich.edu/event/conference-symposiumu-m-data-science-ai-summit-2023/
LOCATION:Rackham Graduate School (Horace H.)
CATEGORIES:Ai In Science And Engineering,Applications,Artificial Intelligence,big data,Biostatistics,Climate and Space Sciences and Engineering,Computational Modeling,Computational Science,Computational Social Science,computing,Data Curation,Data Science,data visualization,Deep Learning,Electrical And Computer Engineering,Electrical Engineering and Computer Science,Engineering,Faculty,Free,Graduate,Graduate Students,Industrial and Operations Engineering,Information and Technology,Interdisciplinary,Lecture,Machine Learning,Michigan Engineering,Midas,Natural Language Processing,Networking,Science,Social Impact,symposium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20230929T120000
DTEND;TZID=America/Detroit:20230929T130000
DTSTAMP:20230912T223037Z
CREATED:20230817T202936Z
LAST-MODIFIED:20230912T223037Z
UID:10000610-1695988800-1695992400@micde.umich.edu
SUMMARY:MICDE / MIDAS Graduate Information Session
DESCRIPTION:The educational programs represented are: \n\nPhD in Scientific Computing (MICDE)\nGraduate Certificate in Computational Discovery & Engineering (MICDE)\nGraduate Certificate in Computational Neuroscience (MICDE)\nGraduate Certificate in Data Science (MIDAS)\n\nThese programs are open to all U-M graduate students with an interest in scientific computing or data science. These methodologies can have a wide range of applications – current and past students have come from a variety of home departments including Aerospace Engineering\, Applied Physics\, Biostatistics\, Biomedical Engineering\, Civil & Environmental Engineering\, Chemistry\, Chemical Engineering\, Climate and Space Sciences and Engineering\, Computational Medicine and Bioinformatics\, Ecology and Evolutionary Biology\, Earth and Environmental Sciences\, Epidemiology\, Health Behavior and Health Education\, Health Infrastructures & Learning Systems\, Information\, Industrial & Operations Engineering\, Kinesiology\, Linguistics\, Macromolecular Science & Engineering\, Math\, Molecular\, Cellular\, and Developmental Biology\, Mechanical Engineering\, Materials Science & Engineering\, Naval Architecture & Marine Engineering\, Nuclear Engineering & Radiological Sciences\, Neuroscience\, Pharmaceutical Sciences\, Physics\, Political Science\, Psychology\, Environment and Sustainability\, Sociology and Statistics.\nIf you have any questions about these programs or about the information session\, please reach out to MICDE (micde-contact@umich.edu) or MIDAS (midas-contact@umich.edu).
URL:https://micde.umich.edu/event/presentationgraduate-studies-in-computational-data-sciences-information-session-2-2/
LOCATION:1100 North University Building – 1528
CATEGORIES:Computation,Computational Modeling,Computational Science,Computational Social Science,data,Data Science,Deep Learning,Engineering,Free,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,In Person,Interdisciplinary,Machine Learning,Micde,Michigan Engineering,Midas,Neuroscience,Prospective Graduate Students,Rackham,Research,Science,Scientific Computing
ATTACH;FMTTYPE=image/gif:https://micde.umich.edu/wp-content/uploads/2023/08/Info-session.gif
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20230927T160000
DTEND;TZID=America/Detroit:20230927T170000
DTSTAMP:20230912T222916Z
CREATED:20230817T202936Z
LAST-MODIFIED:20230912T222916Z
UID:10000612-1695830400-1695834000@micde.umich.edu
SUMMARY:MICDE / MIDAS Graduate Information Session
DESCRIPTION:The educational programs represented are: \n\nPhD in Scientific Computing (MICDE)\nGraduate Certificate in Computational Discovery & Engineering (MICDE)\nGraduate Certificate in Computational Neuroscience (MICDE)\nGraduate Certificate in Data Science (MIDAS)\n\nThese programs are open to all U-M graduate students with an interest in scientific computing or data science. These methodologies can have a wide range of applications – current and past students have come from a variety of home departments including Aerospace Engineering\, Applied Physics\, Biostatistics\, Biomedical Engineering\, Civil & Environmental Engineering\, Chemistry\, Chemical Engineering\, Climate and Space Sciences and Engineering\, Computational Medicine and Bioinformatics\, Ecology and Evolutionary Biology\, Earth and Environmental Sciences\, Epidemiology\, Health Behavior and Health Education\, Health Infrastructures & Learning Systems\, Information\, Industrial & Operations Engineering\, Kinesiology\, Linguistics\, Macromolecular Science & Engineering\, Math\, Molecular\, Cellular\, and Developmental Biology\, Mechanical Engineering\, Materials Science & Engineering\, Naval Architecture & Marine Engineering\, Nuclear Engineering & Radiological Sciences\, Neuroscience\, Pharmaceutical Sciences\, Physics\, Political Science\, Psychology\, Environment and Sustainability\, Sociology and Statistics.\nIf you have any questions about these programs or about the information session\, please reach out to MICDE (micde-contact@umich.edu) or MIDAS (midas-contact@umich.edu).
