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X-WR-CALDESC:Events for Michigan Institute for Computational Discovery and Engineering
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DTSTART;TZID=America/Detroit:20190416T140000
DTEND;TZID=America/Detroit:20190416T160000
DTSTAMP:20260606T073446
CREATED:20230905T171359Z
LAST-MODIFIED:20230905T171359Z
UID:10000215-1555423200-1555430400@micde.umich.edu
SUMMARY:Statistical analysis with missing data in Python
DESCRIPTION:Missing 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.    \nThe 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/
LOCATION:Rackham Building\, Earl Lewis Room\, 3rd Floor East\, 915 E. Washington St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Workshops
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190416T093000
DTEND;TZID=America/Detroit:20190416T120000
DTSTAMP:20260606T073446
CREATED:20230905T171359Z
LAST-MODIFIED:20230905T171359Z
UID:10000101-1555407000-1555416000@micde.umich.edu
SUMMARY:Web Scraping with Python
DESCRIPTION:This workshop will provide an overview of how to scrape data from html pages and website APIs using Python. This will mostly be accomplished using the requests\, beautifulsoup\, retry modules and the browser developer tools. The workshop is intended for users with basic Python knowledge. Anaconda Python 3.5 will be used.
URL:https://micde.umich.edu/event/web-scraping-with-python-3-2-2/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190412T133000
DTEND;TZID=America/Detroit:20190412T170000
DTSTAMP:20260606T073446
CREATED:20230905T171359Z
LAST-MODIFIED:20230905T171359Z
UID:10000189-1555075800-1555088400@micde.umich.edu
SUMMARY:Open Source GIS and Geometric Network Analysis
DESCRIPTION:This workshop will cover GIS concepts and techniques for analyzing geometric networks embedded in geographical space. We will mainly focus on road network\, but the ideas and techniques apply to similar network such as water and electric distribution and gas pipelines. We will primarily use open source tools in R and QGIS\, but will also touch upon the functionalities in ArcGIS. \nYou should know the introductory concepts and tools in GIS and should be familiar with R and QGIS.
URL:https://micde.umich.edu/event/open-source-gis-and-geometric-network-analysis/
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
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190410T080000
DTEND;TZID=America/Detroit:20190410T170000
DTSTAMP:20260606T073446
CREATED:20230905T171359Z
LAST-MODIFIED:20230905T171359Z
UID:10000141-1554883200-1554915600@micde.umich.edu
SUMMARY:The 2019 MICDE Symposium
DESCRIPTION:[vc_row type=”in_container” full_screen_row_position=”middle” scene_position=”center” text_color=”dark” text_align=”left” overlay_strength=”0.3″ shape_divider_position=”bottom” bg_image_animation=”none”][vc_column column_padding=”no-extra-padding” column_padding_position=”all” background_color_opacity=”1″ background_hover_color_opacity=”1″ column_link_target=”_self” column_shadow=”none” column_border_radius=”none” width=”1/1″ tablet_width_inherit=”default” tablet_text_alignment=”default” phone_text_alignment=”default” column_border_width=”none” column_border_style=”solid” bg_image_animation=”none”][vc_column_text]The Michigan Institute for Computational Discovery and Engineering 2019 Symposium will feature eminent scientists from around the world and the U-M campus. \n\n\nSPEAKERS\n\n\n\n\n\n\n\n\n\n\nMarsha Berger\nProfessor\, Computer Science and Mathematics\nNew York University Courant Institute of Mathematical Sciences \n\nMarisa Eisenberg\nAssociate Professor\, Epidemiology and Mathematics\nUniversity of Michigan \n\nCarla Gomes\nProfessor and Director\, Institute for Computational Sustainability\nCornell University \n\nJan Hesthaven\nDean\, School of Basic Sciences\nEPFL\, Switzerland \n\nNecmiye Ozay\nAssistant Professor\, Electrical Engineering and Computer Science\nUniversity of Michigan \n\nStephen Wolfram\nFounder and CEO\, Wolfram Research\nCreator of Mathematica \n\n\n\n\n\n\n\nA poster competition will be held\, open to post-docs and graduate students. \nMore information will be posted here as it becomes available. Also see micde.umich.edu/symposium19[/vc_column_text][/vc_column][/vc_row]
URL:https://micde.umich.edu/event/the-2019-micde-symposium/
LOCATION:Michigan League\, 911 N. University\, Ann Arbor\, MI\, 48104\, United States
CATEGORIES:Featured Events,Seminar
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190409T140000
DTEND;TZID=America/Detroit:20190409T160000
DTSTAMP:20260606T073446
CREATED:20230905T171359Z
LAST-MODIFIED:20230905T171359Z
UID:10000214-1554818400-1554825600@micde.umich.edu
SUMMARY:Mediation analysis in Python
DESCRIPTION:Mediation 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. \n 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-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
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190404T120000
DTEND;TZID=America/Detroit:20190404T130000
DTSTAMP:20260606T073446
CREATED:20230905T171359Z
LAST-MODIFIED:20230905T171359Z
UID:10000220-1554379200-1554382800@micde.umich.edu
SUMMARY:MICDE Seminar: Prith Banerjee\, Chief Technology Officer\, ANSYS\, Inc.
