David Gleich
Jyoti and Aditya Mathur Professor of Computer Science
Joined department: Fall 2011
Education
Ph.D., Stanford University, Computational and Mathematical Engineering (2009)
M.S., Stanford University, Computational and Mathematical Engineering (2006)
B.S., Harvey Mudd College, Computer Science and Mathematics (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).
Selected Publications
Arif Khan, David F. Gleich, Mahantesh Halappanavar and Alex Pothen, "A multithreaded algorithm for network alignment via approximate matching", Supercomputing 2012. http://conferences.computer.org/sc/2012/papers/1000a054.pdf
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: Dec 4, 2020 1:55 PM