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DTSTART;TZID=America/Detroit:20190304T083000
DTEND;TZID=America/Detroit:20190304T150000
DTSTAMP:20260606T094739
CREATED:20230905T171359Z
LAST-MODIFIED:20230905T171359Z
UID:10000038-1551688200-1551711600@micde.umich.edu
SUMMARY:Statistical Analysis with R
DESCRIPTION:This is a two day workshop (March 4 and 5) in R which  is a free and open source environment for data analysis and statistical computing.  While R contains many built-in statistical procedures\, a powerful feature of R is the facility for users to extend these procedures to suit their own needs.  Excellent graphing capability is another reason R is gaining wide popularity. \n\nHow to Obtain R\nHelp Tools\nImporting / Exporting Data\nData Management\nDescriptive and Exploratory Statistics\nCommon Statistical Analyses (t-test\, Regression Modeling\, ANOVA\, etc.)\nGraphics\nCreating Functions\n\n 
URL:https://micde.umich.edu/event/statistical-analysis-with-r-2/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190227T140000
DTEND;TZID=America/Detroit:20190227T173000
DTSTAMP:20260606T094739
CREATED:20230905T171359Z
LAST-MODIFIED:20230905T171359Z
UID:10000186-1551276000-1551288600@micde.umich.edu
SUMMARY:Geospatial Analysis with Google Earth Engine
DESCRIPTION:Google Earth Engine combines a multi-petabyte catalog of satellite imagery and geospatial datasets with planetary-scale analysis capabilities. This hands-on workshop will help you understand the power (and limitation) of GEE for carrying out an end-to-end analysis. \nYou should have some exposure to GEE and remote sensing. We will focus on contemporary environmental issues and learn how to carry out more advanced analysis and visualization in GEE. We will use the web-based IDE for the Earth Engine JavaScript API.
URL:https://micde.umich.edu/event/geospatial-analysis-with-google-earth-engine-2/
LOCATION:Rackham Building\, Earl Lewis Room\, 3rd Floor East\, 915 E. Washington St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Workshops
GEO:42.2807892;-83.7381556
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:20190226T100000
DTEND;TZID=America/Detroit:20190226T120000
DTSTAMP:20260606T094739
CREATED:20230905T171357Z
LAST-MODIFIED:20230905T171357Z
UID:10000202-1551175200-1551182400@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. \nAll examples will use Python; some familiarity with Pyt hon is recommended. Computers will be available to complete exercises.
URL:https://micde.umich.edu/event/introduction-to-deep-neural-networks-with-keras-tensorflow-3/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190221T110000
DTEND;TZID=America/Detroit:20190221T120000
DTSTAMP:20260606T094739
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:20260606T094739
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:20190220T153000
DTEND;TZID=America/Detroit:20190220T173000
DTSTAMP:20260606T094739
CREATED:20230905T171358Z
LAST-MODIFIED:20230905T171358Z
UID:10000185-1550676600-1550683800@micde.umich.edu
SUMMARY:Generalized Additive Models
DESCRIPTION:Nonlinear relationships abound in nature\, though typical statistical models ignore this in favor of simplicity\, often at a cost of both predictive capabilities and better understanding of the underlying phenomenon of interest.  One means to explore such relationships is through generalized additive models (GAM). \nThis workshop will introduce participants to GAMs as a means to extend their efforts beyond the usual GLM setting.  In addition\, extensions and connections to other models will be noted (e.g. mixed and spatial).  Demonstration will be conducted with R\, and the mgcv package in particular. \nLink: https://m-clark.github.io/generalized-additive-models/
URL:https://micde.umich.edu/event/generalized-additive-models-2/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190219T140000
DTEND;TZID=America/Detroit:20190219T160000
DTSTAMP:20260606T094739
CREATED:20230905T171358Z
LAST-MODIFIED:20230905T171358Z
UID:10000198-1550584800-1550592000@micde.umich.edu
SUMMARY:Survival analysis in Python
DESCRIPTION:Survival analysis is used when working with data that may be censored\, as often is the case in studies of human subjects with incomplete follow-up.  The presence of censoring makes most forms of regression and other standard statistical analyses inappropriate. A body of specialized techniques for analyzing this type of data has been developed\, including methods for estimating and comparing marginal survival functions\, and regression methods including the widely-utilized Cox proportional hazards model.  This workshop will briefly review the key principles of survival analysis\, then illustrate by example how various survival analysis methods can be carried out using Python with the Statsmodels package.  \nParticipants should bring a laptop if they want to work with the examples during the presentation\, but this is optional.
