Fall 2021 Information Sessions

By | Educational, Events

Fall 2021 information sessions on graduate programs in computational and data sciences at U-M

U-M graduate students interested in computational and data sciences are invited to learn about joint programs that will prepare them for success in computationally intensive fields. The programs are organized by the Michigan Institute for Computational Discovery & Engineering, and the Michigan Institute for Data Science. Both institutes offer vast training and networking opportunities, including webinar series, symposia and student centered events.

Two sessions are scheduled

The sessions will address:

  • The Graduate Certificate in Computational Discovery and Engineering: trains students in computationally intensive research so they can excel in interdisciplinary HPC-focused research and product development environments.

  • The Graduate Certificate in Data Science: focuses on developing core proficiencies in data analytics: modeling, technology and practice.

  • The Graduate Certificate in Computational Neuroscience: provides training in interdisciplinary computational neuroscience to students in experimental neuroscience programs, and to students in quantitative science programs, such as physics, biophysics, mathematics and engineering.

  • The  Ph.D. in Scientific Computing: 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.”

University of Michigan’s Ph.D. in Scientific Computing: A history of supporting research through education

By | Educational, Feature

#Computationalscience everywhere!

Left side, 2167 configuration console for the IBM/System 360 Model 67-2 (duplex) at the University of Michigan, c. 1969 [Picture by Scott Gerstenberger – Scott Gerstenberger, Public Domain]

The University of Michigan’s joint Ph.D. program in Scientific Computing recently achieved a record enrollment of 137 students. Between 2015, when 15 students were enrolled -mainly from the Colleges of Engineering and Literature, Science and the Arts- and today, the program has witnessed an explosive growth of interest on the part of U-M students. The program now has students enrolled from over 30 departments spanning 8 different schools and colleges, and more than 130 students have graduated in the last 31 years, including 17 students to-date in 2020.

This popularity is emblematic of the dominant role that computation plays in the world today. With the breakneck pace at which new hardware and software architectures are being developed, the boom in simulation-based research in a growing number of disciplines, and the initiatives in data and computational sciences implemented at U-M in the last few years, including the establishment of the Michigan Institute for Computational Discovery & Engineering, and the Michigan Institute for Data Science (MIDAS), it may seem only natural that scientific computing should attract this level of interest. However, like all exceptionally successful undertakings, it owes a great deal to its past. We reached back more than three decades to piece together the history of the Ph.D. in Scientific Computing at U-M.

The broader history of computational science and high performance computing at the University of Michigan is rich and extensive. U-M has been at the forefront of Cyberinfrastructure research for many decades, marked by the acquisition of U-M’s first virtual memory computer in 1967, an IBM 360/67, one of the first computers of its kind in the world. This milestone was followed by many others, including further hardware acquisitions and establishment of new units to support advanced research computing. An important early step was taken in 1985 when the College of Engineering established the Laboratory for Scientific Computation (LaSC). LaSC’s goal was to foster and promote the use of scientific computation in research and instruction at U-M. During those years, several reports from national study committees established computational science as the third pillar of scientific methodology, along with theory and experimentation. Faculty members of LaSC, who were at the forefront of driving these trends  recognized that any initiative in this field needed to include a robust student training program. 

left: Prof. Kenneth Powell (Aerospace Engineering), director of the Ph.D. in Scientific Computing program since 2005; right: Prof. William Martin (Nuclear Eng. and Rad. Sciences), director of the program from 1989 to 2004.