DESCRIPTION:Bio: Prith Banerjee is the Chief Technology Officer of ANSYS where he is responsible for leading the evolution of ANSYS’ Technology strategy and champion the company’s next phase of innovation and growth. He also serves on the Board of Directors of Cray\, Inc. and Cubic Corporation. Previously he used to be Senior Client Partner at Korn Ferry where he was responsible for IOT and Digital Transformation in the Global Industrial Practice. Formerly\, he was Executive Vice President\, Chief Technology Officer of Schneider Electric. Previously\, he was Managing Director of Global Technology Research and Development at Accenture. Formerly\, he was Chief Technology Officer and Executive Vice President of ABB. Earlier\, he was Senior Vice President of Research at HP and Director of HP Labs. Formerly\, he was Dean of the College of Engineering at the University of Illinois at Chicago. Formerly\, he was the Walter P. Murphy Professor and Chairman of Electrical and Computer Engineering at Northwestern University. Prior to that\, he was Professor of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign. In 2000\, he founded AccelChip\, a developer of products for electronic design automation\, which was acquired by Xilinx Inc. in 2006. During 2005-2011\, he was Founder\, Chairman and Chief Scientist of BINACHIP Inc.\, a developer of products in electronic design automation. He was listed in the FastCompany list of 100 top business leaders in 2009. He is a Fellow of the AAAS\, ACM and IEEE\, and a recipient of the 1996 ASEE Terman Award and the 1987 NSF Presidential Young Investigator Award. He received a B.Tech. in electronics engineering from the Indian Institute of Technology\, Kharagpur\, and an M.S. and Ph.D. in electrical engineering from the University of Illinois\, Urbana. \nFUTURE OF SIMULATION-BASED PRODUCT INNOVATION IN THE DIGITAL WORLD\nDigital transformation refers to the use of digital technologies such as cloud\, IOT\, AI/ML\, to transform the way business is executed. Digital transformation is impacting every industry – automotive\, agriculture\, logistics\, healthcare and manufacturing. In this talk we will discuss how Digital Transformation is disrupting the manufacturing industry. In the past\, engineered products were designed with mechanical and electrical CAD tools\, simulated and validated for correctness with CAE tools\, prototypes were fabricated and tested\, and products were then manufactured at scale in factories. This process required long product cycles often requiring years to build a new product. Today\, one can use unlimited computing and storage available from the cloud to do generative design to explore 10\,000 design choices in near real-time\, verify these products accurately through simulation (eliminating the need to build physical prototypes) and manufacture the products using additive manufacturing and factory automation (Industrie 4.0). In the past\, simulation tools were used to model specific physics such as mechanical structures\, or fluid dynamics\, or electromagnetic interactions by solving second order partial differential equations using numerical methods. Today the simulation tools are being used to solve multi-physics problems (fluid-structure-electromagnetics interactions) at scale using the most complex solvers. These products once built are connected using IOT so that manufacturers have 24/7 connectivity to all these products\, and can monitor how customers are using these product; this helps the manufacturers design future generations of products even faster. The connectivity also allows them to monitor the products for failures using predictive analytics\, and service these products remotely. In this talk I will discuss how the ANSYS Pervasive Simulation Platform allows hardware and software developers to work together in all phases of a product development lifecycle including Ideation\, Design Manufacturing\, and Operations. Simulation tools are increasingly being used in the ideation phase by designers to get real-time simulation of the parts as soon as they are being conceptualized. This has resulted in shorter\, agile product cycles even for hardware products allowing innovative products to be designed and produced in months and days. Companies are increasingly using model-based systems engineering concepts to take high level requirements of products\, and manage the complexity of product design using concepts of Digital Threads\, Digital Twins\, and Digital Continuity. We will touch upon some future directions of simulation-based product innovation around AI/Machine Learning\, Multi-physics Platforms\, Hyperscale Simulation\, and the convergence of the Digital and Physical worlds using IOT and Augmented Reality/Virtual Reality.