URL:https://micde.umich.edu/event/survival-analysis-in-python-2/
LOCATION:Rackham Building\, Earl Lewis Room\, 3rd Floor East\, 915 E. Washington St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Workshops
GEO:42.2807892;-83.7381556
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:20190219T100000
DTEND;TZID=America/Detroit:20190219T163000
DTSTAMP:20260606T094739
CREATED:20230905T171358Z
LAST-MODIFIED:20230905T171358Z
UID:10000175-1550570400-1550593800@micde.umich.edu
SUMMARY:The 2nd Annual Data for Public Good Symposium
DESCRIPTION:Do you have experience in working alongside community partners in data analysis or program evaluation? Do you want to connect with others who are using their skills for public good? National efforts from organizations such as DataKind\, Data Science for Social Good\, and Statistics without Borders have been expanding in recent years as more individuals recognize their potential to impact social change.  Great things can happen when individuals are empowered to dedicate time\, resources\, and knowledge to the pursuit of public good. Whether we work in the foreground or the background\, we can all contribute to improving the lives of those around us. \nStatistics in the Community (STATCOM)\, in collaboration with the Center for Education Design\, Evaluation\, and Research (CEDER) and the Community Technical Assistance Collaborative (CTAC)\, invite you to attend the 2nd Annual Data for Public Good Symposium hosted by the Michigan Institute for Data Science (MIDAS). The symposium will take place on Tuesday\, February 19\, 2019 and will showcase the many research efforts and community-based partnerships at U-M that focus on improving humanity by using data for public good. If you are interested in attending\, please register here. \nSchedule:\n10:00 – 10:30: Registration and Networking\n10:30 – 11:30: Presentations \n\nPartners for Preschool: The Added Value of Learning Activities at Home During the Preschool Year\, Amanda Ketner\, School of Education\nUniversity-Community Partnership to Support Ambitious STEM Teaching: Leveraging University of Michigan expertise in education\, research\, and evaluation to support innovative\, interactive teaching across the S.E. Michigan region and beyond\, C. S. Hearn\, Center for Education Design\, Evaluation\, and Research (CEDER)\nOpen Data Flint\, Stage II\, Kaneesha Wallace\, MICHR\nResearch-Practice Partnerships at the Youth Policy Lab\, A Foster\, ISR Youth Policy Lab and School of Education\nThe LOOP Estimator: Adjusting for Covariates in Randomized Experiments\, Edward Wu\, Statistics\n\n11:30 – 01:00: Lunch/Poster Session\n01:00 – 02:00: Presentations \n\nBarrier Busters: Unconditional Cash Transfers as a Strategy to Promote Economic Self-Sufficiency\, Elise Gahan\, School of Public Health\nImplementing Trauma-Informed Care at University Libraries\, Monte-Angel Richardson\, School of Social Work\nWhy did the global crude oil price start to rise again after 2016?\, Shin Heuk Kang\, Economics\nPoverty and economic hardship in Michigan communities: Data from the Michigan Public Policy Survey (MPPS)\, Natalie Fitzpatrick\, Center for Local\, State\, and Urban Policy\nUnderstanding Networks of Influence on U.S. Congressional Members’ Public Personae on Twitter\, Angela Schopke\, Chris Bredernitz\, Caroline Hodge\, School of Information\n\n02:00 – 02:30: UM Student Organization Presentations\n02:30 – 04:30: Workshop Debrief & Closing \n\nAbout the Organizers: STATCOM is a community outreach organization offering the expertise of statistics graduate students – free of charge – to nonprofit governmental and community organizations. CTAC is a community-university partnership convened to serve a universal need identified by community partners around data and evaluation. CEDER is a School of Education center devoted exclusively to offering high-quality designs\, evaluations\, and research on teaching\, learning\, leadership\, and policy at multiple levels of education. This symposium is part of our effort to bring together university organizations that promote similar ideals and individuals whose research provides a service for the greater good. \nQuestions: Please contact salernos@umich.edu. \n  \n    \n  \n  \n  \n 
URL:https://micde.umich.edu/event/2nd-annual-data-for-public-good-symposium/
LOCATION:Forum Hall\, Palmer Commons
CATEGORIES:Conference,Statistics,Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190218T150000
DTEND;TZID=America/Detroit:20190218T160000
DTSTAMP:20260606T094739
CREATED:20230905T171358Z
LAST-MODIFIED:20230905T171358Z
UID:10000207-1550502000-1550505600@micde.umich.edu
SUMMARY:MICDE Seminar: Jim Haxby\, Evans Family Distinguished Professor; Director\, Center for Cognitive Neuroscience\, Dartmouth College
DESCRIPTION:Bio1: James V. Haxby is a professor in the Department of Psychological and Brain Sciences at Dartmouth College and the Director for the Dartmouth Center for Cognitive Neuroscience. He is best known for his work on face perception and applications of machine learning in functional neuroimaging. Haxby received a BA from Carleton College in 1973 and completed a Fulbright Scholarship at the University of Bonn in 1974. He obtained a PhD in clinical psychology at the University of Minnesota in 1981. After receiving his PhD\, Haxby held several clinical psychology positions at the Minneapolis VA Medical Center. Starting in 1982\, Haxby began a two-decade tenure at the National Institutes of Health\, working as a research psychologist at the National Institute on Aging and later as chief of the Section on Functional Brain Imaging at the National Institute of Mental Health. In 2002\, Haxby began a professorship in the Department of Psychology at Princeton University\, and in 2008 became the Evans Family Distinguished Professor of Psychological and Brain Sciences at Dartmouth College. \nHaxby’s scientific contributions span several topics in cognitive neuroscience. He has published numerous papers using functional neuroimaging to investigate the cortical organization underlying visual perception and semantic memory.He has also proposed an influential model of face perception where certain brain areas process invariant face properties such identity\, while others process dynamic features critical for social interaction\, such