David M. Pennock

New York, NY  USA                                                                        dpennock17      ß Email me

I blog at Oddhead Blog                                                                     @gmail.com     ß

Find me elsewhere on twitter, facebook, and linkedin

 

 

 

Highlights

Currently Assistant Managing Director and Principal Researcher at Microsoft Research NYC

70+ journal and conference publications, including PNAS, Science, IEEE Computer, Theoretical Computer Science, Electronic Commerce Research, Electronic Markets, AAAI, EC, WWW, STOC, KDD, UAI, SIGIR, ICML, NIPS, INFOCOM, SAINT, VLDB

3 patents, 13 patent applications; over 40 presentations

Press interviews include New York Times, Newsweek, Washington Post, The New Yorker, Investors Business Daily, LA Business Journal, Dow Jones/Wall Street Journal

Reports on my research have appeared in Discover Magazine, New Scientist, CNN/Money,
New York Times, E! Online, Slate, Tech TV, Surowiecki’s “The Wisdom of Crowds”

Named Top 35 Technology Innovator Under Age 35 by MIT Technology Review, 2005

 

 

 

 

Research Interests

 Designing, building, and analyzing new online markets, including prediction markets and wagering mechanisms

Topics: economics and computation, artificial intelligence, intelligent markets, prediction markets, wagering, probability, decision theory, machine learning

 

 

Education

Ph.D. Computer Science              University of Michigan, Ann Arbor, MI, Dec 1999

Concentration in Artificial Intelligence; Graduate Certificate in Complex Systems

M.S. Computer Science                               Duke University, Durham, NC, Aug 1994

B.S. Physics, 2nd Major: Computer Science    Duke University, Durham, NC, May 1993

 

 

Activities

Santa Fe Institute Complex Systems Summer School, June 1996

Duke in Cambridge Program in England, Summer 1992

Pi Kappa Alpha Fraternity, 1990–1993; Community Service Chair, 1991–1992

 

 

Honors

Ranked 34th among “Most Influential Scholars in Web and Information Retrieval” by AMiner
ACM SIGIR Test of Time award, Honorable Mention, for “research that has had long-lasting influence”, 2014
Outstanding Paper Award, ACM Conference on Electronic Commerce, 2008

ACM Senior Member, 2006

MIT Technology Review’s TR35: Top 35 Technology Innovator Under Age 35, 2005

Fellowship, Michigan Decision Behavior Consortium, 1998

Best Student Paper Finalist, Decision Analysis Society,1998

Graduated magna cum laude, 1993

Dean’s List, 1989–1993

Golden Key National Honors Society, 1991

Phi Eta Sigma Freshman Honors Society, 1990

 

 

 

Journal and Conference Publications

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Journal and Conference Publications
(cont’d)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Journal and Conference Publications
(cont’d)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Journal and Conference Publications
(cont’d)

 

 

 

 

 

 

R. Freeman, D.M. Pennock, and J. Wortman Vaughan (2017). The double clinching auction for wagering. ACM Conference on Economics and Computation

R. Freeman, S. Lahaie, and D.M. Pennock (2017). Crowdsourced outcome determination in prediction markets. AAAI Conference on Artificial Intelligence

A. Farhadi, M. Hajiaghayi, M. Ghodsi, S. Lahaie, D.M. Pennock, M. Seddighin, S. Seddighin, and H. Yami (2017). Fair allocation of indivisible goods to asymmetric agents. International Conference on Autonomous Agents and Multiagent Systems

R. Cummings, D.M. Pennock, and J. Wortman Vaughan (2016). The possibilities and limitations of private prediction markets. ACM Conference on Economics and Computation

E. Wah, S. Lahaie, and D.M. Pennock (2016). An empirical game-theoretic analysis of price discovery in prediction markets. International Joint Conference on Artificial Intelligence

D.M. Pennock, V. Syrgkanis, and J. Wortman Vaughan (2016). Bounded rationality in wagering mechanisms. Conference on Uncertainty in Artificial Intelligence

H. Heidari, S. Lahaie, D.M. Pennock, and J. Wortman Vaughan (2015). Integrating market makers, limit orders, and continuous trade in prediction markets. ACM Conference on Economics and Computation

N. Devanur, M. Dudik, Z. Huang, and D.M. Pennock (2015). Budget constraints in prediction markets. Conference on Uncertainty in Artificial Intelligence.

