Robert Rallo
Division Director
Robert Rallo joined PNNL in 2017 and his research background and interests are at the intersection of chemistry and computer science. His scientific contributions and research areas focus on data-driven analysis and modeling of complex systems, machine learning (ML), artificial intelligence (AI), and urban data science.
Draguna Vrabie
Deputy Division Director and Chief Data Scientist
Draguna Vrabie is deputy division director and chief data scientist in the Data Sciences and Machine Intelligence group. Her work is at the intersection of control system theory and machine learning and is aimed at the design of adaptive decision and control systems. Her current focus is on deep learning methodologies and algorithms for design and operation of high-performance, cyber-physical systems.
Prior to joining Pacific Northwest National Laboratory in 2015, she was a senior scientist at United Technologies Research Center in East Hartford, Connecticut. Vrabie holds a doctorate in electrical engineering from the University of Texas at Arlington, and a ME and BS in automatic control and computer engineering from Gheorghe Asachi Technical University, Iaşi, Romania.
Angela Norbeck
Group Lead - Software and Data Systems Engineering Group
Angela Norbeck draws from her years of experience in biological data analysis and data sciences to explore solutions in biosecurity, cybersecurity, and computing. Specific areas of focus in computing include data integration, big data management, using high-performance computing(HPC) for performance optimization, and user interfaces with intelligent controls and monitoring.
Panos Stinis
Group Lead - Computational Mathematics Group
Panos Stinis specializes in scientific computing with current application interests in model reduction of complex systems, singularity detection and tracking, particle filtering, mesh refinement, and ML.
Mahantesh Halappanavar
Group Lead - Data Science Group
Mahantesh Halappanavar conducts research and development in the broad areas of high-performance scientific computing and data sciences. His research has spanned multiple technical foci and includes combinatorial scientific computing; design and implementation of parallel graph algorithms; ML; and application of graph theory and game theory to solve problems in applied domains, such as scientific computing, electric power grids, cybersecurity, and life sciences.
Kevin Barker
Group Lead - High-Performance Computing Group
Kevin Barker drives research in novel computing architectures, cybersecurity, and large-scale performance prediction methods. He leads the advanced architecture testbed capability at PNNL which integrates empirical and predictive analysis to gain insight into the impact of emerging and novel computing technologies. He also conducts research into hardware/software co-design methodologies, bringing together capabilities within the high-performance computing group to design the next generation of specialized architectures and software tools.
