U-M students invited to apply for MICDE fellowships — May 19 deadline

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University of Michigan students are invited to apply for Michigan Institute for Computational Discovery and Engineering (MICDE) Fellowships for the 2017-2018 academic year. These $4,000 fellowships are available to students in both the Ph.D in Scientific Computing and the Graduate Certificate Program in Computational Discovery and Engineering. Applicants should be graduate students enrolled in either program, although students not yet enrolled but planning to do so may simultaneously submit program and fellowship applications.

Fellows will receive a $4,000 research fund that can be used to attend a conference, to buy a computer, or for any other approved activity that enhances the Fellow’s graduate experience. We also ask that Fellows attend at least 8 MICDE seminars between Fall 2017 and Winter 2018, attend one MICDE students’ networking event, and present a poster at the MICDE Symposium on March 22, 2018. For more details and to apply please visit http://micde.umich.edu/academic-programs/micde-fellowships/.

Interested students should download and complete the application form, and submit it with a one-page resume as a SINGLE PDF DOCUMENT to MICDE-apps@umich.edu. The due date for applications is May 19, 2017, 5:00 E.T. We expect to announce the awardees onJune 5, 2017.

We encourage applications from all qualified candidates, including women and minorities.

MICDE Annual Symposium – Poster Competition Winners

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Fifty-six posters were submitted to the 2017 MICDE symposium poster competition.

Last week’s MICDE annual symposium included a poster competition for students and postdocs. The event featured 56 posters that highlighted the interdisciplinary nature of the institute. (Some of the posters were described in a story in the Michigan Daily). All of the titles and abstracts submitted are in this spreadsheet.

Victor Wu, Ph.D. Candidate in the department of Industrial and Operations Engineering, won first place and $500 for his poster “Multicriteria Optimization for Brachytherapy Treatment Planning.” Wu and co-authors Epelman, Sir, Pasupathy, Herman and Duefel, introduced an efficient Pareto-style planning approach and intuitive graphical user interface that enables a planner or physician to directly explore dose-volume histogram metric trade-offs for brachyotherapy treatment – a common method for treating cancer patients with radiation.

Sambit Das, Ph. D. Candidate of Mechanical Engineering, earned second place and a $250 prize for his work on “Large Scale Electronic Structure Studies on the Energetics of Dislocations in Al-Mg Materials System and Its Connection to Mesoscale Models

Third place, also with a $250 prize, went to Joseph Cicchese, Ph. D. Candidate in the Department of Chemical Engineering, for his poster titled “How to optimize tuberculosis antibiotic treatments using a computational granuloma model. Cicchese and co-authors Pienaar, Kirschner and Linderman, proposed a method of combining an agent-based and multi-scale model of tuberculosis granuloma formation and treatment with surrogate-assisted optimization to identify optimal tuberculosis treatments.

 

MIDAS starting research group on mobile sensor analytics

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The Michigan Institute for Data Science (MIDAS) is convening a research working group on mobile sensor analytics. Mobile sensors are taking on an increasing presence in our lives. Wearable devices allow for physiological and cognitive monitoring, and behavior modeling for health maintenance, exercise, sports, and entertainment. Sensors in vehicles measure vehicle kinematics, record driver behavior, and increase perimeter awareness. Mobile sensors are becoming essential in areas such as environmental monitoring and epidemiological tracking.

There are significant data science opportunities for theory and application in mobile sensor analytics, including real-time data collection, streaming data analysis, active on-line learning, mobile sensor networks, and energy efficient mobile computing.

Our working group welcomes researchers with interest in mobile sensor analytics in any scientific domain, including but not limited to health, transportation, smart cities, ecology and the environment.

Where and When:

Noon to 2 pm, April 13, 2017

School of Public Health I, Room 7625

Lunch provided

Agenda:

  • Brief presentations about challenges and opportunities in mobile sensor analytics (theory and application);

  • A brief presentation of a list of funding opportunities;

  • Discussion of research ideas and collaboration in the context of grant application and industry partnership.

Future Plans: Based on the interest of participants, MIDAS will alert researchers to relevant funding opportunities, hold follow-up meetings for continued discussion and team formation as ideas crystalize for grant applications, and work with the UM Business Engagement Center to bring in industry partnership.

Please RSVP.  For questions, please contact Jing Liu, Ph.D, MIDAS research specialist (ljing@umich.edu; 734-764-2750).

Workshop co-chaired by MIDAS co-director Prof. Hero releases proceedings on inference in big data

By | Al Hero, Educational, General Interest, Research | No Comments

The National Academies Committee on Applied and Theoretical Statistics has released proceedings from its June 2016 workshop titled “Refining the Concept of Scientific Inference When Working with Big Data,” co-chaired by Alfred Hero, MIDAS co-director and the John H Holland Distinguished University Professor of Electrical Engineering and Computer Science.

The report can be downloaded from the National Academies website.

The workshop explored four key issues in scientific inference:

  • Inference about causal discoveries driven by large observational data
  • Inference about discoveries from data on large networks
  • Inference about discoveries based on integration of diverse datasets
  • Inference when regularization is used to simplify fitting of high-dimensional models.

The workshop brought together statisticians, data scientists and domain researchers from different biomedical disciplines in order to identify new methodological developments that hold significant promise, and to highlight potential research areas for the future. It was partially funded by the National Institutes of Health Big Data to Knowledge Program, and the National Science Foundation Division of Mathematical Sciences.

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Michigan Biological Software Team to compete at iGEM with MICDE support

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MICDE is pleased to announce its support of the Michigan Biological Software Team (MiBioSoft), for its attendance at the 2017 International Genetically Engineered Machine (iGEM) competition in Boston.

