MICDE funds 7 new catalyst projects

By | General Interest, Happenings, News

Every year, The Michigan Institute for Computational Discovery & Engineering (MICDE) Catalyst Grants fund innovative research projects in computational science that combine elements of mathematics, computer science, and cyberinfrastructure.

Topics of interest include, but are not limited to:

  • Computational science approaches, algorithms, frameworks, etc.
  • Emerging paradigms in computing (exascale computing, quantum computing, FPGA computing, etc.)
  • Applications in emerging areas (neuroscience, ecology, evolutionary biology, human-made complex systems, mobility etc.)
  • Extensions of traditional computational sciences to complex decision making (reinforcement learning, transfer learning, neuromorphic computing, etc.)
  • Artificial Intelligence informing and informed by science

This year, MICDE awarded its third round of catalyst grants to faculty leading seven innovative projects in computational science.

The projects, supported by up to $90,000 in grant funding, span several research areas ranging from cosmology to artificial intelligence systems in computational systems.

Learn more about the 2019-2020 catalyst grants.

The background image is a multi-color image of the Milky Way disk, its halo and nearby satellite galaxies obtained with the European Space Agency’s Gaia Satellite (http://sci.esa.int/gaia/) . The blue curve shows an example of (half) of a regular trajectory that a star in the halo of the Milky Way might follow. [M. Valluri, Astronomy]

MICDE announces 2019-2020 fellowship recipients

By | Educational, General Interest, Happenings, News

The Michigan Institute for Computational Discovery and Engineering (MICDE) is pleased to announce the 2019-2020 MICDE Fellowship recipients. They were chosen to receive this honor because of their exceptional academic record and the outstanding promise of their research in computational sciences. Fellows are working on a wide range of groundbreaking problems, including the strategic interaction of parties and electors in democratic elections (S. Baltz, Political Science), the effects of disruption of synaptic signaling on neuronal structures (M. Budak, Biophysics),  and on the development of robust, efficient, and scalable algorithms for multidisciplinary design optimization applications applied to the design of the next generation of fuel-efficient aircrafts (A. Yildirim, Aerospace). The fellowships, which carry a $4,000 stipend, are meant to augment other sources of funding and are available to students in our three educational programs. Visit our fellowship page to learn more about the program and the fellows.

2019-2020 MICDE Fellows (from left to right) Guodong Chen (Aero), Suyash Tandon (ME), Jiale Tan (Epidemiology), Fuming Chang (ClaSp), Kelly Broen (Epidemiology), Bradley Dice (Physics), Liz Livingston (ME), Will Weaver (EEB), Yuan Yao (ME), Samuel Baltz (Pol Sci), Joe Hollowed (Physics), Minki Kim (ME), Allison Roessler (Chem), Chongxing Fan(ClaSp), Maral Budak (Biophysics), Saibal De (Math), Xian Yu (IOE), Jiaming Zhang (Physics). [Not pictured: Thomas Waltmann (Physics), Anil Yildirim (Aero), and Jessica Conrad (IAM)]

AWARDEES

Samuel Baltz, Political Science
Kelly Broen, Epidemiology
Maral Budak, Biophysics
Fuming Chang, Climate and Space Sciences and Engineering
Guodong Chen, Aerospace Engineering
Jessica Conrad, Applied & Interdisciplinary Mathematics
Saibal De, Applied & Interdisciplinary Mathematics
Bradley Dice, Physics
Chongxing Fan, Climate and Space Sciences and Engineering
Joseph Hollowed, Physics
Minki Kim, Mechanical Engineering
Elizabeth Livingston, Mechanical Engineering
Allison Roessler, Chemistry
Jiale Tan, Epidemiology
Suyash Tandon, Mechanical Engineering
Thomas Waltmann, Physics
William Weaver, Ecology and Evolutionary Biology
Yuan Yao, Mechanical Engineering
Anil Yildirim, Aerospace Engineering
Xian Yu, Industrial & Operations Engineering
Jiaming Zhang, Physics

Ruiwei Jiang wins NSF CAREER award for work in operations research

By | General Interest, Happenings, News

Ruiwei Jiang, assistant professor in Industrial and Operations Engineering and an MICDE-affiliated faculty member, has won an NSF CAREER award for work evaluating the potential benefits of incorporating decision-dependent uncertainty into decision-making problems in service industries and investigate new optimization approaches to maneuvering such uncertainty to improve decision-making.