URL:https://micde.umich.edu/event/presentationgraduate-studies-in-computational-data-sciences-information-session/
LOCATION:Lurie Robert H. Engin. Ctr – Johnson Rooms\, 3rd floor
CATEGORIES:Computation,Computational Modeling,Computational Science,Computational Social Science,data,Data Science,Deep Learning,Engineering,Free,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,In Person,Interdisciplinary,Machine Learning,Micde,Michigan Engineering,Midas,Neuroscience,Prospective Graduate Students,Rackham,Research,Science,Scientific Computing
ATTACH;FMTTYPE=image/gif:https://micde.umich.edu/wp-content/uploads/2023/08/Info-session.gif
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20220317T140000
DTEND;TZID=America/Detroit:20220317T160000
DTSTAMP:20220112T185149Z
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:20211020T100000
DTEND;TZID=America/Detroit:20211020T113000
DTSTAMP:20230217T195752Z
CREATED:20211001T162623Z
LAST-MODIFIED:20230217T195752Z
UID:10000533-1634724000-1634729400@micde.umich.edu
SUMMARY:Getting Started with the Python Multiprocessing Package
DESCRIPTION:OVERVIEW\nThis workshop will provide a gentle introduction to using the multiprocessing package in Python for parallelizing and speeding up code. We will use hands-on programming exercises to demonstrate how to quickly get started with commonly used components of the multiprocessing package. Note that a Great Lakes account is optional for this workshop\, but you must have an account before the start of the workshop if you wish to use Great Lakes. See below for account request information. If you do not wish to use Great Lakes\, you must have python installed on your computer before the start of the workshop. \nINSTRUCTOR\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. \nMATERIALS\nPrerequisites: Familiarity with connecting to the Great Lakes cluster via SSH/PuTTY and UMVPN\, Basic Linux command line familiarity\, basic programming experience in Python\, and an understanding of loops and basic data structures such as lists are all necessary for this hands-on workshop. \nFor more information on The Great Lakes cluster\, click here. \nClick here to fill out an account request form\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. \n  \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. \nIf you have questions about this workshop\, please send an email to the instructor at arburks@umich.edu \n\n\n\nArmand R. Burks\, Ph. D. \nResearch Data Scientist\nAdvanced Research Computing\nSchool of Information\nUniversity of Michigan
URL:https://micde.umich.edu/event/https-ttc-iss-lsa-umich-edu-ttc-sessions-getting-started-with-the-python-multiprocessing-package/
LOCATION:Your Desktop
CATEGORIES:Data Science,Data Science Skills Series,Great Lakes,High Performance Computing,hpc-events,Info Session,Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20211014T140000
DTEND;TZID=America/Detroit:20211014T160000
DTSTAMP:20230217T195820Z
CREATED:20211001T161248Z
LAST-MODIFIED:20230217T195820Z
UID:10000536-1634220000-1634227200@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. \nINSTRUCTORS\nMeghan Richey\nMachine Learning Specialist\nInformation and Technology Services – Advanced Research Computing \nMeghan Richey 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/
LOCATION:Your Desktop
CATEGORIES:Data Science,Great Lakes,High Performance Computing,Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210507T100000
DTEND;TZID=America/Detroit:20210507T120000
DTSTAMP:20230905T171444Z
CREATED:20230905T171444Z
LAST-MODIFIED:20230905T171444Z
UID:10000467-1620381600-1620388800@micde.umich.edu
SUMMARY:Advanced ML topics: Algorithms\, writing ML code\, comparing implementations