Prominent at that time in LaSC were Prof. William “Bill” Martin (Nuclear Engineering and Radiological Sciences – NERS), the laboratory’s director, Prof. John Boyd (Atmospheric, Oceanic and Space Sciences), the laboratory’s associate director, and Prof. Edward Larsen (NERS), who was hired as part of the College of Engineering’s initiative to move aggressively in the area of scientific computing. Together, they designed a graduate academic program with the goal of giving students a more comprehensive training in numerical analysis and computer science than is typically possible within standard disciplinary programs housed within individual departments and schools. The fundamental idea was that, to excel in computational science and engineering, one must have a thorough understanding of the mathematical and physical problems to be solved, expertise in  the methodologies and algorithms, and a foundation in computer science to be able to apply this arsenal of techniques on modern computer platforms. The need for a thorough understanding of the physical problems led directly to the requirement that students had to be enrolled in a traditional Rackham degree program (i.e., a home department), while the need for mathematical underpinning and knowledge of algorithms and computer science topics led to the requirements for courses in numerical analysis, parallel algorithms, and related topics. The PhD in Scientific Computing program was approved by the State of Michigan in 1988, and enrolled its first students in 1989. This was well in advance of a wider recognition of the centrality of computation in academia and industry. It is true today, as it was in 1988, that students can apply to the PhD in Scientific Computing program from any Rackham-recognized PhD program at the UM. This unique and flexible administrative structure has enabled the rapid growth experienced in recent years as scientific computing has become an indispensable tool in many fields of academic endeavor. 

Prof. Quentin Stout, director of the Center for Parallel Computing 1992-2001 [Picture source: NASA Insights 1998]

The oversight of the degree program has evolved over the years as administrative structures around scientific computing have shifted. Regardless of its administrative home, the program has always been organized under the Rackham School of Graduate Studies. Originally, the College of Engineering had oversight of the program, with Prof. Martin appointed as director, and with guidance from the LaSC Education Committee. This setup continued through the merger of LaSC and the Center for Parallel Computing1 into the Center for Advanced Computing in 2001. In 2005, Prof. Kenneth Powell (Aerospace Engineering) was named director of the program succeeding Prof. Martin, and has continued in the role since. In 2008, the Office of Research Cyberinfrastructure (ORCI) was established, and the oversight of the program changed to the U-M Office of Research. In 2013, when ORCI was re-named as Advanced Research Computing, and the Michigan Institute for Computational Discovery & Engineering (MICDE) was born, oversight was transferred to MICDE.

Since its inception, the program has been described as intended for students who will make intensive use of large-scale computation, computational methods or algorithms in their doctoral studies. Although the requirements and goals of the program have not  changed in 31 years, the research applications, the algorithms and methodologies, and the computer platforms have been in constant evolution. Naturally, the courses offered in support of the program have followed closely. In 1989 the core research areas behind the program were computational fluid dynamics, advanced computer architectures, and particle transport, with the majority of the students coming from engineering, and mathematics. Still, students working in areas where computation was less recognized, such as AIDS transmission or social research projects, also were enrolled. Over the next two decades, the tremendous increase in simulation-based research by the faculty in engineering and physical sciences added many other focus areas, including material science, astronomy, and high energy physics, to name just a few. This growth added a new driver as data-intensive research gained importance in those fields. 

Prof. Suzanne Weekes, Associate Dean of Undergraduate Studies, ad interim, and Professor of Mathematical Sciences at Worcester Polytechnic Institute (U-M 1995, Mathematics and Scientific Computing) [Picture source: SIAM News Sept. 2020]

Several faculty members have had an important role shaping the program, by offering fundamental courses and providing mentorship. Notably, Prof. Quentin Stout, from Computer Science and Engineering, has had a prominent role in the program. He was the founding director of the Center for Parallel Computing, which  provided the basis for subsequent units in this sphere at U-M. He also developed, and has been teaching, Parallel Computing since 1985, innovating its curriculum to remain at the cutting edge of the current techniques, important aspects of which have been based on his own research. Other foundational courses, such as the Department of Mathematics’ Numerical Methods for Scientific Computing I & II and Numerical Linear Algebra have been offered for more than 30 years. More recently the Department of Physics course, Computational Physics, and the College of Engineering course, Methods and Practice of Scientific Computing, along with an array of courses in machine learning, have played prominent roles in transforming the curriculum in scientific computing as research in these areas has likewise redefined the field.