as emotional expressions and eye gaze. Haxby has played a critical role in introducing machine learning methods to functional magnetic resonance imaging (fMRI) data analysis. This approach was popularized by a paper demonstrating that neural representations of faces and object categories are encoded in a distributed fashion in human ventral temporal cortex\, a position that is typically contrasted with more modular accounts of the functional neuroanatomy of face processing. \n[1] https://en.wikipedia.org/wiki/James_V._Haxby \nBRIDGING THE DIVIDE: FOSTERING INTERDISCIPLINARY COLLABORATIVE RESEARCH IN COMPUTATIONAL COGNITIVE NEUROSCIENCE\nComputational cognitive neuroscience is a burgeoning field. Sensitive imaging methods can now measure changing patterns of brain activity noninvasively producing massive\, rich datasets. With open neuroscience\, vast amounts of functional brain imaging data are publicly available. Advances in computational methods for analyzing these data and modeling the underlying cognitive processes have produced a host of sophisticated algorithms that produce surprising new insights\, and these algorithms are available in extensive repositories of open source code. Building the interdisciplinary community for this type of collaborative research\, however\, presents challenges. Taking advantage of these resources requires integration of knowledge of cognitive neuroscience to direct projects to important questions and knowledge of rapidly evolving computational approaches that can tackle these questions in innovative ways. Building an interdisciplinary community will involve developing both productive interdisciplinary collaborative teams and a new breed of “bilingual” computational cognitive neuroscientist. \nProf. Haxby is being hosted my MICDE and the Michigan Neuroimaging Initiative. If you would like to meet Prof. Haxby\, please send an email to micde-events@umich.edu. If you are an MICDE\, MIDAS or Neuroscience student or postdoc and would like to join him for lunch\, please RSVP here (space is limited\, first-come\, first-serve)
URL:https://micde.umich.edu/event/micde-seminar-jim-haxby-evans-family-distinguished-professor-director-center-for-cognitive-neuroscience-dartmouth-college/
LOCATION:1017 H. H. Dow\, 2300 Hayward St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2019/02/James-V.-Haxby.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190215T130000
DTEND;TZID=America/Detroit:20190215T140000
DTSTAMP:20260606T094739
CREATED:20230905T171358Z
LAST-MODIFIED:20230905T171358Z
UID:10000205-1550235600-1550239200@micde.umich.edu
SUMMARY:MICDE Seminar: Rhonda Dzakpasu\, Associate Professor\, Department of Physics\, Georgetown University
DESCRIPTION:Bio: Rhonda Dzakpasu received a B.S. in Computer Science from The City College of New York. After working as a research assistant in a semiconductor laboratory\, she entered the PhD program at the University of Michigan where she completed a PhD in experimental optical physics. Her thesis work resulted in the development of an optical technique that images dynamically scattered light fluctuation decay rates.  She remained at the University of Michigan for her postdoctoral training where she performed computational modeling to study how architecture influences the dynamics within networks of coupled non-linear oscillators. As part of her postdoctoral training\, she also participated in two intensive neuroscience summer courses at the Marine Biological Laboratory (MBL) in Woods Hole\, MA: SPINES and Neurobiology. Prof. Dzakpasu joined the faculty in the Department of Physics as well as the Department of Pharmacology and Physiology at Georgetown University in 2008. Her current research incorporates experimental in vitro as well as computational techniques to probe the dynamical patterns that arise from the interactions within networks of neurons. \nWhat can we learn from neurochemical and cellular perturbations of in vitro neuronal network dynamics?\nProbing neural systems is essential to understanding the circuitry that underlies complex neuronal dynamics. Tools such as pharmacological assays are widely employed to assess differences between healthy and pathological states of a network and to elucidate biochemical mechanisms of a variety of cognitive processes. Manipulating the cellular composition of neural systems can also provide insights into the basic interactions between the constituent partners within the neural circuit.\nI will discuss results from two studies. In the first study\, we use neuromodulation to perturb the excitatory/inhibitory balance within a network of hippocampal neurons using pharmacological agents. Neuromodulation impacts oscillatory activity within cortical and hippocampal circuits and these oscillations have been shown to be important for cognitive processes such as working memory and attention. The oscillatory states are indicative of information transmission within the neural circuit and to examine changes in information transmission\, we perform extracellular recordings of action potentials from cultured hippocampal neuronal networks using an array of microelectrodes. We show a time-dependent effect on bursting dynamics after application of one of these agents and will discuss two possible mechanisms that may be involved.\nIn the second study\, I will present results from a new tissue co-culture system designed to investigate the network effects due to APOE\, the strongest genetic risk factor for Alzheimer’s disease. While the pathogenesis of Alzheimer’s is not well understood\, neural seizure-like activity has been shown to influence disease progression. Recent research suggests a link between Alzheimer’s disease and seizure-like brain activity. However\, little is known about how APOE affects activity across networks of neurons. I will discuss how APOE genotype impacts spiking dynamics of developing in vitro neuronal networks and its impact on the basic biophysical properties of the extracellular network voltage. \nProf. Dzakpasu is being hosted by Prof. Zochowski (Physics & Biophysics). If you would like to meet with her during her visit\, please send an email to micde-events@umich.edu. If you are an MICDE students\, or a Physics graduate student and would like to join Prof. Dzakpasu for lunch\, please sign up here.
