Communications of the ACM
DOE Selects Six Computing Researchers for Early Career Program Funding
The U.S. Department of Energy has selected 84 scientists from across the United States—including 30 from DOE's national laboratories and 54 from U.S. universities—to receive significant funding for research as part of the DOE Office of Science's Early Career Research Program. The program, now in its ninth year, is designed to bolster the United States' scientific workforce by providing support to exceptional researchers during the crucial early career years, when many scientists do their most formative work.
Advanced Scientific Computing Research is one of six Career Research topic areas within the DOE's Office of Science. Six researchers received awards is this area this year.
"Supporting talented researchers early in their career is key to building and maintaining a skilled and effective scientific workforce for the nation. By investing in the next generation of scientific researchers, we are supporting lifelong discovery science to fuel the nation's innovation system," said U.S. Secretary of Energy Rick Perry "We are proud of the accomplishments these young scientists have already made, and look forward to following their achievements in years to come."
Under the program, university-based researchers will receive grants for at least $150,000 per year and researchers based at DOE national laboratories will receive grants for at least $500,000 per year. The research grants are planned for five years and will cover salary and research expenses.
To be eligible for the DOE award, a researcher must be an untenured, tenure-track assistant, or associate professor at a U.S. academic institution or a full-time employee at a DOE national laboratory, who received a Ph.D. within the past 10 years.
The following Advanced Scientific Computing Research grants were awarded this year:
| Principal Investigator | Institution | City, State | Title |
| Prasanna Balaprakash | Argonne National Laboratory | Lemont, IL | Scalable Data-Efficient Learning for Scientific Domains |
| Eric Cyr | Sandia National Laboratories | Albuquerque, NM | Parallel-in-Layer Methods for Extreme-Scale Machine Learning |
| Joshua Levine | University of Arizona | Tucson, AZ | Analyzing Multifaceted Scientific Data with Topological Analytics |
| Paris Perdikaris | University of Pennsylvania | Philadelphia, PA | Probabilistic data fusion and physics-informed machine learning: A new paradigm for modeling under uncertainty, and its application to accelerating the discovery of new materials |
| Omer San | Oklahoma State University | Stillwater, OK | Physics-reinforced machine learning for multiscale closure model discovery |
| Julian Shun | Massachusetts Institute of Technology | Cambridge, MA | Portable Parallel Algorithms and Frameworks for Exascale Graph Analytics |
Other research topics in the Careers Research program are Basic Energy Sciences, Biological and Environmental Research, Fusion Energy Sciences, High Energy Physics, and Nuclear Physics.
Awardees were selected from a large pool of university- and national laboratory-based applicants. Selection was based on peer review by outside scientific experts. This year's announced projects are selections for negotiation of financial award. The final details for each project award are subject to final grant and contract negotiations between DOE and the awardees.
The 84 awardees, their institutions, and titles of research projects are published online.
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