URL:https://micde.umich.edu/event/prith-banerjee-ansys/
LOCATION:1005 EECS\, 1301 Beal Ave\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2019/03/Prith-Banerjee.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190403T130000
DTEND;TZID=America/Detroit:20190403T160000
DTSTAMP:20260606T073446
CREATED:20230905T171359Z
LAST-MODIFIED:20230905T171359Z
UID:10000218-1554296400-1554307200@micde.umich.edu
SUMMARY:Sliding into Slurm:  An early look at U-M's new high-performance computing environment
DESCRIPTION:This workshop will provide a brief overview of the the new HPC environment and is intended for current Flux and Armis users.  We will use the temporary Beta HPC cluster to demonstrate how jobs will be submitted and managed under the new Great Lakes\, Armis2\, and Lighthouse clusters available later this year. \nThere are many differences between the familiar Flux environment and that of the new HPC clusters\, including a new batch scheduling system\, a new interactive batch job environment\, a new HPC web portal\, a new module environment\, and a new on-demand-only job accounting system. \nWe will cover these differences in the workshop\, and provide hands-on training in creating and running job submission scripts in the new HPC environment.  Students are expected to be conversant with the Linux command line and have experience in creating\, submitting\, and troubleshooting PBS batch scripts.
URL:https://micde.umich.edu/event/sliding-into-slurm-an-early-look-at-u-ms-new-high-performance-computing-environment-2/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:High Performance Computing,Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190402T140000
DTEND;TZID=America/Detroit:20190402T160000
DTSTAMP:20260606T073446
CREATED:20230905T171400Z
LAST-MODIFIED:20230905T171400Z
UID:10000201-1554213600-1554220800@micde.umich.edu
SUMMARY:Go for data processing 1/2/3
DESCRIPTION:This is a three-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. \nSession 1: March 19\, 2:00pm – 4:00pm \nSession 2: March 26\, 2:00pm – 4:00pm \nSession 3: April 2\, 2:00pm – 4:00pm \nNote: Interested participants only need to register with the 1st session. 
URL:https://micde.umich.edu/event/go-for-data-processing-1-2-3-2-2/
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
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190401T153000
DTEND;TZID=America/Detroit:20190401T170000
DTSTAMP:20260606T073446
CREATED:20230905T171400Z
LAST-MODIFIED:20260401T195156Z
UID:10000190-1554132600-1554138000@micde.umich.edu
SUMMARY:Understanding How the Brain Processes Music Through the Bach Trio Sonatas
DESCRIPTION:This event is open to the public. \nDaniel Forger\, Professor of Mathematics and Computational Medicine and Bioinformatics\nJames Kibbie\, Professor of Music and Chair of the Organ Department\, University Organist\nCaleb Mayer\, Graduate Student Research Assistant (Mathematics)\nSarah Simko\, Graduate Student Research Assistant (Organ Performance) \nWith support from the Data Science for Music Challenge Initiative through MIDAS\, the team is taking a big data approach to understanding the patterns and principles of music. The project is developing and analyzing a library of digitized performances of the Trio Sonatas for organ by Johann Sebastian Bach\, applying novel algorithms to study the music structure from a data science perspective. Organ students from the School of Music\, Theatre & Dance will demonstrate how the Frieze Memorial Organ in Hill Auditorium is used to create big data files of live performances. The team will discuss how its analysis compares different performances to determine features that make performances artistic\, as well as the common mistakes performers make. The digitized performances will be shared with researchers and will enable research and pedagogy in many disciplines\, including data science\, music performance\, mathematics and music psychology.
