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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200615T130000
DTEND;TZID=America/Detroit:20200615T150000
DTSTAMP:20260605T112455
CREATED:20230905T171250Z
LAST-MODIFIED:20230905T171250Z
UID:10000366-1592226000-1592233200@micde.umich.edu
SUMMARY:SRTI: Software For Cross-Language Real-Time Data Communication
DESCRIPTION:A BlueJeans link will be sent to all registered participants. \nComputer software simulation is used in virtually every discipline. These programs virtually represent small components of real-world events and behaviors\, and allow scientists to test different models to guide real-world research. However\, these can be individually complex\, and written in different computer languages and programs. It’s a difficult task to combine simulators from different parts of a research team to represent larger systems. \nThe “Simple Run-Time Infrastructure” is an open-source\, free-to-use software tool\, developed at the University of Michigan. It was built to simplify the process of sharing data between multiple live simulators\, using a “publish/subscribe” model with messages rather than directly to specific programs. This workshop will present the background of the SRTI’s development\, what it is capable of\, and will provide a step-by-step example for participants. \nJava will be required to run the SRTI. The example will use an optional mixture that includes simulators written in Java\, Matlab\, and Python.
URL:https://micde.umich.edu/event/srti-software-for-cross-language-real-time-data-communication/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200610T140000
DTEND;TZID=America/Detroit:20200610T160000
DTSTAMP:20260605T112455
CREATED:20230905T171345Z
LAST-MODIFIED:20230905T171345Z
UID:10000377-1591797600-1591804800@micde.umich.edu
SUMMARY:R IV: Visualization
DESCRIPTION:This session will be held online\, and presenters will be in touch with more information after you register.\n\nVisualizing the results of research is a key aspect in facilitating scientific communication to a broad audience. The focus of this workshop will be on using common tools in R for visualization\, general concerns in producing visual information\, and demonstration of approaches that allow for interactivity.\n\n\nPrereq: Some experience using R is required (R I\, preferably R II workshops)\, as well as exposure to basic statistical analysis would be beneficial.\n\n\nContent: http://m-clark.github.io/data-processing-and-visualization/
URL:https://micde.umich.edu/event/r-iv-visualization/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200608T140000
DTEND;TZID=America/Detroit:20200608T163000
DTSTAMP:20260605T112455
CREATED:20230905T171345Z
LAST-MODIFIED:20230905T171345Z
UID:10000365-1591624800-1591633800@micde.umich.edu
SUMMARY:Mapping tools to visualize COVID19 data
DESCRIPTION:This session will be held online\, and presenters will be in touch with more information after you register.\n\nThis workshop will help you learn the approaches and tools to visualize spatial data using R and QGIS. We will use the COVID19 data available at (https://github.com/nytimes/covid-19-data) and combine it with information from Census and other sources to visualize spatial patterns and make production quality maps.\n\nParticipants should have some exposure to R and vector data GIS.
URL:https://micde.umich.edu/event/mapping-tools-to-visualize-covid19-data/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200602T150000
DTEND;TZID=America/Detroit:20200602T160000
DTSTAMP:20260605T112455
CREATED:20230905T171345Z
LAST-MODIFIED:20230905T171345Z
UID:10000605-1591110000-1591113600@micde.umich.edu
SUMMARY:MICDE Webinar Series: Gabriel Ehrlich\, Director\, Research Seminar in Quantitative Economics\, University of Michigan
DESCRIPTION:Bio: Dr. Gabriel Ehrlich is the Director of the Research Seminar in Quantitative Economics (RSQE)\, and an Assistant Research Scientist in the department of Economics at the University of Michigan. Prior to joining RSQE\, he worked in the Financial Analysis Division at the Congressional Budget Office (CBO)\, where he forecast interest rates and conducted analysis on monetary policy and the mortgage finance system. His academic research focuses on several areas of housing and land economics as well as the effects of wage rigidity on labor market outcomes. \nMODELING THE ECONOMIC OUTLOOK IN THE TIME OF COVID-19\nWe will present the Research Seminar in Quantitative Economics’ (RSQE’s) forecast for the national and Michigan economies from 2020 to 2022. We will discuss the incoming data during the COVID-19 pandemic\, the near-term economic damage\, and the prospects for economic recovery. RSQE is the world’s oldest continuously operating economic forecasting unit and is home to the “Michigan Model” of the U.S. economy.
URL:https://micde.umich.edu/event/micde-webinar-series-gabriel-ehrlich-director-research-seminar-in-quantitative-economics-university-of-michigan/
LOCATION:Zoom Event\, MI\, United States
CATEGORIES:Education,Featured Events,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/07/Gabriel-Ehrlich.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200602T150000
DTEND;TZID=America/Detroit:20200602T160000
DTSTAMP:20260605T112455
CREATED:20230905T171345Z
LAST-MODIFIED:20230905T171345Z
UID:10000375-1591110000-1591113600@micde.umich.edu
SUMMARY:MICDE Webinar Series: Gabriel Ehrlich\, Director\, Research Seminar in Quantitative Economics\, University of Michigan
DESCRIPTION:Bio: Dr. Gabriel Ehrlich is the Director of the Research Seminar in Quantitative Economics (RSQE)\, and an Assistant Research Scientist in the department of Economics at the University of Michigan. Prior to joining RSQE\, he worked in the Financial Analysis Division at the Congressional Budget Office (CBO)\, where he forecast interest rates and conducted analysis on monetary policy and the mortgage finance system. His academic research focuses on several areas of housing and land economics as well as the effects of wage rigidity on labor market outcomes. \nMODELING THE ECONOMIC OUTLOOK IN THE TIME OF COVID-19\nWe will present the Research Seminar in Quantitative Economics’ (RSQE’s) forecast for the national and Michigan economies from 2020 to 2022. We will discuss the incoming data during the COVID-19 pandemic\, the near-term economic damage\, and the prospects for economic recovery. RSQE is the world’s oldest continuously operating economic forecasting unit and is home to the “Michigan Model” of the U.S. economy. \nWatch the full seminar.
