Communications of the ACM
Seven CS Researchers Selected For Recovery Act Early Career Funds
Seven computer science researchers supported by the U.S. Department of Energy's Office of Advanced Scientific Computing Research (ASCR) are among 69 scientists who will share $85 million in funding under the American Recovery and Reinvestment Act for five-year research grants as part of the DoE's new Early Career Research Program. Secretary Steven Chu announced the recipients last month for research ranging from climate modeling to energy efficient supercomputing.
The Early Career Research Program is designed to support the development of individual research programs of outstanding scientists early in their careers and to stimulate research careers in the disciplines supported by the DoE Office of Science. The minimum award size is $150,000 per year for five years for universities and $500,000 per year for five years for DOE national laboratories. In addition to ASCR, areas of study include Biological and Environmental Research, Basic Energy Sciences, Fusion Energy Sciences, High Energy Physics, and Nuclear Physics.
The seven ASCR-supported researchers and their areas of study are:
- Grigory Bronevetsky, Lawrence Livermore National Laboratory, "Reliable High Performance Peta- and Exa-Scale Computing;"
- Patrick Yin Chiang, Oregon State University, "Sustainable Silicon — Energy-Efficient VLSI Interconnect for Extreme-Scale Computing;"
- Christiane Jablonowski, University of Michigan, "Introducing Enabling Computational Tools to the Climate Sciences: Multi-Resolution Climate Modeling with Adaptive Cubed-Sphere Grids;"
- Youssef Marzouk, Massachusetts Institute of Technology, "Predictive Modeling of Complex Physical Systems: New Tools for Uncertainty Quantification, Statistical Inference, and Experimental Design;"
- Kalyan Perumalla, Oak Ridge National Laboratory, "ReveR-SES: Reversible Software Execution Systems;"
- Michelle Strout, Colorado State University, "Separating Algorithm and Implementation via Programming Model Injection (SAIMI);"
- Anil Vullikanti, Virginia Polytechnic Institute and State University, "Diffusion on Complex Networks: Algorithmic Foundations."
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