Events

  • SC2 Workshop Series: QGIS – Visualizing Geospatial Data

    Modern Languages Building (MLB), Room 2001A

    QGIS is a user friendly Open Source Geographic Information System (GIS). You can visualize, manage, edit, analyze data, and compose printable maps. The workshop will use R. This workshop is part of the Scientific Computing Student Club’s (SC2) 2020 Visualization Challenge. It is the second workshop in the series. Learn more about the workshop series and the Visualization […]

    Programming with R

    Modern Languages Building (MLB), Room 2001A

    People using R for applied research are often not taught basic programming practices such as writing functions, efficient iterative processing, vectorization, and other practices that would make their research far more efficient and reproducible.  Understandably, focus is on basic data manipulation and getting model results.  Unfortunately, this can mean the data isn’t as explored as it should […]

    Rcpp: Integrating C++ into R

    Modern Languages Building (MLB), Room 2001A

    The Rcpp package for R provides “seamless R and C++ integration”.  In this workshop, we will discuss the use of Rcpp to speed up existing R code by rewriting slow functions in C++.   The workshop will be centered around a couple of case studies with an opportunity provided for participants to implement a few of their […]

    Research Computing on the Great Lakes Cluster

    Modern Languages Building (MLB), Room 2001A

    OVERVIEW This 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 […]

  • SC2 Workshop Series: Data Processing and Visualizations with R and Python

    Modern Languages Building (MLB), Room 2001A

    This workshop will provide some tools, tips, and packages that make data processing and visualization in R easier. Some coding experience is required – not necessarily R. Instructor: Dr. Michael Clark, Consultant, Consulting for Statistics, Computing and Analytic Research (CSCAR) Space is limited. Learn more and register here.

    Anna Vainchtein

    MICDE Seminar: Anna Vainchtein, Professor, Mathematics, University of Pittsburgh

    1084 East Hall 530 Church St., Ann Arbor, MI, United States

    Bio: Anna Vainchtein is a professor in the Department of Mathematics at the University of Pittsburgh. She is generally interested in mathematical modeling and analysis of nonlinear phenomena in materials science, physics and biology. Examples include dynamics of phase boundaries, cracks and dislocations in crystals, hysteresis in phase-transforming materials, solitary and heteroclinic traveling waves in nonlinear […]

    Bo Zhu

    MICDE Seminar: Bo Zhu, Assistant Professor, Computer Science, Dartmouth College

    1303 EECS 1301 Beal Ave, Ann Arbor, MI, United States

    Bio: Bo Zhu is an assistant professor of Computer Science at Dartmouth College. Prior to that, he was a postdoctoral associate at MIT CSAIL. He received his Ph.D. in Computer Science from Stanford University in 2015. His research interests encompass computer graphics, computational physics, and computational fabrication. In particular, he focuses on building computational approaches […]

    Intro to D3.js for data visualization

    Modern Languages Building (MLB), Room 2001A

    D3.js is a JavaScript library for producing dynamic, interactive data visualizations in web browsers. It makes use of the widely implemented SVG, HTML5, and CSS standards. We’ll explore how to get started with D3 and the anatomy of a basic D3 plot with animation using a top-down approach. We’ll be using the baseball chart at […]

  • MICDE Seminar: Grace Gu, Assistant Professor, Mechanical Engineering, University of California, Berkeley

    Venue TBA MI, United States

    Bio: Research interests: Composites, additive manufacturing, fracture mechanics, topology optimization, machine learning, finite element analysis, and bioinspired materials. SEMINAR TITLE Abstract Prof. Xu is being hosted by Prof. XXX.  If you would like to meet with her during her visit, please send an email to [email protected]. If you are an MICDE and would like to […]

    Introduction to Deep Neural Networks with Keras/TensorFlow

    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 […]