URL:https://micde.umich.edu/event/webinar-gabriel-ehrlich-2020/
CATEGORIES:Featured Events,Webinar
ATTACH;FMTTYPE=image/jpeg:https://micde.umich.edu/wp-content/uploads/2023/02/Ehrlich.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200601T150000
DTEND;TZID=America/Detroit:20200601T170000
DTSTAMP:20260605T112455
CREATED:20230905T171345Z
LAST-MODIFIED:20230905T171345Z
UID:10000376-1591023600-1591030800@micde.umich.edu
SUMMARY:CSCAR/MIDAS Workshop on Data\, Methodology\, and Covid
DESCRIPTION:Zoom link:  https://umich.zoom.us/j/99072338239 \n  \nThe second CSCAR/MIDAS workshop on Data\, Methodology\, and Covid will focus on Covid testing and mortality data from the Covid Tracking Project (covidtracking.com) and Worldometer (worldometer.com).  We will develop insight into how the reported PCR testing data from various US states\, and from different countries\, can be informative about Covid deaths in those localities.  We will also discuss some of the challenges of estimating the “infection fatality ratio” with this type of data\, and conduct some sensitivity analyses to see what the IFR would be in different settings. \nThe workshop will use intermediate statistical methods (to be reviewed in the workshop)\, and computations will be done in Python.  Notebooks and links to data will be provided.
URL:https://micde.umich.edu/event/cscar-midas-workshop-on-data-methodology-and-covid/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200529T130000
DTEND;TZID=America/Detroit:20200529T160000
DTSTAMP:20260605T112455
CREATED:20230905T171345Z
LAST-MODIFIED:20230905T171345Z
UID:10000373-1590757200-1590768000@micde.umich.edu
SUMMARY:Advanced research computing on the Great Lakes Cluster
DESCRIPTION:OVERVIEW\n\n\nThis workshop will cover some more advanced topics in computing on the U-M Great Lakes Cluster. Topics to be covered include a review of common parallel programming models and basic use of Great Lakes; dependent and array scheduling; workflow scripting using bash; high-throughput computing using launcher; parallel processing in one or more of Python\, R\, and MATLAB; and profiling of parallel code using Allinea Performance Reports and Allinea MAP. \nPRE-REQUISITES\nThis course assumes familiarity with the Linux command line as might be got from the CSCAR/ARC-TS workshop Introduction to the Linux Command Line. In particular\, participants should understand how files and folders work\, be able to create text files using the nano editor\, be able to create and remove files and folders\, and understand what input and output redirection are and how to use them. \nINSTRUCTORS\nDr. Charles J Antonelli\nResearch Computing Services\nLSA Technology Services \nCharles is a member of the LSA Technology Services Research team at the University of Michigan\, where he is responsible for high performance computing support and education\, and was an Advocate to the Departments of History and Communications. Prior to this\, he built a parallel data ingestion component of a novel earth science data assimilation system\, a secure packet vault\, and worked on the No. 5 ESS Switch at Bell Labs in the 80s. He has taught courses in operating systems\, distributed file systems\, C++ programming\, security\, and database application design. \nJohn Thiels\nResearch Computing Services\nLSA Technology Services \nMATERIALS\n\nLecture Notes\nMPI Profiling with Allinea MAP\nGreat Lakes Slurm HPC cluster\n\n\nCOURSE PREPARATION\nIn order to participate successfully in the workshop exercises\, you must have a user login\, a Slurm account\, and be enrolled in Duo. The user login allows you to log in to the cluster\, create\, compile\, and test applications\, and prepare jobs for submission. The Slurm account allows you to submit those jobs\, executing the applications in parallel on the cluster and charging their resource use to the account. Duo is required to help authenticate you to the cluster. \nUSER LOGIN\nIf you already have a Flux user login\, you don’t need to do anything.  Otherwise\, go to the Flux user login application page at: http://arc-ts.umich.edu/login-request/ . \nPlease note that obtaining a user account requires human processing\, so be sure to do this at least two business days before class begins. \nSLURM ACCOUNT\nWe create a Slurm account for the workshop so you can run jobs on the cluster during the workshop and for one day after for those who would like additional practice. The workshop job account is quite limited and is intended only to run examples to help you cement the details of job submission and management. If you already have an existing Slurm account\, you can use that\, though if there are any issues with that account\, we will ask you to use the workshop account. \nDUO AUTHENTICATION\nDuo two-factor authentication is required to log in to the cluster. When logging in\, you will need to type your UMICH (AKA Level 1) password as well as authenticate through Duo in order to access Great Lakes. \nIf you need to enroll in Duo\, follow the instructions at Enroll a Smartphone or Tablet in Duo. \nPlease enroll in Duo before you come to class. \n\nLAPTOP PREPARATION\nYou will need an ssh client to connect to the Great Lakes cluster. Mac OS X and Linux platforms have this built-in. Here are a couple of choices for Windows platforms: \n\nDownload and install U-M PuTTY/WinSCP from the Compute at the U website. This includes both the PuTTY ssh client and terminal emulator and a graphical file transfer tool in one installer.\nDownload and install PuTTY directly from the developer.Our Great Lakes User Guide in Section 1.2 describes in more detail how to use PuTTY to connect to Great Lakes.\n\nPlease prepare and test your computer’s ability to make remote connections before class; we cannot stop to debug connection issues during the class. \n\nA Zoom link will be provided to the participants the day before the class. Registration is required.