N.S. Lambert, J.Langford, J. Wortman Vaughan, Y. Chen, D.M. Reeves, Y. Shoham, and D.M. Pennock (2015). An axiomatic characterization of wagering mechanisms. Journal of Economic Theory, 156: 389-416

Y. Chen, N.R. Devanur, D. Pennock, and J. Wortman Vaughan (2014). Removing arbitrage from wagering mechanisms. ACM Conference on Economics and Computation

W. Kets, D.M. Pennock, R. Sethi, and N. Shah (2014). Betting strategies, market selection, and the wisdom of crowds. AAAI Conference on Artificial Intelligence

D. Rothschild and D.M. Pennock (2014). The extent of price misalignment in prediction markets. Algorithmic Finance 3(1-2): 3-20

A. Othman, D.M. Pennock, D. Reeves, and T. Sandholm (2013). A practical liquidity-sensitive automated market maker. ACM Transactions on Economics and Computation, 1(3)
Conference version: ACM Conference on Electronic Commerce, 2010

M. Dudik, S. Lahaie, D.M. Pennock, and D. Rothschild (2013). A combinatorial prediction market for the U.S. elections. ACM Conference on Electronic Commerce

M. Dudik, S. Lahaie, and D.M. Pennock (2012). A tractable combinatorial market maker using constraint generation, ACM Conference on Electronic Commerce

A. Beygelzimer, J. Langford, and D.M. Pennock (2012). Learning performance of prediction markets with Kelly bettors. International Conference on Autonomous Agents and Multiagent Systems

S. Goel, D.M. Pennock, M. Mahdian, and D.M. Reeves (2012). TrustBets: Betting over an IOU network. International Conference on Autonomous Agents and Multiagent Systems

A. Beygelzimer, J. Langford, and D.M. Pennock (2012). Learning performance of prediction markets with Kelly bettors. International Conference on Autonomous Agents and Multiagent Systems

S. Goel, M. Mahdian, D.M. Pennock, and D.M. Reeves (2012). TrustBets: Operating a prediction market on an IOU network. International Conference on Autonomous Agents and Multiagent Systems

L. Xia and D.M. Pennock (2011). An efficient Monte-Carlo algorithm for pricing combinatorial prediction markets for tournaments. International Joint Conference on Artificial Intelligence: 452-457

D.M. Pennock and L. Xia (2011). Price updating in combinatorial prediction markets with Bayesian networks. Conference on Uncertainty in Artificial Intelligence: 581-588

 

 

S. Goel, J. Hofman, S. Lahaie, D.M. Pennock, and D.J. Watts (2010). Predicting consumer behavior with web search. Proc. of the National Academy of Sciences, 107(41): 17486-17490

S. Goel, D.M. Reeves, D.J. Watts, and D.M. Pennock (2010). Prediction without markets. ACM Conference on Electronic Commerce: 357-366

Y. Chen and D.M. Pennock (2010). Designing Markets for Prediction. AI Magazine, 31(4): 42-52

Y. Chen, S. Dimitrov, R. Sami, D.M. Reeves, D.M. Pennock, R.D. Hanson, L. Fortnow, and R. Gonen (2010). Gaming prediction markets: Equilibrium strategies with a market maker. Algorithmica, 58(4): 930-969

S. Goel, D.M. Reeves, and D.M. Pennock (2009). Collective revelation: A mechanism for self-verified, weighted, and truthful predictions. ACM Conference on Electronic Commerce: 265-274

M. Guo and D.M. Pennock (2009). Combinatorial prediction markets for event hierarchies. International Conference on Autonomous Agents and Multiagent Systems, (1): 201-208

X. Gao, Y. Chen, and D.M. Pennock (2009). Betting on the real line. Workshop on Internet and Network Economics: 553-560

J. Feigenbaum, D.C. Parkes, and D.M. Pennock (2009). Computational challenges in e-commerce. Communications of the ACM, 52(1): 70-74