DESCRIPTION:OVERVIEW\n\n\nThis workshop is designed as a follow-up to the basic introduction to machine learning earlier in this series. We will cover several examples in Python and compare different implementations. We will also look at advanced topics in machine learning\, such as GPU optimization\, parallel processing\, and deep learning. A basic understanding of Python is required. \nINSTRUCTORS\nMeghan Richey\nMachine Learning Specialist\nInformation and Technology Services – Advanced Research Computing – Technology Services \nMeghan Richey is a machine learning specialist in the Advanced Research Computing- Technology Services 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. \n\n\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 9-10 AM for computer setup assistance. \nPlease note\, this session will be recorded.   \n\nRegister here \nIf you have questions about this workshop\, please send an email to the instructor at richeym@umich.edu
URL:https://micde.umich.edu/event/advanced-ml-topics-algorithms-writing-ml-code-comparing-implementations-2/
LOCATION:Your Desktop
CATEGORIES:Data Science,High Performance Computing,Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20201201T100000
DTEND;TZID=America/Detroit:20201201T120000
DTSTAMP:20230905T171255Z
CREATED:20230905T171255Z
LAST-MODIFIED:20230905T171255Z
UID:10000424-1606816800-1606824000@micde.umich.edu
SUMMARY:Introduction to Machine Learning
DESCRIPTION:OVERVIEW\n\n\nMachine learning is becoming an increasingly popular tool in several fields\, including data science\, medicine\, engineering\, and business. This workshop will cover basic concepts related to machine learning\, including definitions of basic terms\, sample applications\, and methods for deciding whether your project is a good fit for machine learning. No prior knowledge or coding experience is required \nINSTRUCTORS\nMeghan Richey\nMachine Learning Specialist\nInformation and Technology Services – Advanced Research Computing – Technology Services \nMeghan Richey is a machine learning specialist in the Advanced Research Computing- Technology Services 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. \nMATERIALS\n\n\n\nIntroduction to Machine Learning Topics\n\n\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 9-10 AM for computer setup assistance. \nPlease note\, this session will be recorded.   \n\nRegister here \nIf you have questions about this workshop\, please send an email to the instructor at richeym@umich.edu
URL:https://micde.umich.edu/event/introductions-to-machine-learning-2/
LOCATION:Your Desktop
CATEGORIES:Data Science,Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190425T130000
DTEND;TZID=America/Detroit:20190425T160000
DTSTAMP:20230905T171400Z
CREATED:20230905T171400Z
LAST-MODIFIED:20230905T171400Z
UID:10000223-1556197200-1556208000@micde.umich.edu
SUMMARY:Sliding into Slurm:  An early look at U-M's new high-performance computing environment
DESCRIPTION:This workshop will provide a brief overview of the the new HPC environment and is intended for current Flux and Armis users.  We will use the temporary Beta HPC cluster to demonstrate how jobs will be submitted and managed under the new Great Lakes\, Armis2\, and Lighthouse clusters available later this year. \nThere are many differences between the familiar Flux environment and that of the new HPC clusters\, including a new batch scheduling system\, a new interactive batch job environment\, a new HPC web portal\, a new module environment\, and a new on-demand-only job accounting system. \nWe will cover these differences in the workshop\, and provide hands-on training in creating and running job submission scripts in the new HPC environment.  Students are expected to be conversant with the Linux command line and have experience in creating\, submitting\, and troubleshooting PBS batch scripts.