URL:https://micde.umich.edu/event/micde-seminar-rhonda-dzakpasu-associate-professor-department-of-physics-georgetown-university/
LOCATION:411 West Hall (1085 S. University)\, 1085 S. University Ave\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2019/01/Rhonda-Dzakpasu.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190212T140000
DTEND;TZID=America/Detroit:20190212T160000
DTSTAMP:20260606T094739
CREATED:20230905T171358Z
LAST-MODIFIED:20230905T171358Z
UID:10000184-1549980000-1549987200@micde.umich.edu
SUMMARY:Multilevel models in Python
DESCRIPTION:Multilevel modeling is the state-of-the-art approach for handling data with complex dependence structure in a regression analysis.  This workshop will discuss fitting multilevel models in Python using the Statsmodels package. We will discuss the motivation and main use cases for multilevel modeling\, and illustrate by example how to fit linear and generalized linear mixed models.   \nParticipants should bring a laptop if they want to work with the examples during the presentation\, but this is optional.
URL:https://micde.umich.edu/event/multilevel-models-in-python/
LOCATION:Rackham Building\, Earl Lewis Room\, 3rd Floor East\, 915 E. Washington St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Workshops
GEO:42.2807892;-83.7381556
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:20190212T093000
DTEND;TZID=America/Detroit:20190212T120000
DTSTAMP:20260606T094739
CREATED:20230905T171345Z
LAST-MODIFIED:20230905T171345Z
UID:10000204-1549963800-1549972800@micde.umich.edu
SUMMARY:Python for Data Analysis
DESCRIPTION:Learn data analysis with Python. We’ll be using pandas\, the go-to Python library used for data wrangling and analysis. We’ll be practicing with several different real-world datasets (e.g. time-series\, text) and learning how to read\, write\, clean\, transform\, merge and reshape data.  \nThe workshop is intended for users with basic Python knowledge. Anaconda Python 3.6 and a Jupyter Notebook will be used.
URL:https://micde.umich.edu/event/python-for-data-analysis-2/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190211T123000
DTEND;TZID=America/Detroit:20190211T153000
DTSTAMP:20260606T094739
CREATED:20230905T171356Z
LAST-MODIFIED:20230905T171356Z
UID:10000059-1549888200-1549899000@micde.umich.edu
SUMMARY:Introduction to the Linux Command Line
DESCRIPTION:This course will familiarize the student with the basics of accessing and interacting with Linux computers using the GNU/Linux operating system’s Bash shell\, also generically referred to as “the command line”. Topics include: a brief overview of Linux\, the Bash shell\, navigating the file system\, basic commands\, shell redirection\, permissions\, processes\, and the command environment. The workshop will also provide a quick introduction to nano a simple text editor that will be used in subsequent workshops to edit files. \n \nInstructor\nKenneth Weiss\nIT Project Senior Manager\nMedical School Information Services (MSIS) \nKen is a High Performance Computing Consultant in the Computational Research Consulting Division of MSIS at the University of Michigan. He works with a team of IT specialists to provide high performance computing support and training for the Medical School. Prior to this\, he spent 21 years managing research computing\, including an HPC cluster\, for Dr. Charles Sing in the Human Genetics Department. \nMaterials\n\nLecture Notes (updated Sept. 21\, 2017)\nReference text: William E Shotts\, Jr.\, “The Linux Command Line: A Complete Introduction\,” No Starch Press\, January 2012 .http://linuxcommand.org/tlcl.php\nDownload Creative Commons Licensed version at http://downloads.sourceforge.net/project/linuxcommand/TLCL/13.07/TLCL-13.07.pdf\n\n\nCourse Preparation\nYou must register at least three full days prior to the event so that we have time to insure you have proper UM credentials for the workshop. This allows enough time for you to get your account adjusted by ITS in case you do not have access to the Linux systems.
URL:https://micde.umich.edu/event/introduction-to-the-linux-command-line-2-3-3/
LOCATION:East Hall B254\, 530 Church St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:High Performance Computing,Workshops
ORGANIZER;CN="Advanced Research Computing":MAILTO:arc-contact@umich.edu
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:20190211T090000
DTEND;TZID=America/Detroit:20190211T120000
DTSTAMP:20260606T094739
CREATED:20230905T171356Z
LAST-MODIFIED:20230905T171356Z
UID:10000197-1549875600-1549886400@micde.umich.edu
SUMMARY:Advanced batch computing on the Flux cluster
DESCRIPTION:This course will cover some more advanced topics in cluster computing on the U-M Flux Cluster. Topics to be covered include a review of common parallel programming models and basic use of Flux; dependent and array scheduling; advanced troubleshooting and analysis using checkjob\, qstat\, and other tools; and parallel debugging and profiling of C and Fortran code\, including logging\, gdb (line-oriented debugging)\, ddt (GUI-based debugging) and map (GUI-based profiling) of MPI and OpenMP programs. We will issue you a temporary allocation to use for the course\, or you can use your existing Flux allocations\, if any. \nCourse Prerequisites:  Introduction to Batch Computing on Flux or equivalent. This course assumes familiarity with the Linux command line\, text editing on Linux\, and a basic understanding of Flux including how to submit and track jobs.
