David Haglin has extensive expertise in graph algorithms and graph theory as well as with parallel programming. He’s developed theory-proving theorems about parallel computation complexity of graph problems and worked on many implementations of products that leverage graph computation in both commercial and research prototype domains.
David began as a Senior Scientist and was then promoted to Chief Scientist for High Performance Data Analytics at Pacific Northwest National Laboratory (PNNL) from 2009 to 2016. At PNNL, he worked on large-scale data analytics, graph algorithms, and massively parallel computation platforms. Prior to PNNL, David spent 18 years as a faculty member in Computer Science at Minnesota State University, Mankato (1991-2009.) He began his career at Sperry Corporation working on data communication software from 1983-1991.
David holds M.S. and Ph.D. degrees in Computer and Information Sciences from the University of Minnesota, and a B.A. in Mathematics from Concordia College, Moorhead, MN.