URL:https://micde.umich.edu/event/sliding-into-slurm-an-early-look-at-u-ms-new-high-performance-computing-environment-4/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Data Science,High Performance Computing,Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190417T130000
DTEND;TZID=America/Detroit:20190417T160000
DTSTAMP:20230905T171400Z
CREATED:20230905T171400Z
LAST-MODIFIED:20230905T171400Z
UID:10000222-1555506000-1555516800@micde.umich.edu
SUMMARY:Sliding into Slurm:  An early look at U-M's new high-performance computing environment
DESCRIPTION:This workshop will provide a brief overview of the the new HPC environment and is intended for current Flux and Armis users.  We will use the temporary Beta HPC cluster to demonstrate how jobs will be submitted and managed under the new Great Lakes\, Armis2\, and Lighthouse clusters available later this year. \nThere are many differences between the familiar Flux environment and that of the new HPC clusters\, including a new batch scheduling system\, a new interactive batch job environment\, a new HPC web portal\, a new module environment\, and a new on-demand-only job accounting system. \nWe will cover these differences in the workshop\, and provide hands-on training in creating and running job submission scripts in the new HPC environment.  Students are expected to be conversant with the Linux command line and have experience in creating\, submitting\, and troubleshooting PBS batch scripts.
URL:https://micde.umich.edu/event/sliding-into-slurm-an-early-look-at-u-ms-new-high-performance-computing-environment-3/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Data Science,High Performance Computing,Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190221T110000
DTEND;TZID=America/Detroit:20190221T120000
DTSTAMP:20230905T171357Z
CREATED:20230905T171357Z
LAST-MODIFIED:20230905T171357Z
UID:10000211-1550746800-1550750400@micde.umich.edu
SUMMARY:Introduction to the campus Hadoop cluster
DESCRIPTION:This course will cover 4 areas: \n\nLogging into the cluster\nHow to upload your data\nHow to run a job\nHow to get your data from the cluster\n\nPrerequisites: Workshop participants should take the “Introduction to the Linux Command Line” workshop\, and view the following videos: \nhttps://youtu.be/4Gfl0WuONMY \nhttps://www.youtube.com/watch?v=bcjSe0xCHbE \nClick here for more information on The Cavium ThunderX Cluster \nClick here to fill out an account request form \nNote: 3 business days are needed for creation of accounts \nStudents should fill in “Workshop” in the “Advisor” section. \nIt is recommended that students get an account at Kaggle ( https://www.kaggle.com/ ) as this is where we will source our data sets. \nCampus VPN access is required for off-campus access but not from on campus. An SSH client\, and Duo will be required during the workshop. \n  \nIf you have questions about this workshop\, please send an email to smeyer@umich.edu
URL:https://micde.umich.edu/event/introduction-to-the-campus-hadoop-cluster-4/
LOCATION:East Hall B254\, 530 Church St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Data Science,Hadoop,High Performance Computing,Workshops
GEO:42.2757302;-83.7351764
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=East Hall B254 530 Church St. Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=530 Church St.:geo:-83.7351764,42.2757302
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190220T160000
DTEND;TZID=America/Detroit:20190220T170000
DTSTAMP:20230905T171357Z
CREATED:20230905T171357Z
LAST-MODIFIED:20230905T171357Z
UID:10000208-1550678400-1550682000@micde.umich.edu
SUMMARY:Introduction to the campus Hadoop cluster
DESCRIPTION:This course will cover 4 areas: \n\nLogging into the cluster\nHow to upload your data\nHow to run a job\nHow to get your data from the cluster\n\nPrerequisites: Workshop participants should take the “Introduction to the Linux Command Line” workshop\, and view the following videos: \nhttps://youtu.be/4Gfl0WuONMY \nhttps://www.youtube.com/watch?v=bcjSe0xCHbE \nClick here for more information on The Cavium ThunderX Cluster \nClick here to fill out an account request form \nNote: 3 business days are needed for creation of accounts \nStudents should fill in “Workshop” in the “Advisor” section. \nIt is recommended that students get an account at Kaggle ( https://www.kaggle.com/ ) as this is where we will source our data sets. \nCampus VPN access is required for off-campus access but not from on campus. An SSH client\, and Duo will be required during the workshop. \n  \nIf you have questions about this workshop\, please send an email to smeyer@umich.edu
URL:https://micde.umich.edu/event/introduction-to-the-campus-hadoop-cluster-3/
LOCATION:East Hall B254\, 530 Church St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Data Science,Hadoop,High Performance Computing,Workshops
GEO:42.2757302;-83.7351764
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=East Hall B254 530 Church St. Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=530 Church St.:geo:-83.7351764,42.2757302
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20180123T100000
DTEND;TZID=America/Detroit:20180123T150000
DTSTAMP:20230905T171417Z
CREATED:20230905T171417Z
LAST-MODIFIED:20230905T171417Z
UID:10000123-1516701600-1516719600@micde.umich.edu
SUMMARY:Android Application Development: Why and How
DESCRIPTION:Mobile app development is one of the biggest new industries of the last decade. As of 2017\, Google has stated that over 2 billion devices around the world use the Android operating system\, alongside Apple’s 1 billion iOS mobile devices around the globe. The capabilities and adopted use of modern smartphones can provide an easy gateway to collect data or engage with participants for research purposes. It might seem a daunting task for newcomers to write a program for the computer in their pocket\, but modern tools and software make it more accessible than ever. We will present a brief overview of the differences between Android and iOS development requirements\, and provide demonstrations on how to program an app for your Android phone using a Windows PC environment and a sample of free software packages. \nA familiarity with programming languages and logic is assumed. Program code presented during the workshop may be written in languages including (but not limited to) Java and C#\, familiarity with syntax of these languages is recommended. It is not expected for attendees to program during the workshop\, but those who wish to do so are recommended to install the “Android Studio” IDE in advance.