URL:https://micde.umich.edu/event/advanced-batch-computing-on-the-flux-cluster-7/
LOCATION:East Hall B254\, 530 Church St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES: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:20190208T150000
DTEND;TZID=America/Detroit:20190208T160000
DTSTAMP:20260606T094739
CREATED:20230905T171357Z
LAST-MODIFIED:20230905T171357Z
UID:10000206-1549638000-1549641600@micde.umich.edu
SUMMARY:MICDE Seminar: David Nordsletten\, Associate Professor\, Department of Biomedical Engineering and Cardiac Surgery\, U-M
DESCRIPTION:Bio: Dr. Nordsletten joined the University of Michigan in January 2019 as an Associate Professor\, is a Reader in cardiovascular biomechanics at King’s College London\, and is the recipient of the EPSRC HTCA leadership fellowship. His research focuses on the novel application of biomechanics integrated with magnetic resonance imaging (MRI) for the advancement of human cardiovascular health. This broad focus encompasses a range of projects spanning from numerical methods development through to direct analysis of medical imaging data for diagnostics in cardiovascular disease. \nTRANSLATIONAL CARDIOVASCULAR BIOMECHANICS AND MAGNETIC RESONANCE IMAGING\nThe application of biomechanics in the heart and cardiovascular system has presented many opportunities to provide unique insights into physiology as well as potential tools for translation to clinical medicine. Key to this analysis is the merger with imaging and experimental tissue mechanics\, providing a core underpinning for studying the heart and cardiovascular system. In this presentation\, I will present recent work in my team exploring a variety of ways in which imaging\, biomechanics and modelling can be leveraged to better understand tissues and blood flow in health and disease.
URL:https://micde.umich.edu/event/micde-seminar-david-nordsletten-associate-professor-department-of-biomedical-engineering-and-cardiac-surgery-u-m/
LOCATION:NCRC Building 10 Research Auditorium\, 2800 Plymouth Rd\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2019/01/David-Nordsletten.png
GEO:42.3016367;-83.7054664
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=NCRC Building 10 Research Auditorium 2800 Plymouth Rd Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=2800 Plymouth Rd:geo:-83.7054664,42.3016367
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190208T140000
DTEND;TZID=America/Detroit:20190208T160000
DTSTAMP:20260606T094739
CREATED:20230905T171357Z
LAST-MODIFIED:20230905T171357Z
UID:10000170-1549634400-1549641600@micde.umich.edu
SUMMARY:Mixed Effects Modeling in Stata
DESCRIPTION:We’ll discuss mixed model regression (also known as multi-level models or hierarchical linear models) in this session which is used for repeated measures data or data which has a clustering element.  We’ll start with a theoretical overview\, discuss choosing an appropriate model\, fitting the models\, checking assumptions and post-hoc analysis. We’ll also cover diagnosing convergence issues. Participants should have basic familiarity with Stata and some working knowledge of linear regression (ordinal least squares).
URL:https://micde.umich.edu/event/mixed-effects-modeling-in-stata-2/
LOCATION:Rackham Building\, Earl Lewis Room\, 3rd Floor East\, 915 E. Washington St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Workshops
GEO:42.2807892;-83.7381556
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:20190208T090000
DTEND;TZID=America/Detroit:20190208T130000
DTSTAMP:20260606T094739
CREATED:20230905T171357Z
LAST-MODIFIED:20230905T171357Z
UID:10000196-1549616400-1549630800@micde.umich.edu
SUMMARY:Introduction to the Flux cluster and batch computing
DESCRIPTION:This workshop will provide a brief overview of the components of the Flux Cluster. The main body of the workshop will cover the resource manager and scheduler\, creating submissions scripts to run jobs and the options available in them\, and hands-on experience. By the end of the workshop\, every participant should have created a submission script\, submitted a job\, tracked its progress\, and collected its output. Participants will have several working examples from which to build their own submissions scripts in their own home directories. \nCourse Preparation (PLEASE READ) \nObtain a user account on Flux. If you do not have a Flux user account\, go to the account application page at: https://arc-ts.umich.edu/fluxform/ \nRegister for Duo authentication. \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.