Unsurprisingly, the Ph.D. in Scientific Computing has produced many exceptional alumni. The first student graduated from the program in 1992, and notably for its time, two of the first four graduates were women, when gender imbalance was barely recognized. A majority of the program graduates went on to  positions in academia or the National Laboratories, with the rest working in varied fields in industry or government. Some of these outstanding alumni include Suzanne Weekes, U-M 1995 (Mathematics and Scientific Computing), currently Associate Dean of Undergraduate Studies, ad interim, and Professor of Mathematical Sciences at Worcester Polytechnic Institute. Prof. Weekes has recently been named SIAM executive director, and will start her new role on January 1, 2021.  Another alumna, Rona Oran, U-M 2014 (Space Science and Scientific Computing), is a computational plasma physicist at MIT and a member of the NASA team that is designing and planning a mission to the metal asteroid Psyche to be launched in 2020.

The current goal of the program is still founded on the original idea of strengthening the students’ foundations in methodology and computer science. The leadership of the program strives to bring computational science to more research fields, but importantly, aims to do so by enhancing diversity in the field. An important marker of U-M’s success on this front came in  2018 in the form of the Henry Luce Foundation’s award to the University of two Claire Boothe Luce Ph.D. fellowships for women to enroll in the Ph.D. in Scientific Computing. The program is committed to pursuing other such opportunities and creating an environment where students of all backgrounds and identities feel welcome and thrive.

1 In 1992 U-M was awarded a major equipment grant by the National Science Foundation to create a testbed of parallel computing architectures. The Center for Parallel Computing was established to operate the facility. The center installed and operated several different parallel computers over the years, including KSR-1, KSR-2, Convex Exemplar, SGI PowerChallenge, IBM SP2, and AMD and Apple clusters.

We welcome 15 students to the 2020-21 class of MICDE graduate fellows

By | Educational, News

MICDE is proud to announce the recipients of the 2020 MICDE graduate fellowships. The fellows’ research projects involve the use and advancement of scientific computing techniques and practices. From political science, psychology, physics, and applied and interdisciplinary mathematics within the College of Literature, Science & the Arts to aerospace engineering, mechanical engineering, materials science engineering, industrial & operations engineering, and civil & environmental engineering within the College of Engineering, the 2020 MICDE fellows epitomize the reach of computation in diverse scientific disciplines.

For the past six years, MICDE has awarded fellowships to over 120 graduate students from our large community of computational scientists. The MICDE graduate student top-off fellowship provides students with a stipend to use for supplies, technology, and other materials that will further their education and research. Among other things, awards have helped many to travel to conferences and meetings around the world to share the rich and diverse research in computational science being carried out at U-M.

The awardees are:

Eytan Adler, Aerospace Engineering
Hessa Al-Thani,
Industrial and Operations Engineering
Zijie Chen,
Mechanical Engineering
Alexander Coppeans
, Aerospace Engineering
Xinyang Dong, Physics
Karthik Ganesan,
Psychology
Iman Javaheri, Aerospace Engineering
Huiwen Jia, Industrial and Operations Engineering
Daeho Kim, Civil and Environmental Engineering
Yudan Liu,
Chemistry
Emily Oliphant
, Materials Science and Engineering
Ryan Sandberg, Applied and Interdisciplinary Mathematics
Patrick Wu, Political Science
Zhucong Xi, Materials Science and Engineering
Yi Zhu, Civil and Environmental Engineering

Learn more about the fellows and the MICDE Fellowship program

U-M draws global attention for MOOC: Problem Solving using Computational Thinking

By | Educational, Feature, Research

Problem Solving using Computational Thinking, a Massive Open Online Course (MOOC) launched by the University of Michigan in November of 2019, has already drawn more than 1,200 learners from around the globe. The Michigan Institute for Computational Discovery & Engineering (MICDE) and the University of Michigan Center for Academic Innovation partnered to create this course. The idea for this MOOC arose from the team’s recognition of the ubiquity of computation. However, the developers were equally keen to distinguish this offering from MOOCs on programming and to instead highlight how broader computational thinking also makes its presence felt in somewhat unexpected domains.

Using computational thinking, the MOOC challenges learners with a series of real-world examples, including how it is possible to help plan and prepare for a flu season–a subject that has gained particular relevance in the months following the launch of this MOOC, track human rights violations or monitor the safety of crowds.