URL:https://micde.umich.edu/event/understanding-how-the-brain-processes-music-through-the-bach-trio-sonatas/
LOCATION:Hill Auditorium\, 825 N University Ave\, Ann Arbor\, MI 48109\, Ann Arbor\, MI\, 48104\, United States
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190326T140000
DTEND;TZID=America/Detroit:20190326T160000
DTSTAMP:20260606T073446
CREATED:20230905T171400Z
LAST-MODIFIED:20230905T171400Z
UID:10000200-1553608800-1553616000@micde.umich.edu
SUMMARY:Go for data processing 1/2/3
DESCRIPTION:This is a three-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. \nSession 1: March 19\, 2:00pm – 4:00pm \nSession 2: March 26\, 2:00pm – 4:00pm \nSession 3: April 2\, 2:00pm – 4:00pm \nNote: Interested participants only need to register with the 1st session. 
URL:https://micde.umich.edu/event/go-for-data-processing-1-2-3-2/
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
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190322T093000
DTEND;TZID=America/Detroit:20190322T160000
DTSTAMP:20260606T073446
CREATED:20230905T171358Z
LAST-MODIFIED:20230905T171358Z
UID:10000077-1553247000-1553270400@micde.umich.edu
SUMMARY:Introduction to Stata
DESCRIPTION:Topics: \n\nBy the end of the workshop\, participants will be able to:\n\nWork with Stata\, including using Do-files and using the help system.\nGet data into Stata and manage your data files\nEstablish familiarity with your data\nClean the data to prepare it for analysis\nCheck for basic errors in the data\nGenerate new variables or manipulate existing variables\nMerge or reshape the data.\nProduce summary tables and descriptive statistics.\n\n\nNote: This is a full day workshop. To get the most out of it\, please plan to stay for the entire class.\n\n(Topics subject to change) \n 
URL:https://micde.umich.edu/event/introduction-to-stata-3-3-2-2/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190320T153000
DTEND;TZID=America/Detroit:20190320T170000
DTSTAMP:20260606T073446
CREATED:20230905T171358Z
LAST-MODIFIED:20230905T171358Z
UID:10000219-1553095800-1553101200@micde.umich.edu
SUMMARY:Doing more with RStudio
DESCRIPTION:This talk will serve as an demonstration of what RStudio can offer for those that do not use it\, as well as a showcase for more advanced use for those who use it only for scripting purposes. \nTopics include but are not limited to: \n\nScripting shortcuts\nCustomization\nUsing Projects\nDocument generation\nAddins\nPackage Development\nDebugging and Profiling\nVersion Control\n\nWhile this is more of a demo than a workshop\, attendees are encouraged to try some things out and explore as we go along. \n If you have questions about this workshop\, please send an email to micl@umich.edu
URL:https://micde.umich.edu/event/doing-more-with-rstudio/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190319T140000
DTEND;TZID=America/Detroit:20190319T160000
DTSTAMP:20260606T073446
CREATED:20230905T171358Z
LAST-MODIFIED:20230905T171358Z
UID:10000199-1553004000-1553011200@micde.umich.edu
SUMMARY:Go for data processing 1/2/3
DESCRIPTION:This is a three-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. \nSession 1: March 19\, 2:00pm – 4:00pm \nSession 2: March 26\, 2:00pm – 4:00pm \nSession 3: April 2\, 2:00pm – 4:00pm \nNote: Interested participants only need to register with the 1st session.
