New on-campus data-science and computational research services available

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Researchers across campus now have access to several new services to help them navigate the new tools and methodologies emerging for data-intensive and computational research.

As part of the U-M Data Science Initiative announced in fall 2015, Consulting for Statistics, Computing and Analytics Research (CSCAR) is offering new and expanded services, including guidance on:

  • Research methodology for data science.
  • Large scale data processing using high performance computing systems.
  • Optimization of code and use of Flux and other advanced computing systems.
  • Advanced data management.
  • Geospatial data analyses.
  • Exploratory analysis and data visualization.
  • Obtaining licensed data from commercial sources.
  • Scraping, aggregating and integrating data from public sources.
  • Analysis of restricted data.

“With Big Data and computational simulations playing an ever-larger role in research in a variety of fields, it’s increasingly important to provide researchers with a comprehensive ecosystem of support and services that address those methodologies,” said CSCAR Director Kerby Shedden.

As part of this significant expansion of its scope, the campuswide statistical consulting service CSCAR has been renamed Consulting for Statistics, Computing and Analytics Research. It was formerly known as the Center for Statistical Consultation and Research.

For more information, see the University Record article.

New graduate course offering: “Methods and Practice of Scientific Computing”

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The Michigan Institute for Computational Discovery and Engineering (MICDE) is pleased to announce “Methods and Practice of Scientific Computing”, the first graduate course designed and organized by MICDE faculty. The course will be taught in Fall 2016, coordinated by Dr. Brendan Kochunas. This foundational course in scientific computing has been developed as a broad introduction to the subject, and has been designed to support research in all disciplines represented in MICDE. In addition to Brendan Kochunas, the course was developed by MICDE professors Bill Martin, Karthik Duraisamy, Vikram Gavini, and Shravan Veerapaneni, and MICDE Assistant Director Mariana Carrasco-Teja.

The details follow:

NERS 590
4 credits
Prerequisites: Graduate standing and permission of instructor.

This course is designed for graduate students who are developing the methods, and using the tools, of scientific computing in their research. With the increased power and availability of computers to do massively scaled simulations, computational science and engineering as a whole has become an integral part of research that complements experiment and theory. This course will teach students the necessary skills to be effective computational scientists and how to produce work that adheres to the scientific method. A broad range of topics will be covered including: software engineering best practices, computer architectures, computational performance, common algorithms in engineering, solvers, software libraries for scientific computing, uncertainty quantification, verification and validation, and how to use all the various tools to accomplish these things. The class will have lecture twice a week and have an accompanying lab component. Students will be graded on homeworks, lab assignments, and a course project.

A draft of the syllabus can be found here. Please contact MICDE at micde-contact@umich.edu with any questions.

Krishna Garikipati appointed Director of MICDE

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Statement from S. Jack Hu, U-M Vice President for Research:

krishnaGarikipatiI’m very pleased to announce that Prof. Krishna Garikipati (Mechanical Engineering and Mathematics) has been appointed the new Director of the Michigan Institute for Computational Discovery and Engineering (MICDE). The Institute has grown significantly since its establishment in 2013 as the interdisciplinary home for the development and use of mathematical algorithms on high performance computers at U-M. Prof. Garikipati has been involved as associate director for research since Fall 2014 and is uniquely positioned to take the institute to the next level.

MICDE is a joint initiative of UMOR, the College of Engineering, and the College of Literature, Science and the Arts. In the past year, it has seen many new and important developments, including the launching of two centers focused on network and storage-enabled collaborative science and data-driven computational physics; new planned course offerings for the PhD in Scientific Computing and the Graduate Certificate in CDE; new initiatives on industrial engagement; and the establishment of the Scientific Computing Student Club. A number of new research initiatives are also being planned, with broadening participation of MICDE-affiliated faculty, whose numbers continue to grow.

Prof. Garikipati will take over the directorship of MICDE from Prof. Eric Michielssen (EECS) who founded the institute in Fall 2013 and served as director, in addition to his role as Associate Vice President for Advanced Research Computing. Prof. Michielssen will continue as AVP.

Software Carpentry workshop at U-M — May 2-3

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A Software Carpentry workshop will be held at the U-M Medical School May 2 and 3. These workshops are free and open to anyone on campus; the sessions are suitable for researchers in the humanities and social sciences. Register here.

This hands-on workshop will cover basic concepts and tools, including program design, version control, data management, and task automation. Participants will be encouraged to help one another and to apply what they have learned to their own research problems.

Who: The course is aimed at graduate students, postdocs, and other researchers across the University of Michigan. You don’t need to have any previous knowledge of the tools that will be presented at the workshop.

Where: Furstenberg 2710 (2nd floor of Med Sci II).

Path modeling of chronic kidney disease

Path modeling

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Diabetes, hypertension, and chronic kidney disease (CKD) commonly co-occur within individuals. A team of University of Michigan and external researchers including CSCAR consultant Brady West recently demonstrated that periodontal disease may also play an important role in this comorbid system.

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Analysis of neuroimaging data

Analysis of neuroimaging data

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Magnetoencephalography (MEG) is a form of neuroimaging that can be used to assess activity in various brain regions. Working with researchers from the University of Michigan Department of Psychiatry, CSCAR consultant Dave Childers used spectral coherence analysis to examine connections between pairs of brain regions.

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