Assistant Professor of Computer Science
Joined department: Fall 2011
Ph.D., Computational and Mathematical Engineering
Stanford University (2009)
M.S., Computational and Mathematical Engineering
Stanford University (2006)
B.S., Computer Science and Mathematics
Harvey Mudd College (2004)
Professor Gleich is interested in how we can utilize matrix algebra to express -- and improve --
algorithms in network analysis and data-based simulation analysis. Matrix algebra is a particularly
attractive paradigm to study these procedures as it often gives rise to efficient computational
procedures in a variety of settings (serial, parallel, streaming). This research straddles a few
different areas and often involves working with large datasets on high performance computing
architectures (e.g. MPI clusters) and data computing architectures (e.g. MapReduce).
Arif Khan, David F. Gleich, Mahantesh Halappanavar and Alex Pothen, "A multithreaded algorithm for
network alignment via approximate matching", Supercomputing 2012,
David F. Gleich and C. Seshadhri, "Vertex neighborhoods, low conductance cuts, and good seeds for
local community methods", KDD2012, 10.1145/2339530.2339628.
Reid Andersen and David F. Gleich and Vahab Mirrokni, "Overlapping clusters for distributed
computation", WSDM2012, doi:10.1145/2124295.2124330.
Last Updated: February 11, 2013 06:24pm