URL:https://micde.umich.edu/event/advanced-research-computing-on-the-great-lakes-cluster-3/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200528T100000
DTEND;TZID=America/Detroit:20200528T130000
DTSTAMP:20260605T112455
CREATED:20230905T171345Z
LAST-MODIFIED:20230905T171345Z
UID:10000372-1590660000-1590670800@micde.umich.edu
SUMMARY:Research computing on the Great Lakes Cluster
DESCRIPTION:OVERVIEW \nThis workshop will provide a brief overview of the components of the Great Lakes 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. \nPRE-REQUISITES\nThis course assumes familiarity with the Linux command line as might be got from the CSCAR/ARC-TS workshop Introduction to the Linux Command Line. In particular\, participants should understand how files and folders work\, be able to create text files using the nano editor\, be able to create and remove files and folders\, and understand what input and output redirection are and how to use them. \nINSTRUCTORS\nDr. Charles J Antonelli\nResearch Computing Services\nLSA Technology Services \nCharles is a member of the LSA Technology Services Research team at the University of Michigan\, where he is responsible for high performance computing support and education\, and was an Advocate to the Departments of History and Communications. Prior to this\, he built a parallel data ingestion component of a novel earth science data assimilation system\, a secure packet vault\, and worked on the No. 5 ESS Switch at Bell Labs in the 80s. He has taught courses in operating systems\, distributed file systems\, C++ programming\, security\, and database application design. \nJohn Thiels\nResearch Computing Services\nLSA Technology Services \nMark Champe\nResearch Computing Services\nLSA Technology Services \nMATERIALS\nLecture notes\nGreat Lakes HPC cluster \nCOURSE PREPARATION\nIn order to participate successfully in the workshop exercises\, you must have a user login\, a Slurm account\, and be enrolled in Duo. The user login allows you to log in to the cluster\, create\, compile\, and test applications\, and prepare jobs for submission. The Slurm account allows you to submit those jobs\, executing the applications in parallel on the cluster and charging their resource use to the account. Duo is required to help authenticate you to the cluster. \nUSER LOGIN\nIf you don’t already have a Great Lakes user login\, please visit the application page. \nPlease note that obtaining a user account requires human processing\, so be sure to do this at least two business days before class begins. \nSLURM ACCOUNT\nWe create a Slurm account for the workshop so you can run jobs on the cluster during the workshop and for one day after for those who would like additional practice. The workshop job account is quite limited and is intended only to run examples to help you cement the details of job submission and management. If you already have an existing Slurm account\, you can use that\, though if there are any issues with that account\, we will ask you to use the workshop account. \nDUO AUTHENTICATION\nDuo two-factor authentication is required to log in to the cluster. When logging in\, you will need to type your UMICH (AKA Level 1) password as well as authenticate through Duo in order to access Great Lakes. \nIf you need to enroll in Duo\, follow the instructions at Enroll a Smartphone or Tablet in Duo. \nPlease enroll in Duo before you come to class. \nLAPTOP PREPARATION \nYou will need an ssh client to connect to the Great Lakes cluster. Mac OS X and Linux platforms have this built-in. Here are a couple of choices for Windows platforms: \nDownload and install U-M PuTTY/WinSCP from the Compute at the U website. This includes both the PuTTY ssh client and terminal emulator and a graphical file transfer tool in one installer.\nDownload and install PuTTY directly from the developer.Our Great Lakes User Guide in Section 1.2 describes in more detail how to use PuTTY to connect to Great Lakes.\nPlease prepare and test your computer’s ability to make remote connections before class; we cannot stop to debug connection issues during the class. \nA Zoom link will be provided to the participants the day before the class. Registration is required.
URL:https://micde.umich.edu/event/research-computing-on-the-great-lakes-cluster-10/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200527T130000
DTEND;TZID=America/Detroit:20200527T160000
DTSTAMP:20260605T112455
CREATED:20230905T171345Z
LAST-MODIFIED:20230905T171345Z
UID:10000374-1590584400-1590595200@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 \nHITS Academic IT – HPC team \nKen is a High Performance Computing Consultant with the Health Information Technology & Services (HITS) Academic IT – HPC team 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. \nIf 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. \nYou will need an ssh client to connect to the training host. Mac OS X and Linux platforms have this built-in. Here are a couple of choices for Windows platforms: \n· Download and install U-M PuTTY/WinSCP from the Compute at the U website. This includes both the PuTTY ssh client and terminal emulator and a graphical file transfer tool in one installer. \n· Download and install PuTTY directly from the developer. \nDuring class you will be given the name of the training host to be able to participate in the hands-on activities. \nA Zoom link will be provided to the participants the day before the class. Registration is required. \nInstructor will be available at the Zoom link\, to be provided\, from 12-1 PM for computer setup assistance. \n\nIf you have questions about this workshop\, please send an email to the instructor at kgweiss@umich.edu
URL:https://micde.umich.edu/event/introduction-to-the-linux-command-line-12/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200518T150000
DTEND;TZID=America/Detroit:20200518T170000
DTSTAMP:20260605T112455
CREATED:20230905T171345Z
LAST-MODIFIED:20230905T171345Z
UID:10000368-1589814000-1589821200@micde.umich.edu
SUMMARY:CSCAR/MIDAS workshops on data\, methodology\, and Covid
DESCRIPTION:CSCAR and MIDAS will hold a series of on-line technical workshops on the use of publicly-available data for analyzing human health at the population level. Some of the analyses and data are relevant to understanding the covid pandemic\, but the focus of these workshops is on methods that are of broader use in population health research. Participants will gain practical skills in using intermediate methods from statistics and data science to gain meaningful insights from various types of data. Python code and links to all relevant data will be provided for each workshop. The first workshop in this series will be held on May 18th from 3-5pm\, and will cover the use of generalized linear modeling and generalized PCA to gain insight into mortality trends among various demographic subgroups in the United States\, using data from the CDC.