While enrollment numbers are encouraging, the work being done by learners within the MOOC is most inspiring. For their final project, learners have applied the computational thinking strategies discussed throughout the MOOC to a wide array of noble social problems in hopes of finding cogent solutions.

Not surprisingly, there have been several projects that seek to address challenges related to COVID 19.

The MOOC’s Epidemiology Case Study walks the student through the process of building a communicable disease transmission model.

One learner wrote: “For the final project, I am assuming the role of a member of the team responsible to combat COVID-19 from India and I have to decide on what should be our strategy to fight coronavirus in India, be it the extension of a lockdown or any other important decision related to this pandemic.”

In another project, a learner assuming the role of a Wuhan pathologist wrote that they must “decide what the Chinese government’s strategy against coronaviruses” should be.

Learners addressing today’s most pressing societal concerns, such as COVID-19, exemplifies the transformative potential of open-access, digital, and distance education made possible by a MOOC.

Across the board, the MOOC has received tremendously positive reviews, with an overall course rating of 5 out of 5 stars. One learner, in particular, wrote in their course review: “I really enjoyed this course! It got me prepared to study for an entry into a career working with computers!!” Another learner simply stated: “Fantastic, loved it!”

The developers of this MOOC are drawn from the School of Public Health, the College of Engineering, the School of Education and MICDE. Problem Solving using Computational Thinking is available in Coursera through Michigan Online. To learn more please visit online.umich.edu/courses/problem-solving-using-computational-thinking/.

U-M Tobacco Center, CAsToR, accepting applications for scholarships to enroll in short U-M summer courses

By | Educational, Funding Opportunities

The Center for the Assessment of Tobacco Regulations (CAsToR) is accepting applications for scholarships to participate in a short course on tobacco simulation modeling, EPID730 Simulation Modeling of Tobacco Use, Health Effects and Policy Impacts,  or in the course EPID 793 Complex Systems Modeling for Public Health Research, to be offered during the University of Michigan Summer Session in Epidemiology (SSE) Program in 2020. Note that the courses will now be offered in an online format only.

New deadline to apply: 11:59 PM EST on Wednesday April 15, 2020

Additional details on both courses can be found here: sph.umich.edu/umsse/courses/1week.html.  A tentative course syllabus for EPID 730 can be found in this google doc. See the full RFA here. Please contact Katie Zarins (kmrents@umich.edu) with questions.

New MOOC in Computational Thinking has launched!

By | Educational, Feature, Happenings

The Michigan Institute for Computational Discovery & Engineering and the University of Michigan Center for Academic Innovation have partnered to launch a Massive Open Online Course (MOOC) titled Problem Solving using Computational Thinking. The idea for this MOOC arose from the team’s recognition of the ubiquity of computation. However, the developers were equally keen to distinguish this offering from MOOCs on programming, and to instead highlight how broader computational thinking also makes its presence felt in somewhat unexpected domains. The MOOC is organized in a series of real-world examples that includes how, using computational thinking, it is possible to help plan and prepare for a flu season, track human rights violations or monitor the safety of crowds. The process of computational thinking that this MOOC focuses on ranges from problem identification, through abstraction to evaluating solutions. Problem Solving using Computational Thinking seeks to introduce students and teachers to the systematic thinking needed to conceptualize a problem with the intent of eventually using some computational tools to solve it.

The developers of this MOOC are drawn from the School of Public Health, the College of Engineering, the School of Education and MICDE. Problem Solving using Computational Thinking is available in Coursera through Michigan Online. To learn more please visit online.umich.edu/courses/problem-solving-using-computational-thinking/.

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

Research Opportunity, Mechanical Engineering, TREE Lab – Summer 2019

By | Educational, Research, SC2, SC2 jobs

Dr. Bala Chandran’s Research Group, Mechanical Engineering, TREE Lab

Dr. Bala Chandran is seeking a highly motivated graduate (doctoral or masters) student interested in
doing research in the broad area of understanding radiative heat transfer in granular and
suspension flows via computational modeling for applications of high-temperature
energy storage and catalysis applications. Applicants are expected to have a sound
knowledge of fluid/continuum mechanics and the fundamentals of heat-transfer;
experience in complex fluids or multiphase flows is desirable, though not essential.
Applicants should be interested in the computational aspects of this project to develop
and write code.