URL:https://micde.umich.edu/event/go-for-data-processing-1-2-3/
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:20190319T100000
DTEND;TZID=America/Detroit:20190319T120000
DTSTAMP:20260606T073446
CREATED:20230905T171358Z
LAST-MODIFIED:20230905T171358Z
UID:10000203-1552989600-1552996800@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-3-2/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190315T093000
DTEND;TZID=America/Detroit:20190315T120000
DTSTAMP:20260606T073446
CREATED:20230905T171358Z
LAST-MODIFIED:20230905T171358Z
UID:10000213-1552642200-1552651200@micde.umich.edu
SUMMARY:Intro to Web Applications using Flask and Python
DESCRIPTION:Ever want to build your own web application? Do you want to do it using Python? Well then\, Flask is the answer you are looking for. Its a micro web framework for Python to help you build your first web app. Come learn how to get started building\, testing and deploying your first app to the web. \nAttendees should be familiar with HTML\, CSS and Python or RShiny. Anaconda Python 3.6 will be used.
URL:https://micde.umich.edu/event/into-to-web-applications-using-flask-and-python/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190314T150000
DTEND;TZID=America/Detroit:20190314T160000
DTSTAMP:20260606T073446
CREATED:20230905T171358Z
LAST-MODIFIED:20230905T171358Z
UID:10000154-1552575600-1552579200@micde.umich.edu
SUMMARY:MICDE Seminar: Narayana R. Aluru\, Professor\, Department of Mechanical Science and Engineering\, Beckman Institute for Advanced Science and Technology\, University of Illinois at Urbana-Champaign
DESCRIPTION:Bio: Professor Aluru studies problems at the crossroads of mechanical engineering\, electrical engineering\, materials science and chemical engineering. His work in the area of microelectromechanical systems (MEMS) and nanoelectromechanical systems (NEMS) revealed previously unknown nonlinear dynamic phenomena\, such as complex oscillations\, period doubling bifurcation to chaos\, and U-sequence. These insights led him to perform fundamental studies on thermoelastic damping in MEMS and to develop a new model to predict thermoelastic damping for complex nonlinear oscillations encountered in NEMS. \nIn another effort\, he developed the first bio-MEMS and microfluidics models for the analysis and design of lab-on-a-chip applications\, as well as mathematical models for pH- and electric field-responsive hydrogels-materials with potential applications in small-scale sensing and actuation. \nProfessor Aluru also studies the unique physics that occur at the nanometer level. He discovered several new physical phenomena through nanofluidics research\, including charge inversion\, flow reversal\, anomalously immobilized water\, asymmetric dependence of fluid and ion transport on surface charge\, and enhanced conductivity in nanopores. His recent investigations of surface diffusion demonstrated that liquid molecules move as much as 30 times faster over a solid surface when that surfaced is only partially covered by such molecules\, and that larger molecules move faster on a partially covered surface than shorter ones do. His other work in nanofluidics includes the multiscale modeling of the transport of water and other ions through membranes\, studying the function of biological channels in the membranes of living cells\, investigating the use of carbon nanotubes to filter pathogens and other toxins out of water\, and exploring the use of carbon and boron nanotubes to speed the removal of salt from water during reverse osmosis. \nCOMPUTATIONAL NANOSCALE HYDRODYNAMICS\nMany applications in biology\, engineering and science rely on efficient hydrodynamic transport through nanometer scale pores and channels. For example\, channels and pores in cellular membranes regulate the functionality of the cell by selectively and efficiently exchanging water and ions between extra and intra cellular environments. Selective pores in ultrathin membranes have been shown to be highly efficient for water desalination and power generation. Classical theories often fail to describe fluid physics at nanometer scale. For example\, density layering\, size dependent fluid properties\, restricted translational and rotational motions\, charge inversion\, flow reversal and several other important phenomena have been observed at nanometer scale. The focus of this talk is to develop efficient theories and computational approaches to accurately describe fluid physics at nanometer scales. First\, we will introduce an empirical potential-based quasi-continuum theory (EQT) to accurately predict the structure of confined fluids. We show that the density layering from EQT matches well with molecular dynamics (MD) and EQT is many orders of magnitude faster compared to MD. Next\, we show that the EQT framework can be combined with the generalized Langevin theory to compute diffusion of confined fluids and with the classical Navier-Stokes equations to compute the transport of confined fluids. We will show several examples to demonstrate the accuracy and efficiency of the quasi-continuum theory for confined fluids. \nProf. Aluru is being hosted Professors Krishna Garikipati and Eric Michielssen. If you would like to meet Prof. Aluru\, please send an email to micde-events@umich.edu. If you are an MICDE student or fellow\, or a post-doc\, and would like to join Prof. Aluru for lunch\, please RSVP here.