URL:https://micde.umich.edu/event/cscar-midas-workshops-on-data-methodology-and-covid/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200515T130000
DTEND;TZID=America/Detroit:20200515T153000
DTSTAMP:20260605T112455
CREATED:20230905T171344Z
LAST-MODIFIED:20230905T171344Z
UID:10000362-1589547600-1589556600@micde.umich.edu
SUMMARY:Spatial Point Process Modelling in R
DESCRIPTION:A BlueJeans link will be sent to all registered participants.\n\nSpatial point process models help us analyze the geometrical pattern of points (events) in space and find application in a variety of fields including image processing\, public health\, forestry\, ecology\, and business. This workshop will provide an introduction to point process models focusing on the conceptual aspects and implementation in R.\n\nThe concepts and techniques transfer naturally to similar problems in 1-D (e.g. events in time). So\, the workshop will also be useful for participants who want to learn about analysis of random events in time.
URL:https://micde.umich.edu/event/spatial-point-process-modelling-in-r/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200512T130000
DTEND;TZID=America/Detroit:20200512T140000
DTSTAMP:20260605T112455
CREATED:20230905T171344Z
LAST-MODIFIED:20260522T153619Z
UID:10000364-1589288400-1589292000@micde.umich.edu
SUMMARY:CAsToR Webinar: Modeling in Tobacco Control in the U.S. - the good\, the bad\, the ugly
DESCRIPTION:Center for the Assessment of Tobacco Regulations [CAsToR] leads Drs. Levy\, Mendez\, and Meza will provide an overview of modeling applications in tobacco control research\, discuss the types of models used in this field and their purpose\, as well as future directions for modeling in tobacco regulatory science. A Q&A session will follow. \nPlease contact Katie Zarins (kmrents@umich.edu) with questions \nDr. David Levy\nProfessor\nGeorgetown University\n  \n  \n  \n \nDr. David Mendez\nAssociate Professor\nUM School of Public Health\n  \n  \n  \n \nRafael Meza\nAssociate Professor\nUM School Public Health\n  \n  \n  \n 
URL:https://micde.umich.edu/event/castor-webinar-modeling-in-tobacco-control-in-the-u-s-the-good-the-bad-the-ugly/
LOCATION:Zoom Event
CATEGORIES:Featured Events,Webinar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200505T090000
DTEND;TZID=America/Detroit:20200505T113000
DTSTAMP:20260605T112455
CREATED:20230905T171344Z
LAST-MODIFIED:20230905T171344Z
UID:10000363-1588669200-1588678200@micde.umich.edu
SUMMARY:Intro to SQL
DESCRIPTION:Ever want to know how to communicate with a database? You need to know SQL\, a standard programming language for working with relational database management systems in data warehouses or just Microsoft Access. This workshop will cover the basic syntax of SQL. Material will focus mainly on how to query databases. A web-based tool will be used for the tutorial.
URL:https://micde.umich.edu/event/intro-to-sql-6/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200420T140000
DTEND;TZID=America/Detroit:20200420T163000
DTSTAMP:20260605T112455
CREATED:20230905T171344Z
LAST-MODIFIED:20230905T171344Z
UID:10000359-1587391200-1587400200@micde.umich.edu
SUMMARY:Geostatistical Analysis with R
DESCRIPTION:This session will be held online\, and presenters will be in touch with more information after you register. \n  \nGeostatistical approach models spatially correlated continuous random phenomenon for robust estimation and prediction. The approach is common across different fields in applied science where continuous phenomenon is observed at a few locations in space and the task is to estimate it at un-sampled locations. \nWe will use R to explore and develop an understanding of variogram and kriging and how they can be used for robust and unbiased interpolation of data over space. \nThis workshop will be offered remotely via BlueJeans.
URL:https://micde.umich.edu/event/geostatistical-analysis-with-r/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200417T150000
DTEND;TZID=America/Detroit:20200417T163000
DTSTAMP:20260605T112455
CREATED:20230905T171344Z
LAST-MODIFIED:20230905T171344Z
UID:10000606-1587135600-1587141000@micde.umich.edu
SUMMARY:Webinar: Transmission modeling of infectious diseases and the COVID-19 outbreak
DESCRIPTION:This seminar will focus on differential equation transmission modeling approaches to analyze the spread of infections diseases\, and how Prof. Eisenberg and her colleagues are using them to model the current COVID-19 outbreak in the State of Michigan.Their current model is helping to forecast the numbers of laboratory-confirmed cases\, fatalities\, hospitalized patients\, and hospital capacity issues (such as ICU beds needed)\, and examining how social distancing can impact the spread of the epidemic.
URL:https://micde.umich.edu/event/webinar-transmission-modeling-of-infectious-diseases-and-the-covid-19-outbreak/
LOCATION:BlueJeans Events
CATEGORIES:Education,Featured Events,MICDE Seminar Series,Webinar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2023/07/Marisa-Eisenberg.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200417T090000
DTEND;TZID=America/Detroit:20200417T170000
DTSTAMP:20260605T112455
CREATED:20230905T171344Z
LAST-MODIFIED:20230905T171344Z
UID:10000361-1587114000-1587142800@micde.umich.edu
SUMMARY:Introduction to Survey Design: Data Collection\, Questionnaire Design and Response Processes-Lecture
DESCRIPTION:This session will be held online\, and presenters will be in touch with more information after you register. \n  \nThis lecture-format workshop will present an overview of available modes and methods of survey data collection as well as an introduction to the survey response process and implications for questionnaire design. Participants will gain an appreciation of the tradeoffs inherent in survey design decisions and how design can affect data quality and survey errors. Topics will include: \nSurvey errors\, in particular measurement\, coverage\, and nonresponse error.\nWhat to consider when selecting a data collection method for a particular research question.\nMeasurement (response) error and how to reduce it through question wording/format and questionnaire structure.\nThe role of the interviewer and interviewee effects.
