Inaugural symposium for Michigan Institute for Data Science — Oct. 6

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Top data scientists from around the country will gather in the Rackham Building on Oct. 6 for a symposium to launch the Michigan Institute for Data Science (MIDAS), the centerpiece of the university’s recently announced $100 million investment in data science.

Titled “The Future of Data Science: A Convergence of Academia, Industry and Government,” the symposium will highlight current research across the spectrum of data science and outline faculty opportunities.

A detailed agenda is available here

Click here to register

It also will examine data science challenges in health, learning analytics, social science and transportation; discuss regional, national and international data science initiatives and partnerships; and explore possibilities for collaboration with industry.

“U-M’s strengths in data science are deep and broad. The prospects for leveraging these strengths with new investments that cut across disciplines and methodologies are truly exciting,” said MIDAS co-director Brian Athey, the Michael A. Savageau Collegiate Professor and chair of the Department of Computational Medicine and Bioinformatics.

“The university has shown a strong commitment to data science,” added Alfred Hero, MIDAS co-director and R. Jamison and Betty Williams Professor of Engineering. “We look forward to engaging students, faculty, industry and government in pushing forward research innovations that will benefit many sectors of society.”

The keynote speaker at the symposium will be Daniel Goroff, vice president of the Alfred P. Sloan Foundation, who will speak on “Privacy and Reproducibility in Data Science.” His talk is scheduled for 1:30 p.m.

Other sessions include:

  • U-M leaders, including Provost Martha Pollack, Interim Vice President for Research Jack Hu, Associate Vice President for Advanced Research Computing Eric Michielssen, and Athey and Hero, will present details of the university’s investment in data science. The session begins at 8:30 a.m.
  • Internationally renowned scientists, including Robert Nowak, McFarland-Bascom Professor in Engineering at the University of Wisconsin-Madison; Susan Murphy, H.E. Robbins Distinguished University Professor of Statistics at U-M, and Kathleen McKeown, director of the Institute for Data Sciences and Engineering at Columbia University, will present on cross-cutting data science methodologies. The session begins at 9:20 a.m.
  • A session on Education, Workforce Development and Careers in Data Science, including an overview of the MIDAS education and training program from Ivo Dinov, MIDAS associate director for education and training, and presentations from U-M alumni Erin Shellman, research scientist with Amazon Web Services; Patrick Harrington, director of engineering for WalmartLabs; and Nandit Soparkar, chief executive officer of Ubiquiti. The session begins at 10:40 a.m.
  • Overviews of data science challenges in health, learning analytics, social science and transportation from George Poste, Regents’ Professor and Del E. Webb Chair in Health Innovation at Arizona State University; Bror Saxberg, chief learning officer of Kaplan Inc.; Kathleen Carley, professor of computation, organization and society at Carnegie Mellon University; and Jonathan Owen, director of operations research and vice president of practice, INFORMS, at General Motors. The session begins at 2:20 a.m.
  • A panel discussion of regional, national and international data science initiatives, collaborations and partnerships, including Ed Seidel, Founder Professor in the departments of Physics and Astronomy at University of Illinois at Urbana-Champaign; Kathleen McKeown, director of the Institute for Data Sciences and Engineering at Columbia University; Ratna “Babu” Chinnam, professor of engineering at Wayne State University; Yike Guo, professor of computing science at Imperial College, London; and Keith Elliston, chief executive officer of tranSMART Foundation. The session begins at 4:10 p.m.

The symposium also will include a poster session featuring ongoing data science research at U-M.

The presentations will be held in the Rackham Auditorium, with an overflow video viewing area available in the amphitheater on the fourth floor.

Big data: $5 million to widen “bottleneck to discovery”

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Buried in troves of data that scientists have gathered, but not yet analyzed, could be key insights to improving cancer treatment, understanding Alzheimer’s, predicting climate change effects and developing cheaper, clean energy technologies.

Those are just a few of the countless examples of fields where our capacity to gather scientific data now far exceeds our capacity to crunch it—especially when collaborations span the globe. Some research projects are producing the equivalent of 1,000 consumer hard drives a month, for example.

ARC-TS launches high-speed research storage service

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U-M investigators involved in data-intensive research are getting a new tool to help them store, manage and analyze large data sets.

