Opening The Network

Aleksei Sorokin (Ph.D. AMAT 3rd Year) found a wealth of resources while spending a summer conducting research with Argonne National Laboratory, while also gaining a glimpse as to what it is like to conduct research at a national laboratory as a possible career.

“Having experience at a national laboratory is a big help,” he says. “I’m still trying to decide if I want to get into teaching, a national lab, or the industry.”

Sorokin says the opportunity to work at Argonne came as a suggestion from his Ph.D. adviser, Fred Hickernell, vice provost for research and professor of applied mathematics. Hickernell found a scientist working on a project that overlapped Sorokin’s Ph.D. work. After connecting with Vishwar Rao at Argonne, Sorokin began working on “Credible Intervals for Probability of Failure with Gaussian Processes.”

“The computing resources and access to the supercomputers they have at Argonne makes training these Gaussian models really easy,” Sorokin says. “You just need to make time to use these machines to do your large-scale modeling. It’s really nice to have easy access to those.”

Sorokin explained it would be possible to conduct the research using third party resources at companies such as Google Cloud and Amazon Web Services. However, it would have cost a lot of money and time to use those resources, making it more difficult to conduct the research.

Illinois Institute of Technology has been strengthening ties with the research community at Argonne to expand research opportunities for its students, in addition to the resources of a national laboratory for faculty research.

To strengthen its commitment to research excellence and experiential learning, Illinois Tech recently appointed joint faculty of five staff scientists from Argonne.

Valerie Taylor has accepted an appointment as a research professor, while Xingfu Wu and Michael Kruse have been named research associate professor through Argonne and Illinois Tech’s joint appointment program. The program’s goal is to maximize the intellectual and physical resources of both Argonne and Illinois Tech in order to promote research and collaboration in areas that align with the scientific priorities of Argonne and the United States Depart- ment of Energy. Taylor, Wu, and Kruse are collaborating with several computer science faculty members at Illinois Tech in high-performance computing.

Argonne computer scientists Bogdan Nicolae and Michael E. Papka also joined Illinois Tech’s Department of Computer Science as research professors to enhance stronger research connections between the laboratory and Illinois Tech faculty and students. Nicolae is a technical lead of a project that develops a checkpoint-restart framework for HPC applications. Papka’s research focuses on scientific visualization, large data analysis, and enabling science with computers and computing technology.

“We are delighted to announce these new appointments, which will bring a wealth of opportunity to our faculty and students, including additional funding, more diverse research, and increased collaboration,” says Professor Shlomo Argamon, the former chair of Illinois Tech’s Department of Computer Science. “This brings great benefits to our department, the College of Computing, and the university as a whole.”

The appointees may serve as coadvisers to Ph.D. candidates at Illinois Tech, exposing them to the cuttingedge research projects, as well as open networking pathways and full-time internships at a Department of Energy lab. Although the program has focused on high-performance computing research, the program could expand to collaborations in other computer science areas, such as computational science, data science and learning, environmental science, and bioscience.

“As working scientists today, we have a responsibility to help develop the workforce of tomorrow,” Papka says. “Ideally, the expertise and experience we can bring to the Illinois Tech community will get more students interested in pursuing computational science careers. After all, they have some of the world’s most powerful computing resources available to them, and practically in their backyard.”

Argonne, a U.S. Department of Energy (DOE) laboratory located 20 miles from Illinois Tech’s Mies Campus in suburban Lemont, Illinois, operates world-class user facilities for the research community.

“It’s a great opportunity for students to learn more about our lab and experience hands-on research,” Nicolae says.

Argamon says additional collaboration with Argonne will expand the university’s research possibilities.

“We are very excited about our deepening partnership with Argonne, as exemplified by these new appointments,” Argamon says. “The collaborations that this enables will not only broaden our research activities and extend our impact, but also open up new opportunities for our students to gain practical and interdisciplinary experience by working with scientists at a DOE national lab.”

With these appointments, Papka and Nicolae say they hope to encourage more faculty-led projects, too. Illinois Tech computer science professors have used Argonne resources to work on problems at the forefront of HPC research, with Papka co-supervising Illinois Tech doctoral students working in the same field. Nicolae says he’s had several discussions

with Illinois Tech faculty members covering topics at the intersection of HPC and artificial intelligence.

“It’s a rapidly evolving area that will have a lasting impact and presents plenty of new collaboration opportunities and research topics for the students,” he says.

“I look forward to becoming more engaged with the Illinois Tech community, to continue working with Illinois Tech faculty, and to help students advance and enable the use of computing in discovery science,” Papka says.

For Sorokin, it meant a summer exploring how Gaussian regression models can be used to detect failure within systems. It is important to make sure that a system is reliable and robust enough subject to withstand uncertain forces.

“The nice thing about the Gaussian process is you can make predictions between the data points that you’ve seen,” Sorokin says. “You can use a machine learning models to get this sort of prediction, and it will give you an accurate prediction. With a Gaussian process, it gives you some notion of how confident it is in that prediction. That confidence is something that we used in looking at this probability in the failure metric we developed.”