URL:https://micde.umich.edu/event/introduction-to-survey-design-data-collection-questionnaire-design-and-response-processes-lecture-3/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200413T150000
DTEND;TZID=America/Detroit:20200413T170000
DTSTAMP:20260605T112455
CREATED:20230905T171344Z
LAST-MODIFIED:20230905T171344Z
UID:10000341-1586790000-1586797200@micde.umich.edu
SUMMARY:Statistical analysis with missing data in Python
DESCRIPTION:This session will be held online\, and presenters will be in touch with more information after you register. \n  \nMissing data arise in many fields of research\, and a large body of statistical tools has been developed to facilitate statistical analysis in the presence of missing data.  Here we focus mainly on multiple imputation\, which is a broadly-applicable approach for working with missing data. We will illustrate through several case studies how multiple imputation allows certain types of missing data to be rigorously accounted for\, while preserving the flexibility to use a variety of familiar statistical tools to account for other aspects of the data.   The analyses presented in this workshop will be performed in Python using the Statsmodels package. All software tools covered in this workshop are free and open source.
URL:https://micde.umich.edu/event/statistical-analysis-with-missing-data-in-python-2/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200409T130000
DTEND;TZID=America/Detroit:20200409T143000
DTSTAMP:20260605T112455
CREATED:20230905T171344Z
LAST-MODIFIED:20260522T183951Z
UID:10000358-1586437200-1586442600@micde.umich.edu
SUMMARY:Webinar: 2020 MICDE Catalyst Grants Showcase - Session II
DESCRIPTION:This webinar will showcase some of the game-changing research supported by our Catalyst Grants program. \nThis event was recorded and will be on the UM Youtube channel shortly. \nSpeakers\n \nStephen Smith\nAssociate Professor of Ecology and Evolutionary Biology\nUniversity of Michigan\nThe Emergence of Biological Complexity and Evolutionary Innovation in Plant Genomes\n\nXun Huan\nAssistant Professor of Mechanical Engineering\nUniversity of Michigan\nTowards Bayesian Uncertainty Quantification in Deep Learning Models for Brain Tumor Segmentation\nWhile the use of deep learning (DL) models in healthcare has grown rapidly in recent years\, the uncertainty/confidence information in their predictions is often unavailable and unreported. A lack of such information can render decision-making dangerous\, and prompt clinicians to hesitate in using and trusting these machine learning technologies. We propose to adopt principles and computational methods of uncertainty quantification for medical artificial intelligence applications\, focusing on a problem of brain tumor segmentation from MRI scans. As a first step\, we assess the robustness and sensitivity of two such DL models\, U-Net and SqueezeU-Net\, with respect to uncertainty in model weights\, which may arise due to sparsity and noise in training data features as well as labels. We achieve this through Monte Carlo uncertainty propagation of noise injected on trained weight values. The resulting uncertainty of segmentation maps can then be presented and visualized through robustness maps and summarizing box-plots of the Dice coefficients\, which can help indicate the regions where our models do not predict well and most susceptible to training noise. In our on-going work\, we seek to compute the Bayesian posterior distributions for the weights directly from training data. However\, performing a full-scale inference for the millions of weights in U-Net and SqueezeU-Net would be prohibitive. Instead\, we develop a procedure to use sensitivity analysis to identify the most important subset of weights (or layers)\, and perform a targeted Bayesian inference on this lower-dimensional parameter space. \n\nMonica Valluri\nResearch Professor of Astronomy\nUniversity of Michigan\nProbing the nature of dark matter by modeling the Milky Way\nDespite nearly four decades of research in astrophysics and particle physics\, the nature of dark matter\, the substance that comprises 85% of the matter in the universe\, is unknown. The shape of the Milky Way’s dark matter distribution and the variation of this shape with radius are important probes of the nature of dark matter. Mapping the detailed formation history of the Milky Way\, especially the number of satellites that were assimilated by our Galaxy and their masses and their time of infall will provide clues to the dark matter distribution in satellites as well as evidence for nearby streams and dark matter satellites. We are developing a multi-pronged approach to understanding the nature of dark matter with new dynamical tools\, new simulations and analysis of large cosmological simuations. I will describe progress on our efforts to enhance the galactic dynamics package AGAMA (Vasiliev\, 2019)by adding GPU acceleration for the potential and action solvers. I will provide an update on how we are using positions and velocities for old stars in the Milky Way’s halo to determine the three dimensional shape of the dark matter distribution and its variation with radius.I will describe new simulations of the evolution of satellites that merge with our Milky Way that can lead to insights into the fundamental nature of dark matter. Finally I will descibe the use of two cluster finding tools (a self organizing mapping and multi-dimensional density estimation)\, that when applied to action-space properties of stars in the Milky Way’s halo\, can yield insights into the accretion history of our Galaxy. This concert of efforts will significantly advance our goal of understanding the fundamental nature of dark matter using the properties of stars in the Milky Way.