Read more…

Balzano wins NSF CAREER award for research on machine learning and big data involving physical, biological and social phenomena

By | General Interest, Happenings, News, Research

Prof. Laura Balzano received an NSF CAREER award to support research that aims to improve the use of machine learning in big data problems involving elaborate physical, biological, and social phenomena. The project, called “Robust, Interpretable, and Efficient Unsupervised Learning with K-set Clustering,” is expected to have broad applicability in data science.

Modern machine learning techniques aim to design models and algorithms that allow computers to learn efficiently from vast amounts of previously unexplored data, says Balzano. Typically the data is broken down in one of two ways. Dimensionality-reduction uses an algorithm to break down high-dimensional data into low-dimensional structure that is most relevant to the problem being solved. Clustering, on the other hand, attempts to group pieces of data into meaningful clusters of information.

However, explains Balzano, “as increasingly higher-dimensional data are collected about progressively more elaborate physical, biological, and social phenomena, algorithms that aim at both dimensionality reduction and clustering are often highly applicable, yet hard to find.”

Balzano plans to develop techniques that combine the two key approaches used in machine learning to decipher data, while being applicable to data that is considered “messy.” Messy data is data that has missing elements, may be somewhat corrupted, or is filled heterogeneous information – in other words, it describes most data sets in today’s world.

Balzano is an affiliated faculty member of both the Michigan Institute for Data Science (MIDAS) and the Michigan Institute for Computational Discovery and Engineering (MICDE). She is part of a MIDAS-supported research team working on single-cell genomic data analysis.

Read more about the NSF CAREER award…

H.V. Jagadish appointed director of MIDAS

By | General Interest, Happenings, News

H.V. Jagadish has been appointed director of the Michigan Institute for Data Science (MIDAS), effective February 15, 2019.

Jagadish, the Bernard A. Galler Collegiate Professor of Electrical Engineering and Computer Science at the University of Michigan, was one of the initiators of an earlier concept of a data science initiative on campus. With support from all academic units and the Institute for Social Research, the Office of the Provost and Office of the Vice President for Research, MIDAS was established in 2015 as part of the university-wide Data Science Initiative to promote interdisciplinary collaboration in data science and education.

“I have a longstanding passion for data science, and I understand its importance in addressing a variety of important societal issues,” Jagadish said. “As the focal point for data science research at Michigan, I am thrilled to help lead MIDAS into its next stage and further expand our data science efforts across disciplines.”

Jagadish replaces MIDAS co-directors Brian Athey and Alfred Hero, who completed their leadership appointments in December 2018.

“Professor Jagadish is a leader in the field of data science, and over the past two decades, he has exhibited national and international leadership in this area,” said S. Jack Hu, U-M vice president for research. “His leadership will help continue the advancement of data science methodologies and the application of data science in research in all disciplines.”

MIDAS has built a cohort of 26 active core faculty members and more than 200 affiliated faculty members who span all three U-M campuses. Institute funding has catalyzed several multidisciplinary research projects in health, transportation, learning analytics, social sciences and the arts, many of which have generated significant external funding. MIDAS also plays a key role in establishing new educational opportunities, such as the graduate certificate in data science, and provides additional support for student groups, including one team that used data science to help address the Flint water crisis.

As director, Jagadish aims to expand the institute’s research focus and strengthen its partnerships with industry.

“The number of academic fields taking advantage of data science techniques and tools has been growing dramatically,” Jagadish said. “Over the next several years, MIDAS will continue to leverage the university’s strengths in data science methodologies to advance research in a wide array of fields, including the humanities and social sciences.”