Advanced Research Computing – Technology Services announced that a new service, Turbo Research Storage, is available to researchers on all U-M campuses.

Turbo allows researchers to access their data in place, making real-time analysis of large data sets possible. Learn more or order the Turbo service.

Researchers no longer will need to spend time and resources building their own storage or looking for solutions outside campus. Instead, they can access, process, and analyze data with Turbo, allowing them to focus on their science.

Turbo Research Storage provides scalable storage and is capable of moving data at speeds of up to 40 gigabits per second. This matches the high performance capabilities of Flux, the shared U-M computing cluster.

Turbo also gives researchers the option of two security levels, one for some types of sensitive data and one for non-sensitive data. For questions regarding use of Turbo for sensitive data, please visit the ITS Sensitive Data Guide.

“Turbo provides a solution for researchers looking to take advantage of Big Data, high performance computing, and roaming,” said Brock Palen, associate director of Advanced Research Computing Technology Services (ARC-TS). “It also meets increasing security requirements without the worry about where and how data is stored, accessed, and shared.”

Collaboration and sharing of information are key characteristics of today’s research activities. Turbo is designed for joint work on shared files across a research group, so there is no need for multiple copies of important datasets or complex permission configurations for individual users within a group.

The service is designed to easily connect with Flux, as well as off-campus computing systems and collaborators.

Access to Turbo is limited to researchers. The service is funded by an IT capital request specifically targeted for research use.

Turbo Research Storage is provided by the newly formed ARC-TS, the research computing arm of Information and Technology Services, operating under the auspices of Advanced Research Computing in the Office of Research. ARC-TS is the one-stop destination for delivery of research computing services to researchers across campus.

Turbo is available in increments of 1 terabyte, at a cost of $19.20 per replicated TB per month.

Flux user meetup — Fri., 10/2

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Users of high performance computing resources are invited to meet Flux operators and support staff in person at an upcoming user meeting:

  • Friday, Oct. 2, 1 – 5 p.m., Medical Sciences Building I, Room 7323 (1301 Catherine St.)

There is not a set agenda; come at anytime and stay as long as you please. You can come and talk about your use of any sort of computational resource,Flux, Hadoop, XSEDE, Amazon, or other.

Ask any questions you may have. The Flux staff will work with you on your specific projects, or just show you new things that can help you optimize your research.

This is also a good time to meet other researchers doing similar work.

This is open to anyone interested; it is not limited to Flux users.

Examples potential topics:

• What ARC-TS services are there, and how to access them?
• How to make the most of PBS and learn its features specific to your work?
• I want to do X, do you have software capable of it?
• What is special about GPU/Xeon Phi/Accelerators?
• Are there resources for people without budgets?
• I want to apply for grant X, but it has certain limitations. What support can ARC-TS provide?
• I want to learn more about the compiler and debugging?
• I want to learn more about performance tuning, can you look at my code with me?
• Etc.

U-M launches $100 million Data Science Initiative

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Progress in a wide spectrum of fields ranging from medicine to transportation relies critically on the ability to gather, store, search, and analyze “big data”—collections of information so vast and complex that they challenge traditional approaches to data processing and analysis. The University of Michigan plans to invest $100 million over the next five years in a new Data Science Initiative (DSI) that will enhance opportunities for student and faculty researchers across the University to tap into the enormous potential of big data.

MICDE seminar series announces fall lineup

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The Michigan Institute for Computational Discovery and Engineering (MICDE) has announced its upcoming lineup of speakers in its ongoing seminar series, as well as a number of symposia.

All are welcomed to attend. Students in the Graduate Certificate in Computational Discovery and Engineering and Ph.D in Scientific Computing program are strongly encouraged to attend.