Founded in 2014, MiBioSoft is a student-run organization at the University of Michigan that develops software for use in scientific research, with a focus on synthetic biology. It seeks to provide its members with opportunities to not only improve their skills as software designers, but also to improve their communication and management skills by bringing together students from a variety of backgrounds including Biology, Mathematics, Computer Science, and Chemistry.

MiBioSoft competes annually in the software track of the iGEM competition, where research teams from around the world present their results over the course of a three-day conference. During the first two years at the competition, the team was awarded bronze medals. In 2016, MiBioSoft received Best Software Project award as well as a gold medal for their protocol catalog, ProtoCat, in a competition that featured over 300 teams from more than 40 countries, with more than 5,000 participants in total.

About Protocat

Protocat is protocol catalog software developed by MiBioSoft students to address the issue of reproducibility in synthetic biology. Like many innovative ideas, it began because of a problem. Studies have estimated that only 10-25% of published scientific results are reproducible. A 2014 survey conducted by the Michigan Software team confirmed that the repeatability problem exists in synthetic biology, with every scientist surveyed reporting prior struggles with replicating protocols.

ProtoCat 3.0 is a free database of crowd-sourced protocols designed to make existing protocols more repeatable and enable more accurate computational models of biological systems. MiBioSoft believes this can most efficiently be accomplished with a commitment to open source protocols and a broader more active community of digital troubleshooters. ProtoCat 3.0 works to establish such a community by giving anyone with an internet connection or smartphone access to a repository of synthetic biology protocols collected from all over the world. Additionally, ProtoCat 3.0 encourages the development of higher quality, more repeatable protocols by allowing users to document, rate, review, and edit existing methods.

Graduate Studies in Computational & Data Sciences Info Session — Jan 9 & 11

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Learn about graduate programs that will prepare you for success in computationally intensive fields — pizza and pop provided

  • 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 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

There will be two sessions in January 2017:

Info Session: Data Science Services at U-M — Nov. 1

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Representatives of Consulting for Statistics, Computing and Analytics Research (CSCAR) and the U-M Library (UML) will give an overview of services that are now available to support data-intensive research on campus.  As part of the U-M Data Science Initiative, CSCAR and UML are expanding their scopes and adding capacity to support a wide range of research involving data and computation.  This includes consulting, workshops, and training designed to meet basic and advanced needs in data management and analysis, as well as specialized support for areas such as remote sensing and geospatial analyses, and a funding program for dataset acquisitions.  Many of these services are available free of charge to U-M researchers.  

This event will begin with overview presentations about CSCAR and Library system data services.  There will also be opportunities for researchers to discuss individualized partnerships with CSCAR and UML to advance specific data-intensive projects.  Faculty, staff, and students are welcome to attend.  

Time/Date: 4-5 p.m., November 1,
Location: Earl Lewis Room, Rackham Building

[SC2] HPC resources available to U-M students

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Brock Palen, Associate Director of Advanced Research Computing-Technology Services, joined the SC2 to talk about all the high performance computing (HPC) resources available to U-M graduate and undergraduate students. A summary of his presentation is here.

Resources:

Available at/through Michigan

  1. Flux for Undergraduates: Undergraduates can use the local flux computing cluster FOR FREE! Please visit the page for more information
    • ARC-Connect: use for Jupyter notebooks and VNC (remote desktop) access of flux resources, useful for remote visualization of big data or just getting a feel for working on linux and flux.
  2. Amazon Web Services: Michigan students get $100/year in amazon web services. While not as cost-effective for some things, very good resource to be aware of.
  3. Hadoop: Michigan’s Hadoop cluster is available for free (I believe you have to apply/demonstrate a need, but you don’t have to pay if it’s accepted). This upcoming workshop will go over the basics, read more if you are interested.

Available via Grant

Brock has an up-to-date webpage linking to and detailing various resources you can apply for.

Highlights:
  1. XSEDE:
    • Startup and teaching allocations are available continuously
    • Research allocations accepts 4x/year
  2. Great Lakes Consortium:
    • Alternate way to get some time on Blue Waters
  3. Amazon/Microsoft/Google:

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2015-2016 Education Snapshot

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XSEDESummerBootCamp2016

Students at the U-M satellite site of the XSEDE 2016 Summer Bootcamp

We have over 80 students between our Ph.D. in Scientific Computing and the Graduate Certificate in Computational Discovery and Engineering. The students come from five different schools and colleges, and 30 percent are women. We also have partnered with the Multidisciplinary Design Program to offer our Masters students the experience to work on industrial projects and gain practicum credits.

Our faculty have designed two courses that are being offered for the first time: Methods and Practices of Scientific Computing in Fall 2016 and Data-Driven Analysis and Modeling of Complex Systems in Winter 2017. Methods and Practices of Scientific Computing has gathered a tremendous amount of interest, and very quickly was over-subscribed. Data-Driven Analysis and Modeling of Complex Systems is a fast paced research area that combines scientific computing with big data to improve the existing models’ accuracy and representation of physical and biological systems.

Scientific Computing Student Club social gathering

Scientific Computing Student Club social gathering

We have brought a large community of students together by sponsoring and helping found the Scientific Computing Student Club. Its goal is to become a place for all students that use or want to use high performance computing to meet, share ideas, and find peer-to-peer help. It started in February, with social gatherings, talks from expert speakers, and more. The club has nearly 200 members, including undergraduates, graduate students, and postdocs from six U-M schools and colleges.