S. Goel, J. Hofman, J. Langford, D.M. Pennock, and D.M. Reeves (2009). Centmail: Rate limiting via certified micro-donations. Conference on Email and Anti-Spam

N.S. Lambert,  J. Langford, J. Wortman, Y. Chen, D.M. Reeves, Y. Shoham, and D.M. Pennock (2008). Self-financed wagering mechanisms for forecasting. ACM Conference on Electronic Commerce: 170-179. Won Outstanding Paper Award

N.S. Lambert, D.M. Pennock, and Y. Shoham (2008). Eliciting properties of probability distributions. ACM Conference on Electronic Commerce: 129-138

Y. Chen, L. Fortnow, N.S. Lambert, D.M. Pennock, and J. Wortman (2008). Complexity of combinatorial market makers. ACM Conference on Electronic Commerce: 190-199

Y. Chen, S. Goel, D.M. Pennock (2008). Pricing combinatorial markets for tournaments. ACM Symposium on Theory of Computing: 305-314

S. Lahaie, D.C. Parkes, and D.M. Pennock (2008). An expressive auction design for online display advertising. National Conference on Artificial Intelligence: 108-113

Y. Chen, A. Ghosh, R.P. McAfee, and D.M. Pennock (2008). Sharing online advertising revenue with consumers. Workshop on Internet and Network Economics: 556-565

M. Mahdian, R.P. McAfee, and D.M. Pennock (2008). The secretary problem with a hazard rate condition. Workshop on Internet and Network Economics: 708-715

Y. Chen, L. Fortnow, E. Nikolova, and D.M. Pennock (2007). Betting on permutations. ACM Conference on Electronic Commerce: 326-335

S. Lahaie and D.M. Pennock (2007). Revenue analysis of a family of ranking rules for keyword auctions. ACM Conference on Electronic Commerce: 50-56

S.-T. Park and D.M. Pennock (2007). Applying collaborative filtering techniques to movie search for better ranking and browsing. ACM Conference on Knowledge Discovery and Data Mining: 550-559

A. Ghosh, M. Mahdian, D.M. Reeves, D.M. Pennock, and R. Fugger (2007). Mechanism design on trust networks. Workshop on Internet and Network Economics: 257-268

J. Feng, H. Bhargava, and D.M. Pennock (2007). Implementing sponsored search in web search engines: Computational evaluation of alternative mechanisms.  Informs Journal on Computing, 19(1): 137-148

V. Dani, O. Madani, D.M. Pennock, S.K. Sanghai, and B. Galebach (2006). An empirical comparison of algorithms for aggregating expert predictions. Conference on Uncertainty in Artificial Intelligence

S.-T. Park, D. Pennock, O. Madani, N. Good, and D. DeCoste (2006). Naïve filterbots for robust cold-start recommendations. ACM Conference on Knowledge Discovery and Data Mining: 699-705

B. Mangold, M. Dooley, G.W. Flake, H. Hoffman, T. Kasturi, D.M. Pennock, and R. Dornfest (2005). The Tech Buzz Game. IEEE Computer, 38(7): 94-97

Y. Chen, T. Mullen, C.-H. Chu and D.M. Pennock (2005). Information markets vs. opinion pools: An empirical comparison. ACM Conference on Electronic Commerce

A.I. Schein, A. Popescul, L.H. Ungar, and D.M. Pennock (2005). CROC: A new evaluation criterion for recommender systems. Electronic Commerce Research, 5(1): 51-74

D.M. Pennock (2004). A Dynamic pari-mutuel market for hedging, wagering, and information aggregation. ACM Conference on Electronic Commerce

O. Madani, D.M. Pennock, and G.W. Flake (2004). Co-validation: Using disagreement on unlabeled data to validate classification algorithms. Neural Information Processing Systems

E. Servan-Schreiber, J. Wolfers, D.M. Pennock, and B. Galebach (2004). Prediction markets: Does Money Matter? Electronic Markets,14(3)

G.W. Flake and D.M. Pennock (2004). Self-organization, self-regulation, and self-similarity on the fractal web. Chapter in The Colours of Infinity, Clear Press, UK

J. Feigenbaum, L. Fortnow, D.M. Pennock, and R. Sami (2004). Computation in a distributed information market. Theoretical Computer Science
Conference version: ACM Conference on Electronic Commerce, 2003