URL:https://micde.umich.edu/event/introduction-to-the-flux-cluster-and-batch-computing-7/
LOCATION:East Hall B254\, 530 Church St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES: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:20190207T140000
DTEND;TZID=America/Detroit:20190207T170000
DTSTAMP:20260606T094739
CREATED:20230905T171357Z
LAST-MODIFIED:20230905T171357Z
UID:10000195-1549548000-1549558800@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. \n  \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. \n  \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/
LOCATION:East Hall B254\, 530 Church St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES: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:20190207T130000
DTEND;TZID=America/Detroit:20190207T170000
DTSTAMP:20260606T094739
CREATED:20230905T171357Z
LAST-MODIFIED:20230905T171357Z
UID:10000183-1549544400-1549558800@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-2/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190207T120000
DTEND;TZID=America/Detroit:20190207T130000
DTSTAMP:20260606T094739
CREATED:20230905T171357Z
LAST-MODIFIED:20230905T171357Z
UID:10000129-1549540800-1549544400@micde.umich.edu
SUMMARY:MICDE 2019 Catalyst Grants Informational Session
DESCRIPTION:MICDE seeks proposals for innovative research projects in computational science that combine elements of mathematics\, computer science\, and cyberinfrastructure. Of interest is innovative computational research in any emerging area\, including but not limited to  \n\nComputational science approaches\, algorithms\, frameworks\, etc.\nEmerging paradigms in computing (exascale computing\, quantum computing\, FPGA computing\, etc.)\nApplications in emerging areas (neuroscience\, ecology\, evolutionary biology\, human-made complex systems\, mobility etc.)\nExtensions of traditional computational sciences to complex decision making (reinforcement learning\, transfer learning\, neuromorphic computing\, etc.)\nArtificial Intelligence informing and informed by science\n\nGeneric big data problems that do not fundamentally advance computational science algorithms are not suitable for MICDE Catalyst Grants. Priority will be given to high-impact projects with potential to eventually attract external funding. MICDE expects to fund 3-4 one-year projects at up to $100\,000 each. \nIn this informational session\, MICDE officials will clarify the program’s intent\, answer questions and facilitate team formation among attendees. \nRSVP is appreciated\, but not required. Lunch will be provided. \nThe session will be broadcasted via this bluejeans link. For more information go to micde.umich.edu/catalyst/
URL:https://micde.umich.edu/event/micde-2019-catalyst-grants-info-session/
LOCATION:Weiser Hall\, Room 747\, 500 Church St\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,Info Session
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2022/04/signature-vertical.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190206T110000
DTEND;TZID=America/Detroit:20190206T130000
DTSTAMP:20260606T094739
CREATED:20230905T171423Z
LAST-MODIFIED:20230905T171423Z
UID:10000182-1549450800-1549458000@micde.umich.edu
SUMMARY:Introduction to Programming with Python & Matlab
DESCRIPTION:This is a four-part workshop introducing programming concepts to those with little-to-no programming experience. \nThe four 2-hour sessions will take place over two weeks\, with Python being taught in the first three sessions\, and Matlab in the fourth session. Computers are provided. \nSession 1: Feb 6\, 11am – 1pm – Location: MLB 2001a \nSession 2: Feb 7\, 11am – 1pm –  Location: MLB 2001A \nSession 3: Feb 13\, 11am – 1pm – Location: MLB 2001A \nSession 4: Feb 14\, 11am – 1pm – Location: MLB 2001A
URL:https://micde.umich.edu/event/introduction-to-programming-with-python-matlab/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190206T090000
DTEND;TZID=America/Detroit:20190206T120000
DTSTAMP:20260606T094739
CREATED:20230905T171423Z
LAST-MODIFIED:20230905T171423Z
UID:10000194-1549443600-1549454400@micde.umich.edu
SUMMARY:Advanced batch computing on the Flux cluster
DESCRIPTION:This course will cover some more advanced topics in cluster computing on the U-M Flux Cluster. Topics to be covered include a review of common parallel programming models and basic use of Flux; dependent and array scheduling; advanced troubleshooting and analysis using checkjob\, qstat\, and other tools; and parallel debugging and profiling of C and Fortran code\, including logging\, gdb (line-oriented debugging)\, ddt (GUI-based debugging) and map (GUI-based profiling) of MPI and OpenMP programs. We will issue you a temporary allocation to use for the course\, or you can use your existing Flux allocations\, if any. \nCourse Prerequisites:  Introduction to Batch Computing on Flux or equivalent. This course assumes familiarity with the Linux command line\, text editing on Linux\, and a basic understanding of Flux including how to submit and track jobs.
URL:https://micde.umich.edu/event/advanced-batch-computing-on-the-flux-cluster-6/
LOCATION:East Hall B254\, 530 Church St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES: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:20190205T140000
DTEND;TZID=America/Detroit:20190205T160000
DTSTAMP:20260606T094739
CREATED:20230905T171424Z
LAST-MODIFIED:20230905T171424Z
UID:10000181-1549375200-1549382400@micde.umich.edu
SUMMARY:Generalized estimating equations in Python
DESCRIPTION:GEE is an extension of the generalized linear modeling (GLM) framework for dependent data.  GEE can be used with longitudinal data\, clustered data\, and other forms of dependent data where a GLM may not be appropriate.  In this workshop we will discuss fitting models using GEE in Python with the Statsmodels package.  We will briefly cover the underlying foundation for GEE\, but will mainly focus on practical aspects of utilizing GEE in Python\, through several case studies.  More advanced topics including model selection and regularized fitting may be covered\, depending on student interest.  \nParticipants should bring a laptop if they want to work with the examples during the presentation\, but this is optional.
