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Research Area: Search Technologies |
Profile
Dr. Lang grew up on a farm in Iowa, then attended Grinnell College where he majored in Mathematics. Dr. Lang earned a PhD in Computer Science from Carnegie Mellon University where he worked with Geoffrey Hinton. He also created Oaklisp with Barak Pearlmutter. At NECI in Princeton, he worked on various topics in Learning Theory and Parallel Computation, and ran the Abbadingo DFA learning competition. During the dot-com boom, Lang worked at Fast Forward Networks. At Yahoo!, Dr. Lang's research interests include applications of graph partitioning.
Recent Publications, Projects and News
- Information Theoretic Comparison of Stochastic Graph Models: Some Experiments Kevin J Lang; Konstantin Avrachenkov and Debora Donato and Nelly Litvak, WAW 2009, Springer, 2009 [view abstract]
- An algorithm for improving graph partitions Reid Andersen; Kevin J. Lang, SODA, 2008 [view abstract]
- Statistical Properties of Community Structure in Large Social and Information Networks Jure Leskovec;Kevin Lang;Anirban Dasgupta;Michael Mahoney, WWW, 2008 [view abstract]
- Efficient Discovery of Authoritative Resources Ravi Kumar; Kevin Lang; Cameron Marlow; Andrew Tomkins, ICDE, 2008
- Finding dense and isolated submarkets in a sponsored search spending graph Kevin J. Lang; Reid Andersen, CIKM, ACM, 2007 [view abstract]
- Local Partitioning for Directed Graphs Using PageRank Reid Andersen; Fan Chung; Kevin Lang, WAW, 2007
- Local Graph Partitioning using PageRank Vectors Reid Andersen; Fan Chung; Kevin Lang, FOCS, 2006 [view abstract]
- Fixing two weaknesses of the Spectral Method Kevin J. Lang, NIPS 18, 2006 [view abstract]
- Communities from seed sets Reid Andersen; Kevin J. Lang, WWW, 2006 [view abstract]