L. Fortnow, J. Kilian, D.M. Pennock, and M.P. Wellman (2004). Betting boolean-style: A framework for trading in securities based on logical formulas. Decision Support Systems, 39(1):87-104
Conference version: ACM Conference on Electronic Commerce, 2003

S.-T. Park, D.M. Pennock, C.L. Giles, and R. Krovetz (2004). Analysis of lexical signatures for improving information persistence on the World Wide Web. ACM Transactions on Information Systems, 22(4): 540-572
Conference version: ACM Conference on Information Retrieval, 2002

D. Pavlov, E. Manavoglu, D.M. Pennock and C.L. Giles (2004). Collaborative filtering with maximum entropy. IEEE Intelligent Systems, 19(6): 40-48

A. De Bruyn, C.L. Giles, and D.M. Pennock (2004). Offering collaborative-like recommendations when data is sparse: The case of attraction-weighted information filtering. Conference on Adaptive Hypermedia

S.-T. Park, D.M. Pennock, and C.L. Giles (2004). Comparing static and dynamic measurements and models of the Internet's AS topology. Joint Conference of the IEEE Computer and Communications Societies

G.W. Flake, D.M. Pennock, and D.C. Fain (2003). The self-organized web: The yin to the semantic web’s yang. IEEE Intelligent Systems

S. Debnath, D.M. Pennock, S. Lawrence, and C.L. Giles (2003). Information incorporation in online in-game sports betting markets. ACM Conference on Electronic Commerce

K. Dave, S. Lawrence and D.M. Pennock (2003). Mining the peanut gallery: Opinion extraction and semantic classification of product reviews. World Wide Web Conference

D. Pavlov, A. Popescul, D.M. Pennock and L.H. Ungar (2003). Mixtures of Conditional Maximum Entropy Models. International Conference on Machine Learning

S.K. Lam, D.M. Pennock, D. Cosley, and S. Lawrence (2003). 1 Billion Pages = 1 Million Dollars? Mining the Web to Play "Who Wants to be a Millionaire?". Conference on Uncertainty in Artificial Intelligence

S.-T Park, A. Khrabrov, D.M. Pennock, S. Lawrence, C.L. Giles, and L.H. Ungar (2003). Static and Dynamic Analysis of the Internet's Susceptibility to Faults and Attacks. Joint Conference of the IEEE Computer and Communications Societies

A. Popescul, L.H. Ungar, S.Lawrence, and D.M. Pennock (2003). Statistical relational learning for document mining. International Conference on Data Mining, pp. 275-282

D.Y. Pavlov and D.M. Pennock (2002). A maximum entropy approach to collaborative filtering in dynamic, sparse, high dimensional domains. Neural Information Processing Systems

 

E.J. Glover, D.M. Pennock, S.Lawrence, and B.Krovetz (2002). Inferring hierarchical descriptions. Conference on Information and Knowledge Management

D.M. Pennock, G.W. Flake, S.Lawrence, E.J. Glover, C.L. Giles (2002). Winners don't take all: Characterizing the competition for links on the web, Proceedings of the National Academy of Sciences, 99 (8): 5207-5211

D.M. Pennock, S. Debnath, E.J. Glover, C.L. Giles (2002). Modeling information incorporation in markets with application to detecting and explaining events, Conference on Uncertainty in Artificial Intelligence

E. Glover, K. Tsioutsiouliklis, S. Lawrence, D. Pennock, G. Flake (2002). Using web structure for classifying and describing web pages, World Wide Web Conference

S. Chakrabarti, M. Joshi, K. Punera, D.M. Pennock (2002). The structure of broad topics on the Web, World Wide Web Conference

A.I. Schein, A. Popescul, L.H. Ungar, D.M. Pennock (2002). Methods and metrics for cold-start recommendations, ACM Conference on Information Retrieval

D. Cosley, S. Lawrence, D.M. Pennock (2002). REFEREE: An open framework for practical testing of recommender systems using ResearchIndex, Conference on Very Large Data Bases

D.M. Pennock, S. Lawrence, F.Å. Nielsen, C. Lee Giles (2001). Extracting collective probabilistic forecasts from web games, ACM Conference on Knowledge Discovery and Data Mining, pp. 174–183