URL:https://micde.umich.edu/event/micde-seminar-narayana-aluru-department-of-mechanical-engineering-uicuc/
LOCATION:1005 EECS\, 1301 Beal Ave\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2018/08/Narayana-R.-Aluru.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190314T130000
DTEND;TZID=America/Detroit:20190314T163000
DTSTAMP:20260606T073446
CREATED:20230905T171358Z
LAST-MODIFIED:20230905T171358Z
UID:10000188-1552568400-1552581000@micde.umich.edu
SUMMARY:Open Source GIS
DESCRIPTION:This workshop will cover introductory GIS concepts and techniques using open source tools. We will use QGIS and R and learn the basics of GIS by solving a number of different problems.  You will also learn to generate production quality maps. Some exposure to R will be helpful. \nThe workshop is meant for students and researchers who want to have a quick and simple exposure to GIS concepts and tools.
URL:https://micde.umich.edu/event/open-source-gis-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:20190313T140000
DTEND;TZID=America/Detroit:20190313T163000
DTSTAMP:20260606T073446
CREATED:20230905T171359Z
LAST-MODIFIED:20230905T171359Z
UID:10000212-1552485600-1552494600@micde.umich.edu
SUMMARY:PySpark
DESCRIPTION:Apache Spark is a powerful open source processing engine built around speed\, ease of use\, and sophisticated analytics. Industry has quickly adopted Spark and deployed it at scale for processing big data. Its main advantage include in-memory processing and a rich set of operations for wrangling data using DataFrames. In this workshop\, we’ll introduce attendees to SparkSQL and DataFrames for basic data manipulation\, file I/O and SQL querying. Spark has language bindings to R\, Python\, Scala and Java. We’ll be using PySpark (the Python API) in our workshop. \nThe workshop is intended for users with INTERMEDIATE knowledge of R\, Python\, or comparable language. Attendees should be familiar with DataFrames in Python (pandas) or R (dplyr). Attendees will NEED to have a Cavium account beforehand to participate. http://myumi.ch/6pn5d
URL:https://micde.umich.edu/event/pyspark/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190306T140000
DTEND;TZID=America/Detroit:20190306T170000
DTSTAMP:20260606T073446
CREATED:20230905T171359Z
LAST-MODIFIED:20260401T195302Z
UID:10000187-1551880800-1551891600@micde.umich.edu
SUMMARY:Latent Variable Modeling
DESCRIPTION:Part of the Structural Equation Modeling (SEM) series.  This workshop will help participants develop skills in understanding and conducting latent variable models\, particularly from the perspective of structural equation modeling. After a conceptual overview\, a broad view of matrix factorization techniques will be provided along with specific examples (e.g. PCA\, ‘factor analysis’).  In addition\, measurement error issues\, reliability\, and scale development will be discussed (e.g. ‘confirmatory’ factor analysis). \nPrerequisites: One should have a firm understanding of basic regression. R will be the program of choice\, but nothing beyond very basic skill is assumed (e.g. import data\, run a regression).  Demonstration will be conducted with R\, and the psych and lavaan packages in particular.
URL:https://micde.umich.edu/event/latent-variable-modeling/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190305T083000
DTEND;TZID=America/Detroit:20190305T150000
DTSTAMP:20260606T073446
CREATED:20230905T171359Z
LAST-MODIFIED:20230905T171359Z
UID:10000039-1551774600-1551798000@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-2-2-2-2/2019-03-05/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190304T083000
DTEND;TZID=America/Detroit:20190304T150000
DTSTAMP:20260606T073446
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:20260606T073446
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:20260606T073446
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:20260606T073446
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:20260606T073446
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:20260606T073446
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:20260606T073446
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:20260606T073446
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:20260606T073446
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:20260606T073446
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
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