URL:https://micde.umich.edu/event/generalized-estimating-equations-in-python/
LOCATION:Rackham Building\, Earl Lewis Room\, 3rd Floor East\, 915 E. Washington St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Workshops
GEO:42.2807892;-83.7381556
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:20190205T123000
DTEND;TZID=America/Detroit:20190205T153000
DTSTAMP:20260606T094739
CREATED:20230905T171424Z
LAST-MODIFIED:20230905T171424Z
UID:10000193-1549369800-1549380600@micde.umich.edu
SUMMARY:Introduction to the Linux Command Line
DESCRIPTION:This course will familiarize the student with the basics of accessing and interacting with Linux computers using the GNU/Linux operating system’s Bash shell\, also generically referred to as “the command line”. Topics include: a brief overview of Linux\, the Bash shell\, navigating the file system\, basic commands\, shell redirection\, permissions\, processes\, and the command environment. The workshop will also provide a quick introduction to nano a simple text editor that will be used in subsequent workshops to edit files. \nINSTRUCTOR \nKenneth Weiss\nIT Project Senior Manager\nMedical School Information Services (MSIS) \nKen is a High Performance Computing Consultant in the Computational Research Consulting Division of MSIS at the University of Michigan. He works with a team of IT specialists to provide high performance computing support and training for the Medical School. Prior to this\, he spent 21 years managing research computing\, including an HPC cluster\, for Dr. Charles Sing in the Human Genetics Department. \nMATERIALS \n\nLecture Notes\nReference text: William E Shotts\, Jr.\, “The Linux Command Line: A Complete Introduction\,” No Starch Press\, January 2012 .http://linuxcommand.org/tlcl.php\nDownload Creative Commons Licensed version at http://downloads.sourceforge.net/project/linuxcommand/TLCL/13.07/TLCL-13.07.pdf\n\n\nCOURSE PREPARATION \nYou must register at least three full days prior to the event so that we have time to insure you have proper UM credentials for the workshop. This allows enough time for you to get your account adjusted by ITS in case you do not have access to the Linux systems.
URL:https://micde.umich.edu/event/introduction-to-the-linux-command-line-7/
LOCATION:East Hall B254\, 530 Church St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES: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:20190205T083000
DTEND;TZID=America/Detroit:20190205T150000
DTSTAMP:20260606T094739
CREATED:20230905T171424Z
LAST-MODIFIED:20230905T171424Z
UID:10000037-1549355400-1549378800@micde.umich.edu
SUMMARY:Statistical Analysis with R
DESCRIPTION:This is a two day workshop (February 4 and 5) in R which  is a free and open source environment for data analysis and statistical computing.  While R contains many built-in statistical procedures\, a powerful feature of R is the facility for users to extend these procedures to suit their own needs.  Excellent graphing capability is another reason R is gaining wide popularity. \n\nHow to Obtain R\nHelp Tools\nImporting / Exporting Data\nData Management\nDescriptive and Exploratory Statistics\nCommon Statistical Analyses (t-test\, Regression Modeling\, ANOVA\, etc.)\nGraphics\nCreating Functions\n\n 
URL:https://micde.umich.edu/event/statistical-analysis-with-r-2-2-2/2019-02-05/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190204T130000
DTEND;TZID=America/Detroit:20190204T170000
DTSTAMP:20260606T094739
CREATED:20230905T171423Z
LAST-MODIFIED:20230905T171423Z
UID:10000192-1549285200-1549299600@micde.umich.edu
SUMMARY:Introduction to the Flux cluster and batch computing
DESCRIPTION:This workshop will provide a brief overview of the components of the Flux Cluster. The main body of the workshop will cover the resource manager and scheduler\, creating submissions scripts to run jobs and the options available in them\, and hands-on experience. By the end of the workshop\, every participant should have created a submission script\, submitted a job\, tracked its progress\, and collected its output. Participants will have several working examples from which to build their own submissions scripts in their own home directories. \nCourse Preparation (PLEASE READ) \nObtain a user account on Flux. If you do not have a Flux user account\, go to the account application page at: https://arc-ts.umich.edu/fluxform/ \nRegister for Duo authentication. \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.
URL:https://micde.umich.edu/event/introduction-to-the-flux-cluster-and-batch-computing-6/
LOCATION:East Hall B254\, 530 Church St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES: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:20190204T130000
DTEND;TZID=America/Detroit:20190204T160000
DTSTAMP:20260606T094739
CREATED:20230905T171423Z
LAST-MODIFIED:20230905T171423Z
UID:10000180-1549285200-1549296000@micde.umich.edu
SUMMARY:Data Visualization With 3D Graphics Using Unity3D
DESCRIPTION:Video game development is more accessible than ever thanks to advanced software tools. Unity3D is one of the most popular game engines available\, thanks to its ease of use\, support for multiple platforms\, and affordable pricing options (including free!). In addition to powering the majority of mobile and independently-developed games\, the engine is being used in new applications\, including animated short films by Disney\, automotive design and self-driving training at Audi and Toyota\, and augmented-reality demonstrations. Unity3D is beginning to be a viable tool to use alongside scientific projects\, especially those that require 3D visual representation of pre-computed data for user analysis. \nIn this workshop\, we introduce the Unity3D workspace\, and prepare a demo that allows the user to load an example data-set and view it as a simple set of 3D representations.  \nA basic familiarity with computer programming (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 bring their own laptop with Unity3D (available for Windows or Macintosh) 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/
LOCATION:Rackham Building\, Earl Lewis Room\, 3rd Floor East\, 915 E. Washington St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Workshops
GEO:42.2807892;-83.7381556
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:20190204T083000
DTEND;TZID=America/Detroit:20190204T150000
DTSTAMP:20260606T094739
CREATED:20230905T171423Z
LAST-MODIFIED:20230905T171423Z
UID:10000036-1549269000-1549292400@micde.umich.edu
SUMMARY:Statistical Analysis with R
DESCRIPTION:This is a two day workshop (February 4 and 5) in R which  is a free and open source environment for data analysis and statistical computing.  While R contains many built-in statistical procedures\, a powerful feature of R is the facility for users to extend these procedures to suit their own needs.  Excellent graphing capability is another reason R is gaining wide popularity. \n\nHow to Obtain R\nHelp Tools\nImporting / Exporting Data\nData Management\nDescriptive and Exploratory Statistics\nCommon Statistical Analyses (t-test\, Regression Modeling\, ANOVA\, etc.)\nGraphics\nCreating Functions\n\n 
URL:https://micde.umich.edu/event/statistical-analysis-with-r/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190201T140000
DTEND;TZID=America/Detroit:20190201T160000
DTSTAMP:20260606T094739
CREATED:20230905T171423Z
LAST-MODIFIED:20230905T171423Z
UID:10000169-1549029600-1549036800@micde.umich.edu
SUMMARY:Regression Modeling in Stata
DESCRIPTION:In this session\, we will discuss fitting traditional regression models in Stata\, including linear regression\, logistic regression\, and time-allowing\, poisson regression. We’ll briefly introduce the theory behind the models\, discuss choosing an appropriate model\, fitting the model\, checking assumptions and some post-hoc analysis. Participants are expected to have some basic familiarity with Stata.