A. Popescul, L.H. Ungar, D.M. Pennock, S. Lawrence (2001). Probabilistic models for unified collaborative and content-based recommendation in sparse-data environments, Conference on Uncertainty in Artificial Intelligence, pp. 437–444

D.M. Pennock, S. Lawrence, C.L. Giles, F.Å. Nielsen (2001). The real power of artificial markets. Science, 291(5506): 987–988

S. Lawrence, D.M. Pennock, G.W. Flake, R. Krovetz, F.M. Coetzee, E. Glover, F.Å Nielsen, A. Kruger, C.L. Giles (2001). Persistence of web references in scientific research. Computer, 34(2), pp. 26–31

E.J. Glover, G.W. Flake, S. Lawrence, W.P. Birmingham, A. Kruger, C.L Giles, D.M. Pennock (2001). Improving category specific web search by learning query modifications. Symposium on Applications and the Internet, pp. 23–31

D.M. Pennock and M.P. Wellman (2000). Compact securities markets for Pareto optimal reallocation of risk. Conference on Uncertainty in Artificial Intelligence, pp. 481–488

D.M. Pennock, E. Horvitz, S. Lawrence, C.L. Giles (2000). Collaborative filtering by personality diagnosis: A hybrid memory- and model-based approach. Conference on Uncertainty in Artificial Intelligence, pp. 473–480

D.M. Pennock, P. Maynard-Reid, C.L. Giles (2000). A normative examination of ensemble learning algorithms. International Conference on Machine Learning, pp. 735–742

D.M. Pennock, E. Horvitz, C.L. Giles (2000). Social choice theory and recommender systems: Analysis of the axiomatic foundations of collaborative filtering. National Conference on Artificial Intelligence, pp. 729–734

D.M. Pennock and M.P. Wellman (1999). Graphical representations of consensus belief. Conference on Uncertainty in Artificial Intelligence, pp. 531–540

D.M. Pennock (1998). Logarithmic time parallel Bayesian inference. Conference on Uncertainty in Artificial Intelligence, pp. 431–438

D.M. Pennock and M.P. Wellman (1997). Representing aggregate belief through the competitive equilibrium of a securities market. Conference on Uncertainty in Artificial Intelligence, pp. 392–400

D.M. Pennock and Q.F. Stout (1996). Exploiting a theory of phase transitions in three- satisfiability problems. National Conference on Artificial Intelligence, pp. 253–258

D.M. Pennock and M.P. Wellman (1996). Toward a market model for Bayesian inference. Conference on Uncertainty in Artificial Intelligence, pp. 405–413

C. Connelly, A.W. Biermann, D. Pennock, P. Wu (1996). Homestudy software: Flexible, interactive and distributed software for independent study. ACM SIGCSE Symposium on Computer Science Education, 28(1), pp. 63–67

C. Connelly, A.W. Biermann, D. Pennock, P. Wu (1996). Homestudy software: Complementary systems for computer science courses. Computer Science Education, 7, pp. 53–71

A.W. Biermann, A.F. Fahmy, C. Guinn, D. Pennock, D. Ramm, P. Wu (1995). A Computer animated system for demonstrating hardware and software principles. Journal of Computing in Small Colleges, 10(3), p. 34.

A.W. Biermann, D. Ramm, D. Pennock, A.F. Fahmy, P. Wu (1994). Visualizing computation: Full color and motion demonstration of computer mechanisms. National Conference on College Teaching and Learning

A.W. Biermann, A.F. Fahmy, C. Guinn, D. Pennock, D. Ramm, P. Wu (1994). Teaching a hierarchical model of computation with animation software in the first course. ACM SIGCSE Symposium on Computer Science Education, 26(1), pp. 295–299

 

 

 

Other Publications

D.M. Pennock and R. Sami (2007). Computational aspects of prediction markets. In Algorithmic Game Theory (N. Nisan, T. Roughgarden, E. Tardos, V. Vazirani, editors), Cambridge University Press.

