Jim Ang
Initiative Lead
James “Jim” Ang is chief scientist for computing and PNNL’s program lead for DOE's Office of Advanced Scientific Computing Research. His responsibilities include providing senior leadership in high-performance computing and supporting the development of PNNL’s lab-wide computing strategy. Jim is also cultivating opportunities for PNNL to support DOE Office of Science’s long-term priority research directions in microelectronics.
Kevin Barker
Chief Scientist
Kevin J. Barker is a research computer scientist. His research interests include developing modeling techniques for the prediction of application performance and power for large-scale systems, advanced architectures, and runtime software tools for emerging high-performance computing systems. He serves as the principal investigator for the DOE-ASCR-funded Center for Advanced Technology Evaluation (CENATE) project, which explores the impact of emerging and novel computer architecture technologies on future high-performance computing systems and workloads. Prior to joining PNNL in 2010, he worked at Los Alamos National Laboratory (2004-2010) as a member of the Performance and Architecture Laboratory.
Draguna Vrabie
Converged Workloads Projects Lead
Draguna Vrabie is chief scientist in optimization and control at PNNL. Her work at the intersection of control system theory and machine learning is aimed at design of adaptive decision and control systems. Her current focus is on methodologies and algorithms for design and operation of high-performance cyber-physical systems. Prior to joining PNNL in 2015 she was a senior scientist at United Technologies Research Center, East Hartford, Connecticut. Draguna holds a doctorate in electrical engineering from the University of Texas at Arlington, and an ME and BE in automatic control and computer engineering from Gheorghe Asachi Technical University, Iaşi, Romania.
Gokcen Kestor
Heterogeneous Computing Projects Lead
Gokcen Kestor is a senior research scientist in the high-performance computing group at PNNL. Dr. Kestor is also an adjunct assistant professor at the University of California Merced. Her research solves computer science challenges in HPC software, such as scalability, energy efficiency, programmability, and portability. Her research in HPC system software mainly focuses on providing performance and energy efficiency on advanced HPC systems through runtime and compiler optimizations. She has expertise in programming models, power/performance modeling, emerging architectures, compiler, and runtime systems. She is active in the HPC research community as a program committee member of top-tier HPC conferences, and a co-organizer of the Women in High-Performance Computing workshops. She earned a master’s degree and a doctorate in computer science from the Universitat Politecnica de Catalunya in Spain.