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Developed creative and innovative technologies for Microsoft.
Conducted basic and applied research at the intersection of computer science and economics, including prediction markets, wagering, wisdom of crowds, and artificial intelligence.
Conference on Uncertainty in Artificial Intelligence, pp.
Collaborative filtering by personality diagnosis: A hybrid memory- and model-based approach.
Joint Conference of the IEEE Computer and Communications Societies D.
Static and Dynamic Analysis of the Internet's Susceptibility to Faults and Attacks.
A practical liquidity-sensitive automated market maker. ACM Transactions on Economics and Computation, 1(3) Conference version: ACM Conference on Electronic Commerce, 2010Y.
ACM Transactions on Information Systems, 22(4): 540-572 Conference version: ACM A.
Analysis of lexical signatures for improving information persistence on the World Wide Web.
Decision Support Systems, 39(1):87-104 Conference version: ACM Conference on Electronic Commerce, 2003S.-T.
Betting boolean-style: A framework for trading in securities based on logical formulas.
ACM SIGCSE Symposium on Computer Science Education, 26(1), pp. 8998, Istanbul, Turkey, 2012 Guest lecturer, Princeton University, November 2012 Operations Management seminar, NYU Stern School of Business, NY, NY, November 2012 DIMACS, Rutgers University, New Brunswick, NJ, October 2012 Carnegie Mellon University, Pittsburgh, PA, November 2011 e Bay, Santa Clara, CA, June 2011 Wharton Risk Roundtable, Philadelphia, PA, May 2010 Massachussetts Institute of Technology, Cambridge, MA, May 2010 Harvard Business School, Cambridge, MA, March 2009 University of California, Irvine, CA, March 2009 University of Pennsyvania, Philadelphia, PA, March 2009 Morgan Stanley Process Driven Trading, New York, NY, May 2008 Cornell University, Ithaca, NY, December 2008 Duke University, Durham, NC, 2007 University of Chicago, Chicago, IL, 2007 Brooklyn Polytechnic, New York, NY, 2007Co-founded and co-managed a team of thirty researchers and postdocs covering four areas of data science: machine learning, computational social science, the digital economy, and the ethics of data.