Y. Chen, L. Fortnow, E. Nikolova, and D.M. Pennock (2007). Combinatorial betting. ACM SIGecom Exchanges, 7(1): 61-64

D.M. Pennock (2004). The Eudaemonic Pie: A review. AI Magazine, 25(2): 125-128

D.M. Pennock (2004). Conference report: The fifth ACM conference on electronic commerce. SIGecom Exchanges, 5(1): 48–56

D.M. Pennock (2001). NP markets, or How to get everyone else to solve your intractable problems. Workshop on Economic Agents, Models, and Mechanisms at the International Joint Conference on Artificial Intelligence, pp. 89–98

D.M. Pennock (2001). Conference report: The second ACM conference on electronic commerce. SIGecom Exchanges, 2(1): 33–38

P. Rusmevichientong, D.M.Pennock, S. Lawrence, C.L. Giles (2001). Methods for sampling pages uniformly from the World Wide Web, AAAI Fall Symposium on Using Uncertainty Within Computation

D.M. Pennock and M.P. Wellman (1999). The observability of independence under monetary-based elicitation. Workshop on Conditional Independence Structures and Graphical Models, pp. 56–57

 

Patents

Granted

Patent no. 8,566,205 System and method of making markets for a finite subset of orders placed across continuous and countably infinite outcome spaces

Patent no. 8,527,353 Method and apparatus for administering a bidding language for online advertising

Patent no. 8,166,029 System and method for identifying media content items and related media content items

Patent no. 7,788,158: Dynamic pari-mutuel market

Patent no. 7,457,768: Methods and apparatus for predicting and selectively collecting preferences based on personality diagnosis

Patent no. 7,165,024: Inferring hierarchical descriptions of a set of documents

 

Applications

20160125691 Computer system for multiple user, multiple event real-time online wagering

20150213510 Framework that facilitates user participation in auctions for display advertisements

20140379462 Real-time prediction market

20140122316 Concept valuation in a term-based concept market

20130253994 Systems and methods for micro-payments and donations

20100070322 Method and apparatus for administering a bidding language for online advertising

20100058249 System and method for providing a graphical user interface for prediction markets

20090254475 Prediction market making method and apparatus

20100070322 Method and apparatus for administering a bidding language for online advertising

20100058249 System and method for providing a graphical user interface for prediction markets

20090198613 Method and apparatus for group decision making

20090070873 Safe web based interactions

20090024510 System and method of making markets for a finite subset of orders placed across continuous and countably infinite outcome spaces

20080306819 System and method for shaping relevance scores for position auctions

20080220855 System and method for permutation betting

20080133347 System and method for providing semantic captchas for online advertising

20080133321 System and method for measuring awareness of online advertising using captchas

20050021461 Term-based concept market

20050021442 Term-based concept instruments

20050021441 Concept valuation in a term-based concept market

 

 

Selected Presenta-tions

Smarter Markets
Guest lecturer, Yale University, New Haven, CT, November 2017
Microsoft Techfest, Redmond, WA, March 2017
Cornell University, Ithaca, NY, September 2012

Invited Panelist, UN Youth Assembly, New York, NY, August 2017

Kelly Betting

      Rutgers University, New Brunswick, NJ, April 2017
Microsoft Hack Day, New York, NY, January 2015
Guest lecturer, Harvard University Computer Science, Cambridge, MA, December 2012

Invited Panelist, Workshop on Social Computing and User-Generated Content at EC’15, Portland, Oregon, June 2015

Guest lecturer, Duke University Computer Science course 290.4/590.4, Durham, NC, Feb 2015

Wagering Mechanisms

      Invited Speaker, Cornell Workshop on Computational Social Science, Ithaca, NY, Sep 2015

      Duke University, Durham, NC, February 2015

The extent of price misalignment in prediction markets, Stanford University, April 2013

A Combinatorial Prediction Market for the U.S. Elections

      University of Southern California, Game Theory & Human Behavior Symposium, Apr 2013

      University of California, Irvine, Conference on Wisdom of Crowds, April 2013

The Wisdom of Crowds, Delivered to the Masses
Keynote Speaker, DAGGRE Workshop, George Mason University, March 2012
AI/ML Seminar, University of Maryland, College Park, MD, May 2012