URL:https://micde.umich.edu/event/catalyst-grants-webinar-session-2/
CATEGORIES:Featured Events
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200409T100000
DTEND;TZID=America/Detroit:20200409T113000
DTSTAMP:20260605T112455
CREATED:20230905T171344Z
LAST-MODIFIED:20230905T171344Z
UID:10000356-1586426400-1586431800@micde.umich.edu
SUMMARY:Webinar: 2020 MICDE Catalyst Grants Showcase - Session I
DESCRIPTION:This webinar will showcase some of the game-changing research supported by our Catalyst Grants program. \nThis event was recorded and will be on the UM Youtube channel shortly. \nSpeakers\n \nRobert Krasny\nProfessor of Applied Mathematics and Mathematics\nUniversity of Michigan\nINTEGRAL EQUATION BASED METHODS FOR SCIENTIFIC COMPUTING\nThere are several different approaches to the numerical solution of partial differential equations. For example\, finite-difference methods and finite-element methods discretize either the strong form or the weak form of the equation in real space\, while spectral methods discretize the equation in reciprocal space. This project employs an alternative method which converts the differential equation into an integral equation by convolution with the Green’s function\, followed by discretization and linear solution; the hope is that this approach is more amenable to adaptive refinement and parallelization than other methods. In the past\, integral equation based methods were hindered by the difficulty of discretizing singular integrals and the cost of computing dense matrix-vector products\, but these obstacles are being brought under control. We present our recent work in this area including (1) a GPU-accelerated barycentric treecode for long-range particle interactions\, (2) applications in electrostatics\, electronic structure\, and vortex dynamics. \n\nVikram Gavini\nProfessor of Mechanical Engineering\nUniversity of Michigan\nLong time-scale simulations using exponential time-propagators\nHigh-fidelity long-time scale simulations have been a challenge in a wide range of areas\, including time-dependent electronic structure calculations and molecular dynamics. In particular\, time-dependent density functional theory (TDDFT) calculations are limited to time-scales of the order of hundred femtoseconds\, and MD simulations (even those based on interatomic potentials) are routinely limited to time-scales of the order of nanoseconds. However\, there is very rich material phenomena\, both at the quantum and atomistic scale\, that occurs at time-scales that are orders of magnitude larger than the currently accessible range. In this talk\, I will present the ideas we have been exploring as part of the MICDE catalyst grant to enable long time-scale simulations on a class of time-dependent problems. In particular\, we investigate the use of exponential time-propagators as an alternative to the finite-difference based time-discretization of the PDEs. The ideas will be presented for time-dependent density functional theory and elastodynamics—as a prototypical problem for molecular dynamics—along with numerical results demonstrating the viability and computational efficiency of the proposed ideas. \nThis is joint work with Bikash Kanungo and Paavai Pari. \n\n \nYulin Pan\nAssistant Professor of Naval Architecture and Marine Engineering\nUniversity of Michigan\nReal-Time Phase-resolved ocean wave forecast with data assimilation enabled by gpu-accelerated computation\nThe real-time phase-resolved prediction of ocean waves is crucial for the safety of offshore operations. With the development of the remote sensing technology\, it is now possible to reconstruct the phase-resolved ocean surface from radar measurements in real time. Using the reconstructed ocean surface as initial condition\, nonlinear wave models such as the high-order spectral (HOS) method can be applied to predict the evolution of the ocean waves. However\, the computations reply heavily on large CPU clusters which are usually not available in the offshore onboard environment\, and the prediction can deviate quickly from the true wave evolution due to the chaotic nature of the nonlinear wave equations. To address these problems\, we develop a novel GPU-accelerated computational framework\, which features the coupling of HOS and an ensemble Kalman filter (EnKF) to reduce the uncertainties in the prediction. The new framework algorithm is tested and validated using both synthetic and real wave data\, and is shown promising in fundamentally improving the real-time prediction capability of ocean waves.
URL:https://micde.umich.edu/event/catalyst-grants-webinar-session-1/
CATEGORIES:Featured Events,Webinar
ATTACH;FMTTYPE=image/jpeg:https://micde.umich.edu/wp-content/uploads/2023/02/jzelner-e1584116599101.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200406T150000
DTEND;TZID=America/Detroit:20200406T170000
DTSTAMP:20260605T112455
CREATED:20230905T171344Z
LAST-MODIFIED:20230905T171344Z
UID:10000340-1586185200-1586192400@micde.umich.edu
SUMMARY:Mediation analysis in Python
DESCRIPTION:This session will be held online\, and presenters will be in touch with more information after you register. \n  \nMediation analysis is a set of tools for exploring hypotheses about causal pathways\, with a special focus on differentiating “direct” from “mediated” associations between an exposure and an outcome.  Many approaches to mediation analysis are based on regression analysis. In this workshop\, we will cover some of the basic ideas behind regression-based mediation analysis\, and show how this type of analysis can be performed in Python using the Statsmodels package.  All software tools covered in this workshop are free and open source.
URL:https://micde.umich.edu/event/mediation-analysis-in-python-3/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200402T140000
DTEND;TZID=America/Detroit:20200402T170000
DTSTAMP:20260605T112455
CREATED:20230905T171345Z
LAST-MODIFIED:20230905T171345Z
UID:10000353-1585836000-1585846800@micde.umich.edu
SUMMARY:GIS analysis in R
DESCRIPTION:This session will be held online\, and presenters will be in touch with more information after you register. \n  \nR is a popular open source programming environment for statistics and data science. However\, it has also gradually become very powerful for GIS and spatial data science. \nThis workshop will help you learn about the tools and techniques available in R\, primarily for vector data analysis. Participants should register with the Census and get a census API key (https://api.census.gov/data/key_signup.html).
URL:https://micde.umich.edu/event/gis-analysis-in-r/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200330T130000
DTEND;TZID=America/Detroit:20200330T160000
DTSTAMP:20260605T112455
CREATED:20230905T171342Z
LAST-MODIFIED:20230905T171342Z
UID:10000303-1585573200-1585584000@micde.umich.edu
SUMMARY:Data Visualization With 3D Graphics Using Unity3D and C#
DESCRIPTION:This session will be held online\, and presenters will be in touch with more information after you register. \n  \nVideo game development is more accessible than ever before thanks to modern software tools\, with many options free to download. These tools are also used to program more “serious” applications that require interactive 3D graphics\, from mobile apps\, virtual and augmented reality\, computer vision and artificial intelligence\, and real-time CGI film production.  \n  \nUnity3D is a powerful and popular game engine for both hobbyist and professional projects\, able to compile a ‘game’ to almost any computer platform\, and free to download for non-commercial use. This workshop will show how you can use it to render data from research projects in a 3D interactive representation for user analysis and demonstration. \n  \nIn this workshop\, we introduce the Unity3D workspace\, and prepare a demo that allows the user to load an example dataset and view it as a simple set of 3D representations. A basic familiarity with any computer programming language (C# will be used during the session) is recommended to get the most out of the workshop. To take part\, users will be responsible to bring their own laptop with Unity3D (available for Windows\, Macintosh and Linux) pre-installed. Additional project files will be provided to registered users ahead of the workshop date.