Jagadish joined U-M in 1999. He previously led the Database Research Department at AT&T Labs.

His research, which focuses on information management, has resulted in more than 200 journal articles and 37 patents. Jagadish is a fellow of the Association for Computing Machinery and the American Association for the Advancement of Science, and he served nine years on the Computing Research Association board.

Most CSCAR workshops will be free for the U-M community starting in January 2019

By | Educational, General Interest, Happenings, News

Beginning in January of 2019, most of CSCAR’s workshops will be offered free of charge to UM students, faculty, and staff.

CSCAR is able to do this thanks to funding from UM’s Data Science Initiative.  Registration for CSCAR workshops is still required, and seats are limited.

CSCAR requests that participants please cancel their registration if they decide not to attend a workshop for which they have previously registered.

Note that a small number of workshops hosted by CSCAR but taught by non-CSCAR personnel will continue to have a fee, and fees will continue to apply for people who are not UM students, faculty or staff.

Eric Michielssen completes term as Associate Vice President for Research – Advanced Research Computing

By | General Interest, Happenings, News

Eric Michielssen will step down from his position as Associate Vice President for Research – Advanced Research Computing on December 31, 2018, after serving in that leadership role for almost six years. Dr. Michielssen will return to his faculty role in the Department of Electrical Engineering and Computer Science in the College of Engineering.

Under his leadership, Advanced Research Computing has helped empower computational discovery through the Michigan Institute for Computational Discovery and Engineering (MICDE), the Michigan Institute for Data Science (MIDAS), Advanced Research Computing-Technology Services (ARC-TS) and Consulting for Statistics, Computing and Analytics Research (CSCAR).

In 2015, Eric helped launch the university’s $100 million Data Science initiative, which enhances opportunities for researchers across campus to tap into the enormous potential of big data. He also serves as co-director of the university’s Precision Health initiative, launched last year to harness campus-wide research aimed at finding personalized solutions to improve the health and wellness of individuals and communities.

The Office of Research will convene a group to assess the University’s current and emerging needs in the area of research computing and how best to address them.

U-M approves new graduate certificate in computational neuroscience

By | Educational, General Interest, Happenings, News

The new Graduate Certificate in Computational Neuroscience will help bridge the gap between experimentally focused studies and quantitative modeling and analysis, giving graduate students a chance to broaden their skill sets in the diversifying field of brain science.

“The broad, practical training provided in this certificate program will help prepare both quantitatively focused and lab-based students for the increasingly cross-disciplinary job market in neuroscience,” said Victoria Booth, Professor of Mathematics and Associate Professor of Anesthesiology, who will oversee the program.

To earn the certificate, students will be required to take core computational neuroscience courses and cross-disciplinary courses outside of their home departments; participate in a specialized interdisciplinary journal club; and complete a practicum.

Cross-discplinary courses will depend on a student’s focus: students in experimental neuroscience programs will take quantitative coursework, and students in quantitative science programs such as physics, biophysics, mathematics and engineering will take neuroscience coursework.

The certificate was approved this fall, and will be jointly administered by the Neuroscience Graduate Program (NGP) and the Michigan Institute for Computational Discovery and Engineering (MICDE).

For more information, visit micde.umich.edu/comput-neuro-certificate. Enrollment is not yet open, but information sessions will be scheduled early next year. Please register for the program’s mailing list if you’re interested.

Along with the Graduate Certificate in Computational Neuroscience, U-M offers several other graduate programs aimed at training students in computational and data-intensive science, including:

  • The Graduate Certificate in Computational Discovery and Engineering, which is focused on quantitative and computing techniques that can be applied broadly to all sciences.
  • The Graduate Certificate in Data Science, which specializes in statistical and computational methods required to analyze large data sets.
  • The Ph.D in Scientific Computing, intended for students who will make extensive use of large-scale computation, computational methods, or algorithms for advanced computer architectures in their doctoral studies. This degree is awarded jointly with an existing program, so that a student receives, for example, a Ph.D in Aerospace engineering and Scientific Computing.