Designing Markets for Prediction

      Semi-Plenary Speaker, GAMES, 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
eBay, Santa Clara, CA, June 2011
Wharton Risk Roundtable, Philadelphia, PA, May 2010

Market Madness: Implementing a 9.2 quintillion outcome prediction market
Google, New York, NY, January 2010
Harvard University, Cambridge, MA, February 2010
Northwestern University, Evanston, IL, April 2010
New York University, New York, NY, November 2010

Crowdsourcing predictions
University of Texas, Austin, TX, March 2011
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

The automated economy
University of Pennsylvania, Philadelphia, PA, March 2009
Stanford University, Stanford, CA, March 2009
Yahoo! Big Thinkers India, Bangalore, India, June 2009 (over 500 attendees)
Microsoft Research, Redmond, WA, January 2009

The evolution of online advertising. NBER Working Group on Market Design, Boston, MA, May 2009

 

 

 

 

Selected Presenta-tions (cont’d)

Combinatorial betting
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, 2007

Prediction markets and the wisdom of crowds. Symposium on Statistical Challenges in Electronic Commerce Research, July 2007 (Keynote Speaker)

Information and complexity in securities markets. New York University Stern School of Business, New York, NY, November 2006

Markets in uncertainty: Risk, gambling, and information aggregation
Tutorial at National Conference on Artificial Intelligence (AAAI), San Jose, CA, July 2004
Tutorial at ACM Conference on Electronic Commerce, San Diego, CA, June 2003

A Dynamic pari-mutuel market for hedging, wagering, and information aggregation
Microsoft Research, Redmond, WA, July, 2004
University of Michigan, Ann Arbor, MI, March, 2004

Sports betting markets: Characteristics and information aggregation. International Conference on Gambling and Risk Taking, Vancouver, Canada, May 2003

Information and forecast accuracy in markets and market games.
Google, Inc., Moutain View, CA, September 2002
Overture Services, Inc., Pasadena, CA, August 2002

Modeling information incorporation in markets and market games. Markets and Decisions Workshop, Arlington, VA, June 2002

Semantic explanations of market forecasts. Controlled Market Economies Symposium, Cambridge, MA, May 2002

The power of play: Efficiency, information aggregation, and forecast accuracy in market games. Institute for Operations Research and the Management Sciences National Meeting, Miami, FL, November 2001

Maximizing information, optimizing risk, and leveraging forecasts in securities markets. NEC Research Symposium, Bonn, Germany, May 2001

Recommender systems. Penn State eBusiness Research Center Academic Workshop on Personalization Issues in e-Business, Arlington, VA, April 2001

Winners don’t take all: A model of web link accumulation. Workshop on Data Mining and Learning on the Web at the 14th Conference on Neural Information Processing Systems, Breckenridge, CO, December 2000

E-markets and uncertainty, or What Bayesians can learn by watching market prices. Microsoft Research, Redmond, WA, June 2000

Introduction to auctions. University of Pennsylvania, Philadelphia, PA, April, 2000

Group Coordination: A History of Paradox and Impossibility.
NEC Research Institute, Princeton, NJ, February 2000
Microsoft Research, Redmond, WA, August, 1998

Efficient representations for aggregate belief and compact securities markets. Institute for Operations Research and the Management Sciences National Meeting, Philadelphia, PA, November 1999

 

 

 

 

 

 

                                                                                                  

Employment History

Assistant Managing Director and Principal Researcher
                                        
Microsoft Research, New York, NY, May 2012 to Present

Co-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. Conducted basic and applied research at the intersection of computer science and economics, including prediction markets, wagering, wisdom of crowds, and artificial intelligence. Developed creative and innovative technologies for Microsoft. Published in top journals and conferences; served the academic community.

 

Principal Research Scientist
                                            
Yahoo Research, New York, NY, Nov 2002 to May 2012

Managed a research group focused on algorithmic economics. Conducted basic and applied research on prediction markets, auctions, advertising, and artificial intelligence.