URL:https://micde.umich.edu/event/data-visualization-with-3d-graphics-using-unity3d-and-c-2/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200326T160000
DTEND;TZID=America/Detroit:20200326T170000
DTSTAMP:20260605T112455
CREATED:20230905T171342Z
LAST-MODIFIED:20230905T171342Z
UID:10000352-1585238400-1585242000@micde.umich.edu
SUMMARY:POSTPONED - MICDE/EEB Seminar: Yun Song\, Professor\, Computer Science and Statistics\, University of California\, Berkeley
DESCRIPTION:Bio: Yun S. Song is a professor of EECS and Statistics. He received the BS degrees in mathematics and physics from MIT\, and a PhD in physics from Stanford University. After his PhD\, he spent a year at the Mathematical Institute at the University of Oxford\, where he decided to change fields. He became a postdoctoral researcher in the Department of Statistics at Oxford\, and started doing research in computational biology and mathematical population genetics. From 2004 to 2007\, he was a postdoctoral researcher at UC Davis in the Department of Computer Science\, and the Section of Evolution and Ecology. \nThe key parameters that govern translation efficiency\nTranslation of mRNA into protein is a fundamental biological process mediated by the flow of ribosomes on mRNA transcripts.  With multiple factors that can potentially affect its efficiency\, this transport process is highly complex and heterogeneous: different mRNAs can have different initiation rates\, local elongation rates can vary substantially along the mRNA\, and multiple ribosomes can simultaneously translate the same mRNA\, potentially leading to interference.  In this talk\, I will present new theoretical results on a probabilistic model of mRNA translation which allowed us to identify the key parameters that govern the overall rate of protein synthesis\, sensitivity to initiation rate changes\, and efficiency of ribosome usage.  I will then describe our ongoing study\, which combines in vitro translation experiments with mathematical modeling\, to elucidate the role of the 5′ UTR (particularly uAUGs and uORFs) in regulating translation initiation in eukaryotes.
URL:https://micde.umich.edu/event/micde-seminar-yun-song/
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2021/08/Yun-S.-Song.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200325T100000
DTEND;TZID=America/Detroit:20200325T120000
DTSTAMP:20260605T112455
CREATED:20230905T171343Z
LAST-MODIFIED:20230905T171343Z
UID:10000344-1585130400-1585137600@micde.umich.edu
SUMMARY:Building software projects: CMake is more than a build tool
DESCRIPTION:This workshop is a continuation of the previous workshop “Building software projects: use CMake to build the building plan”.  In this workshop\, we will see that CMake is not just a fancy Makefile generator: it can help us to test\, reuse\, and distribute our software!  We will use CMake to build two interdependent multi-language projects\, and demonstrate how to invoke unit tests after the build\, how to make our code discoverable and reusable by other software developers\, and how to create a distributable package.  If you intend to distribute your software to other research groups\, or if you expect that your project will grow beyond a few files of code and a few months of use — this workshop is for you! \nParticipants will need to have laptops with WiFi connection if they wish to follow the hands-on exercises.  A basic knowledge of Unix-like operating systems would be helpful in following and understanding the material\, but is not required.
URL:https://micde.umich.edu/event/building-software-projects-cmake-is-more-than-a-build-tool/
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:20200324T100000
DTEND;TZID=America/Detroit:20200324T120000
DTSTAMP:20260605T112455
CREATED:20230905T171343Z
LAST-MODIFIED:20230905T171343Z
UID:10000317-1585044000-1585051200@micde.umich.edu
SUMMARY:Introduction to Deep Neural Networks with Keras/TensorFlow
DESCRIPTION:Deep Neural Networks (DNNs) are used as a machine learning method for both regression and classification problems. Keras is a high-level\, Python interface running on top of multiple neural network libraries\, including the popular library TensorFlow. In this workshop\, participants will learn how to quickly use the Keras interface to perform nonlinear regression and classification with standard fully-connected DNNs\, as well as image classification using Convolutional Neural Networks (CNNs). We will also look at regularization techniques and how to deal with under- and over-fitting. All examples will use Python; some familiarity with Python is recommended. Computers will be available to complete exercises. We will run the models using Google Colab\, which requires a Google account.