URL:https://micde.umich.edu/event/android-application-development-why-and-how/
LOCATION:Rackham Building\, Earl Lewis Room\, 3rd Floor East\, 915 E. Washington St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Data Science,Workshops
GEO:42.2807892;-83.7381556
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Rackham Building Earl Lewis Room 3rd Floor East 915 E. Washington St. Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=915 E. Washington St.:geo:-83.7381556,42.2807892
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20180119T140000
DTEND;TZID=America/Detroit:20180119T163000
DTSTAMP:20230905T171417Z
CREATED:20230905T171417Z
LAST-MODIFIED:20230905T171417Z
UID:10000124-1516370400-1516379400@micde.umich.edu
SUMMARY:Regular Expressions II
DESCRIPTION:Regular expressions are perfectly suited for people who like puzzles. Regular expressions are a sequence of characters used to define a search pattern. They are commonly used to do “find” and “find and replace” string operations. They are also used to validate strings like phone numbers\, passwords\, etc. in data entry. Regular expression capabilities can be found in a variety of programming languages and software like ArcGIS\, Java\, Javascript\, Matlab\, Perl\, PHP\, Python\, R\, Visual Basic\, etc. and some text editors. This workshop is part II of a two-part series and will cover more advanced topics like captured groups\, backreferences and assertions. The workshop will consist of hands-on example problems. Basic understanding of regular expressions is required. You should be able to understand expressions like “w{3\,}-d{1\,2}-d{4}“ and “des*ert?s?”. The tutorials will be conducted using Python. A basic programming background is helpful but not required for this workshop.
URL:https://micde.umich.edu/event/regular-expressions-ii/
LOCATION:Modern Languages Building (MLB)\, Room 2001B
CATEGORIES:Data Science,Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20171201T083000
DTEND;TZID=America/Detroit:20171201T173000
DTSTAMP:20230905T171416Z
CREATED:20230905T171416Z
LAST-MODIFIED:20230905T171416Z
UID:10000105-1512117000-1512149400@micde.umich.edu
SUMMARY:2017 U-M Data Science Research Forum
DESCRIPTION:Forum Highlights \n\nOral and poster presentations on\n\nTheoretical foundations of data science\nData science methodology\nData science applications in any research domain\nSocial impact of data science research\n\n\n\n\nHow to engage industry workshop\n\nAdrian Fortino\, Partner (Mercury Fund)\nMike Psarouthakis\, Director (U-M Venture Center)\nKevyn Collins-Thompson\, Associate Professor\, U-M School of Information\nMike Cafarella\, Associate Professor\, U-M Computer Science Engineering\n\n\n\n\nKeynote by Chris Rozell\n\n\nNetworking Reception\n\nAll presentations will come from submissions in response to our call for abstracts\n Abstract Submission Deadline: October 23\, 2017\n We welcome submission from all U-M data science researchers (faculty\, staff\, trainees) \nPlease register for this event.  Please also see the call for abstracts for instruction\, and submit through the Abstract Submission Form. \nPreliminary Schedule
URL:https://micde.umich.edu/event/data-science-research-forum/
LOCATION:Michigan League\, 911 N. University\, Ann Arbor\, MI\, 48104\, United States
CATEGORIES:Conference,Data Science,Seminar
GEO:42.2796269;-83.7374973
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Michigan League 911 N. University Ann Arbor MI 48104 United States;X-APPLE-RADIUS=500;X-TITLE=911 N. University:geo:-83.7374973,42.2796269
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20170424T110000
DTEND;TZID=America/Detroit:20170424T130000
DTSTAMP:20230905T171438Z
CREATED:20230905T171438Z
LAST-MODIFIED:20230905T171438Z
UID:10000081-1493031600-1493038800@micde.umich.edu