Qualifications

  • Strong analytical and computational skills, and intellectual independence (i.e.,
    able to read books and papers and learn by oneself; able to apply theoretical
    knowledge to practical situations)
  • Relevant course work and experience related to
    • Undergraduate level fluid mechanics, solid mechanics, heat transfer,
      radiation, numerical methods and programming, computational fluid/solid
      mechanics
    • Graduate level courses on any/all of the above topics will be a plus point
  • Excellent professional and work ethic
  • Team player that is ready to interface with people developing experiments on
    this project

Application Procedure

If you are interested in this opportunity, please email Prof. Bala Chandran
(rbchan@umich.edu) all the following documents AS SOON AS POSSIBLE:

  1. A 2-page CV with references listed
  2. Unofficial academic transcript
  3. 1 one-page (maximum) statement of interest that explains why you are best suited for working on the proposed research topic and indicates how you meet the required project criteria.
  4. Slides (maximum 5) that showcase your research experience and contributions

PhD student opening in Global Ocean Modeling and Scientific Computing

By | Educational, SC2 jobs

A PhD student is sought for a Department of Energy (DOE)-funded project in Global Ocean Modeling and Scientific Computing. The student will work with Professor Brian Arbic at the University of Michigan (U-M), Dr. Phillip Wolfram and Dr. Andrew Roberts of DOE’s Los Alamos National Laboratory, and other DOE scientists. The student will be admitted to the PhD program of the Department of Earth and Environmental Sciences, and will attain a joint PhD in U-M’s Program in Scientific Computing.

Project Description

The project involves insertion of tides into the ocean component of the DOE Energy Exascale Earth System Model (E3SM). The ocean component is based upon the Model Prediction Across Scales (MPAS) code, which uses a finite-element mesh to focus attention on coastal regions. With the addition of tidal forcing, the model will be an ideal tool with which to quantify the changes likely to occur in coastal areas over the next 50-100 years. The student will be strongly encouraged to spend significant time in Los Alamos, working alongside DOE scientists. The project is ideal for students who wish to apply the tools of scientific computing to societally relevant problems, in a university-DOE partnership with significant networking and travel opportunities. The project will increase the number of professionals familiar with both oceanography and computational science, an identified need in several federal ocean modeling centers including Los Alamos National Laboratory.

Application Procedure

  • Applicants must have strong quantitative and programming skills. Backgrounds in mathematics, computer science, physics, and related fields will be given highest consideration.
  • The preferred start date is January 1, 2020, but a start date of September 1, 2020 is also possible.
  • Students interested in applying to work with Professor Arbic should email their CV, unofficial transcript and cover letter, combined into a single PDF file to: Arbic-Ocean-Modeling-PhD@umich.edu. Questions about the project may also be sent to this email address.
  • In addition, an application to the PhD program in Earth and Environmental Sciences is required. See the Department website for application information. The application deadline to start in January 2020, is September 15, 2019. The application deadline for Fall 2020 is January 7, 2020.

The University of Michigan is an equal opportunity employer and is supportive of the needs of dual career couples. Women and minorities are encouraged to apply

Women in HPC launches mentoring program

By | Educational, General Interest, HPC, News

Women in High Performance Computing (WHPC) has launched a year-round mentoring program, providing a framework for women to provide or receive mentorship in high performance computing. Read more about the program at https://womeninhpc.org/2019/03/mentoring-programme-2019/

WHPC was created with the vision to encourage women to participate in the HPC community by providing fellowship, education, and support to women and the organizations that employ them. Through collaboration and networking, WHPC strives to bring together women in HPC and technical computing while encouraging women to engage in outreach activities and improve the visibility of inspirational role models.

The University of Michigan has been recognized as one of the first Chapters in the new Women in High Performance Computing (WHPC) Pilot Program. Read more about U-M’s chapter at https://arc.umich.edu/whpc/