URL:https://micde.umich.edu/event/3601/
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200323T150000
DTEND;TZID=America/Detroit:20200323T170000
DTSTAMP:20260605T112455
CREATED:20230905T171343Z
LAST-MODIFIED:20230905T171343Z
UID:10000339-1584975600-1584982800@micde.umich.edu
SUMMARY:Go for data processing Part 2
DESCRIPTION:This is a two-session workshop on the use of Go for data processing.  Go is an open source language developed for general-purpose programming.  It is not more difficult to learn and use than a high-level scripting language like Python\, but it is strongly typed\, statically compiled\, and provides native support for concurrency\, leading to much better performance for many common tasks.  In this series of workshops\, we introduce Go as a tool for data processing. No prior exposure to Go is expected\, but participants should have some programming background. Free and open source tools for Go are available for all common platforms.   \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/go-for-data-processing-part-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:20200320T150000
DTEND;TZID=America/Detroit:20200320T160000
DTSTAMP:20260605T112455
CREATED:20230905T171343Z
LAST-MODIFIED:20230905T171343Z
UID:10000351-1584716400-1584720000@micde.umich.edu
SUMMARY:POSTPONED - MICDE/AIM Seminar: John Harlim\, Professor\, Mathematics and Meteorology\, Penn State University
DESCRIPTION:Bio: John Harlim is a Professor in the Department of Mathematics and the Department of Meteorology and Atmospheric Sciences. Harlim received his undergraduate degree in Mathematics from the Universitas Padjadaran (Indonesia)\, a master’s from the University of Guelph in Applied Mathematics\, and a PhD in Applied Mathematics and Scientific Computation from the University of Maryland at College Park. His research interests in applied mathematics include parameter estimation\, machine learning\, manifold learning\, operator estimation\, data assimilation. \n Learning Missing Dynamics through Data\nThe recent success of machine learning has drawn tremendous interest in applied mathematics and scientific computations. In this talk\, I would address the classical closure problem that is also known as model error\, missing dynamics\, or reduced-order-modeling in various community. Particularly\, I will discuss a general framework to compensate for the model error. The proposed framework reformulates the model error problem into a supervised learning task to approximate a very high-dimensional target function involving the Mori-Zwanzig representation of projected dynamical systems. Connection to traditional parametric approaches will be clarified as specifying the appropriate hypothesis space for the target function. Theoretical convergence and numerical demonstration on modeling problems arising from PDE’s will be discussed.
URL:https://micde.umich.edu/event/micde-seminar-john-harlim-psu/
CATEGORIES:Featured Events,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2020/03/John-Harlim.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200319T140000
DTEND;TZID=America/Detroit:20200319T160000
DTSTAMP:20260605T112455
CREATED:20230905T171343Z
LAST-MODIFIED:20230905T171343Z
UID:10000324-1584626400-1584633600@micde.umich.edu
SUMMARY:Machine Learning in R
DESCRIPTION:In this workshop\, we’ll first discuss core machine learning concepts such as: choosing loss functions and evaluation metrics; splitting the data into training\, validation\, and testing sets; and cross-validation patterns for tuning hyper-parameters. Next\, we’ll apply these concepts to train models for identifying isolated letters from speech (https://archive.ics.uci.edu/ml/datasets/isolet). \nSpecifically\, we’ll apply the elastic net (a generalization of ridge and lasso regression)\, random forests\, and gradient boosting to this task.  We’ll briefly discuss each model/method but our primary focus will be on understanding the core functionality of the related R packages (glmnet\, randomForests\, xgboost) and tuning associated hyper-parameters.
URL:https://micde.umich.edu/event/machine-learning-in-r/
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200316T150000
DTEND;TZID=America/Detroit:20200316T170000
DTSTAMP:20260605T112455
CREATED:20230905T171343Z
LAST-MODIFIED:20230905T171343Z
UID:10000338-1584370800-1584378000@micde.umich.edu
SUMMARY:Go for data processing Part 1
DESCRIPTION:This is a two-session workshop on the use of Go for data processing.  Go is an open source language developed for general-purpose programming.  It is not more difficult to learn and use than a high-level scripting language like Python\, but it is strongly typed\, statically compiled\, and provides native support for concurrency\, leading to much better performance for many common tasks.  In this series of workshops\, we introduce Go as a tool for data processing. No prior exposure to Go is expected\, but participants should have some programming background. Free and open source tools for Go are available for all common platforms.   \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/go-for-data-processing-part-1/
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:20200313T150000
DTEND;TZID=America/Detroit:20200313T160000
DTSTAMP:20260605T112455
CREATED:20230905T171343Z
LAST-MODIFIED:20230905T171343Z
UID:10000009-1584111600-1584115200@micde.umich.edu
SUMMARY:MICDE Seminar: Demetrios Papageorgiou\, Professor\, Applied Mathematics\, Imperial College London
DESCRIPTION:POSTPONED UNTIL FURTHER NOTICE\nBio: Demetrious Papageorgiou is a Professor at Imperial College London.  He is an applied mathematician that works on problems that arise in fluid dynamics. He is interested in systems involving immiscible fluids that are characterized by the presence of spatiotemporally evolving sharp interfaces.  \nElectric field effects in immiscible multilayer flows\nMultilayer flows such as falling films and coating flows\, or pressure-driven flows of immiscible fluids in channels and pipes\, are fundamental in applications. Such flows are typically stable if they are slow enough (highly viscous). Such regimes arise in small-scale geometries (e.g. microfluidics)\, and electric fields can be used to drive the system out of equilibrium to produce patterning\, mixing and phase separation. \nI will begin with some experiments and direct numerical simulations (DNS) that show how electric fields can be utilized in their dual role of inducing instabilities or stability depending on geometry and orientation. I will then review the theoretical models underpinning such phenomena and will use asymptotic theories to derive and study reduced-dimension model equations that describe nonlinear interfacial waves in the presence of fields. Computations predict rich dynamics including spatiotemporal chaos and singularity formation. Some novel inertialess nonlinear interfacial instabilities will also be described – these arise due to flux functions of derived evolution equations changing type from hyperbolic to elliptic. Finally\, I will present results on the use of electric fields and/or blowing suction in achieving feedback and optimal control of falling film flows. Comparisons with DNS will be made and these will be used beyond the range of validity of asymptotic models to predict phenomena such as electrostatic suppression of Rayleigh-Taylor instabilities\, and electrostatically induced pumping in microchannels. \nThis seminar is co-sponsored by the Applied & Interdisciplinary Mathematics program. Prof. Papageorgiou is being hosted by Prof. Krasny (MATH).
URL:https://micde.umich.edu/event/fall2019-papageorgiou-imperialcollege/
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/jpeg:https://micde.umich.edu/wp-content/uploads/2023/02/portrait.jpg
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END:VCALENDAR