SUMMARY:MIDAS Working Group on NSF solicitation for Big Data Spokes
DESCRIPTION:This working group is organized by MIDAS to respond to the NSF Big Data Spokes funding solicitation (BD Spokes).   \nAgenda: \n\nA brief presentation about the funding opportunity and the background of the regional BD Hubs (Midwest\, Northeast\, South and West) and existing Spokes\nDiscussion of ideas of new Spokes and forming collaborative teams (within and outside of UM)\nDiscussion on aligning and working with regional BD hubs\n\nThe BD Spokes will work with regional BD hubs and existing spokes to accelerate progress towards societal grand challenges in regional and national priority areas\, help automate the Big Data lifecycle\, enable access to and increase the use of important data sets\, and contribute to education and training.  The focus areas specified by NSF include: Education; Data Intensive Research in the Social\, Behavioral\, and Economic Sciences; Data-driven Research in Chemistry; Neuroscience; Data Analytics for Security; Replicability and Reproducibility in Data Science.  All researchers interested in proposing or collaborating on new BD Spokes are welcome to our working group. \nImportant Dates: \n\nMay 17\, 2017: University of Michigan internal deadline for declaring intent.  NSF allows only one proposal from each university as the lead institution\n\n\nSept. 18\, 2017: full proposal due to NSF\n\nPlease RSVP.  For questions\, please contact Jing Liu\, MIDAS research specialist (ljing@umich.edu; 734-764-2750).  
URL:https://micde.umich.edu/event/midas-working-group-on-nsf-solicitation-for-big-data-spokes/
LOCATION:MIDAS – SPH I\, Suite 7625\, 1415 Washington Heights\, Ann Arbor\, MI\, 48109-2029\, United States
CATEGORIES:Data Science,Workshops
GEO:42.2804938;-83.7300222
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=MIDAS – SPH I Suite 7625 1415 Washington Heights Ann Arbor MI 48109-2029 United States;X-APPLE-RADIUS=500;X-TITLE=1415 Washington Heights:geo:-83.7300222,42.2804938
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20161101T160000
DTEND;TZID=America/Detroit:20161101T170000
DTSTAMP:20230905T171440Z
CREATED:20230905T171440Z
LAST-MODIFIED:20230905T171440Z
UID:10000049-1478016000-1478019600@micde.umich.edu
SUMMARY:Info Session: Data Services at U-M
DESCRIPTION:Representatives of Consulting for Statistics\, Computing and Analytics Research (CSCAR) and the U-M Library (UML) will give an overview of services that are now available to support data-intensive research on campus.  As part of the U-M Data Science Initiative\, CSCAR and UML are expanding their scopes and adding capacity to support a wide range of research involving data and computation.  This includes consulting\, workshops\, and training designed to meet basic and advanced needs in data management and analysis\, as well as specialized support for areas such as remote sensing and geospatial analyses\, and a funding program for dataset acquisitions.  Many of these services are available free of charge to U-M researchers. \nThis event will begin with overview presentations about CSCAR and Library system data services.  There will also be opportunities for researchers to discuss individualized partnerships with CSCAR and UML to advance specific data-intensive projects.  Faculty\, staff\, and students are welcome to attend.
URL:https://micde.umich.edu/event/info-session-data-services-at-u-m-2/
LOCATION:Rackham Building\, Earl Lewis Room\, 3rd Floor East\, 915 E. Washington St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Data Science,Info Session
GEO:42.2807892;-83.7381556
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Rackham Building Earl Lewis Room 3rd Floor East 915 E. Washington St. Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=915 E. Washington St.:geo:-83.7381556,42.2807892
END:VEVENT
END:VCALENDAR