Speakers are:

Mon., Sept. 21, 4 p.m., 340 West Hall
David Ceperly, Prof. of Physics, University of Illinois, Urbana-Champaign
Quantum Monte Carlo studies of dense hydrogen (abstract)

Tue., Sept. 22, 4 p.m., 1012 EECS
Baskar Ganapathysubramanian, Mechanical Engineering, Iowa State University
Computationally exploring process-structure-property relationships in organic electronics (abstract)

Tue., Sept. 22, 9 a.m. – 5 p.m., Rackham 4th floor Amphitheater
Computational Discovery in Complex Systems Biology, Symposium (website)

Wed., Oct. 21, Location TBD
Craig Steward, Associate Dean, Research Technologies; Executive Director of the Pervasive Technology Institute, Indiana University
Topics: Advanced IT research and development

Fri., Oct. 30, Location TBD
Jim Chelikowsky, Director of the ICES Center for Computational Materials, Prof. of Physics, Chemical Eng., and Chemistry and Biochemistry, University of Texas at Austin
Topics: Quantum models for functionalized nanostructures; high performance algorithms for the electronic structure problems.

Tue., Nov. 3, 4 p.m., 1360 East Hall
Marc Bonnet, Research Director / Senior Scientist, Centre National de la Recherche Scientifique (CNRS), France. Adjunct Professor of Civil Eng., University of Minnesota
Topics: Identification and inverse problems; wave propagation, solid and fracture mechanics;  integral equations and asymptotic methods for small geometrical features.

Mon., Nov. 9, Location TBD
Jeffrey Hittinger, Computational Scientist and Group Leader for the Scientific Computing Group, Lawrence Livermore National Laboratory
Topics: Application of advanced discretization methods and techniques to plasma physics simulations.

Wed., Dec. 2, Location TBD
Tom Hughes, Director of the ICES Computational Mechanics Group, Prof. of Aerospace Eng. and Eng. Mechanics, University of Texas at Austin
Topics:  Computational mechanics; Isogeometric Analysis

Date TBD, Location TBD
Maarten de Hoop, Math+X Prof. of Computational and Applied Mathematics, Rice University
Topics: Inverse problems, Earth’s Sciences
For more information, visit the seminar series web page.

Info Session: Graduate studies in computational and data sciences at U-M — Sept. 17

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Learn about graduate programs that will prepare you for success in computationally intensive fields, and enjoy some pizza. Presentations will describe the following programs:

  • The Ph.D. in Scientific Computing is open to all Ph.D. students who will make extensive use of large-scale computation, computational methods, or algorithms for advanced computer architectures in their studies. It is a joint degree program, with students earning a Ph.D. from their current departments, “… and Scientific Computing” — for example, “Ph.D. in Aerospace Engineering and Scientific Computing.”
  • The Graduate Certificate in Computational Discovery and Engineering trains graduate students in computationally intensive research so they can excel in interdisciplinary HPC-focused research and product development environments. The certificate is open to all students currently pursuing Master’s or Ph.D. degrees at the University of Michigan.
  • The new Graduate Certificate in Data Science is focused on developing core proficiencies in data analytics: 1) Modeling — Understanding of core data science principles, assumptions and applications; 2) Technology — Knowledge of basic protocols for data management, processing, computation, information extraction, and visualization; 3) Practice — Hands-on experience with real data, modeling tools, and technology resources.

Thursday, September 17, 5-6 p.m., Ehrlicher Room, North Quad 

Presenters:

  • Ken Powell, Arthur F. Thurnau Professor of Aerospace Engineering
  • Eric Michielssen, Professor of Electrical Engineering and Computer Science
  • Ivo Dinov, Associate Professor of Computational Medicine and Bioinformatics, and Human Behavior and Biological Sciences.

There will be time for questions and discussion.

Symposium: Computational Discovery in Complex System Biology — Sept. 22, Rackham Building

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Title: Computational Discovery in Complex Systems Biology

Time/Date: 9 a.m. – 5 p.m., Tuesday, Sept. 22

Location: Fourth Floor, Rackham Building, 915 E. Washington St.

Schedule:

  • Speakers including:
    • David Odde, Biomedical Engineering, University of Minnesota
    • Tim Elston, Pharmacology, University of North Carolina
    • Jay Humphrey, Biomedical Engineering, Yale University
    • Andrew McCulloch, Bioengineering & Medicine, University of California, San Diego
    • Barry Grant, Computational Medicine & Bioinformatics, University of Michigan
    • Jennifer Linderman, Chemical Engineering, University of Michigan
    • Daniel Forger, Mathematics, University of Michigan
  • Poster session

Registration: Required, but free.

Sponsors: Center for Systems Biology; Michigan Institute for Computational Discovery and Engineering (MICDE); Complex Systems