URL:https://micde.umich.edu/event/regression-modeling-in-stata-2/
LOCATION:Rackham Building\, Earl Lewis Room\, 3rd Floor East\, 915 E. Washington St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Workshops
GEO:42.2807892;-83.7381556
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:20190201T110000
DTEND;TZID=America/Detroit:20190201T120000
DTSTAMP:20260606T094739
CREATED:20230905T171423Z
LAST-MODIFIED:20230905T171423Z
UID:10000176-1549018800-1549022400@micde.umich.edu
SUMMARY:MICDE Seminar: Amir Ali Ahmadi\, Assistant Professor\, Operations Research and Financial Engineering\, Princeton University
DESCRIPTION:Bio: Amir Ali Ahmadi is an Assistant Professor at the Department of Operations Research and Financial Engineering at Princeton University and an Associated Faculty member of the Program in Applied and Computational Mathematics\, the Department of Computer Science\, the Department of Mechanical and Aerospace Engineering\, and the Center for Statistics and Machine Learning. Amir Ali received his PhD in EECS from MIT and was a Goldstine Fellow at the IBM Watson Research Center prior to joining Princeton. His research interests are in optimization theory\, computational aspects of dynamics and control\, and algorithms and complexity. Amir Ali’s distinctions include the Sloan Fellowship in Computer Science\, a MURI award from the AFOSR\, the NSF CAREER Award\, the AFOSR Young Investigator Award\, the DARPA Faculty Award\, the Google Faculty Award\, the Howard B. Wentz Junior Faculty Award as well as the Innovation Award of Princeton University\, the Goldstine Fellowship of IBM Research\, and the Oberwolfach Fellowship of the NSF. His undergraduate course at Princeton (ORF 363\, “Computing and Optimization’’) has received the 2017 Excellence in Teaching of Operations Research Award of the Institute for Industrial and Systems Engineers and the 2017 Phi Beta Kappa Award for Excellence in Undergraduate Teaching at Princeton University. Amir Ali is also the recipient of a number of best-paper awards\, including the INFORMS Optimization Society’s Young Researchers Prize\, the INFORMS Computing Society Prize (for best series of papers at the interface of operations research and computer science)\, the Best Conference Paper Award of the IEEE International Conference on Robotics and Automation\, and the prize for one of two most outstanding papers published in the SIAM Journal on Control and Optimization in 2013-2015. \nPOLYNOMIAL OPTIMIZATION AND DYNAMICAL SYSTEMS\nIn recent years\, there has been a surge of exciting research activity at the interface of optimization (in particular polynomial\, semidefinite\, and sum of squares optimization) and the theory of dynamical systems. In this talk\, we focus on two of our current research directions that are at this interface. In part (i)\, we propose more scalable alternatives to sum of squares optimization and show how they impact verification problems in control and robotics\, as well as some classic questions in polynomial optimization and statistics. Our new algorithms do not rely on semidefinite programming\, but instead use linear programming\, or second-order cone programming\, or are altogether free of optimization. In particular\, we present the first Positivstellensatz that certifies infeasibility of a set of polynomial inequalities simply by multiplying certain fixed polynomials together and checking nonnegativity of the coefficients of the resulting product.\nIn part (ii)\, we introduce a new class of optimization problems whose constraints are imposed by trajectories of a dynamical system. As a concrete example\, we consider the problem of optimizing a linear function over the set of initial conditions that forever remain inside a given polyhedron under the action of a linear\, or a switched linear\, dynamical system. We present a hierarchy of linear and semidefinite programs that respectively lower and upper bound the optimal value of such problems to arbitrary accuracy. \nThis seminar is co-sponsored by the department of Industrial and Operations Engineering. Prof. Ahmadi is being hosted by Prof. Shen (IOE). If you would like to meet with him during his visit\, please send an email to micde-events@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-amir-ali-ahmadi-assistant-professor-operations-research-and-financial-engineering-princeton-university/
LOCATION:2717 IOE\, 1205 BEAL AVE\, ANN ARBOR\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
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