 

Research Scientist
                           
NEC Laboratories America, Princeton, NJ, Oct 1999 to Oct 2002

Conducted research on information markets, Web games, recommender systems, Web hyperlinks, social networks, consensus Bayesian networks, and ensemble machine learning

Adjunct Assistant Professor of Computer Science and Engineering
                                    
Pennsylvania State University, State College, PA, Jun 2001

Taught CSE 597B, Computational aspects of e-commerce

Research Intern            Microsoft Research, Redmond, WA, Jun 1998 to Aug 1998

Conducted research on impossibility theorems in group coordination, recommender systems, and Bayesian networks

Research Assistant  University of Michigan, Ann Arbor, MI, Sep 1995 to May 1999

Conducted research on computationally efficient and decentralized mechanisms for aggregating information using markets

Teaching Assistant  University of Michigan, Ann Arbor, MI, Sep 1994 to Dec 1994

Taught CS 380: Data Structures and Algorithms

Research Assistant                 Duke University, Durham, NC, Sep 1993 to Aug 1994  

Co-developed an educational software program titled “This is How a Computer Works”, currently still in use at Duke University and elsewhere.

 

 

Academic Service

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Academic Service (cont’d)

Co-Editor, ACM Transactions of Economics and Computation, 2017-present; Economic Inquiry, 2008-11; ACM Transactions on Internet Technology, 2006-8

Co-Founder, ACM Transactions on Economics and Computation

Chair, ACM Special Interest Group on Electronic Commerce, 2007-2011

Chair, ACM SIGecom Test of Time Award committee, 2013-2017

Associate Editor, ACM Transactions of Economics and Computation, 2011-2017

Program Co-Chair, ACM Conference on Electronic Commerce, 2006

General Chair, Auctions, Market Mechanisms and their Applications, 2009 (inaugural year)

Track Co-Chair, International World Wide Web Conference, 2002, 2008, 2013

Member, ACM SIGEcom Officers Nominating Committee, 2015

Member, ACM SIG Governing Board, 2011-2013

Member, DIMACS Executive Committee & Council, Rutgers University, 2012-present

Panelist, NSF Program on the Interface between Computer Science and Economics & Social Sciences, 2012

Organizing Committee

Ad Auctions Workshop (a workshop series I co-founded) 2005,2007,2009; Prediction Markets Workshop (a workshop series I co-founded) 2007,2008; DIMACS Workshop on Information Markets, 2005; Session on Markets in Uncertainty at the Institute for Operations Research and the Management Sciences National Meeting, 2001; Workshop on Data Mining and Learning on the Web, 2000

Senior Program Committee

ACM Conference on Electronic Commerce, 2009,2013,2014,2017,2018; AAAI Conference on Artificial Intelligence, 2017, 2018; International Joint Conference on Artificial Intelligence, 2013,2016; Conference on Uncertainty in Artificial Intelligence, 2003

Program Committee

International Joint Conference on Artificial Intelligence 2003,2005,2009,2011; Auctions, Market Mechanisms and their Applications, 2011; CrowdConf, 2010; Recommenders, 2008; International World Wide Web Conference, 2005,2015; ACM Conference on Economics and Computation (was Electronic Commerce), 2004,2007-2011,2016; Conference on Uncertainty in Artificial Intelligence, 2000-2009,2011,2013,2014,2016,2017; Conference on Email and Anti-Spam, 2004,2005; Conference on Very Large Databases, 2005; ACM Conference on Knowledge Discovery and Data Mining 2003,2008; National Conference on Artificial Intelligence, 2002,2005,2008; International Joint Conference on Autonomous Agents and Multi-Agent Systems, 2002,2003,2012; Web Dynamics Workshop at the International World Wide Web Conference, 2002; Workshop on Agent Mediated Electronic Commerce at the International Joint Conference on Autonomous Agents and Multi-Agent Systems, 2002,2003; Workshop on Economic Agents, Models, and Mechanisms at the 17th International Joint Conference on Artificial Intelligence, 2001; Workshop on Internet Bots: Systems and Applications at the 12th International Conference on Database and Expert Systems Applications, 2001; International Symposium on Imprecise Probabilities and Their Applications, 2001

 

 

Other Peer Reviewing Services

Artificial Intelligence; Journal of Artificial Intelligence Research; Proceedings of the National Academy of Sciences; Algorithmic Finance; Journal of Machine Learning Research; ACM Transactions on Information Systems; IEEE Internet Computing; IEEE Intelligent Systems; IEEE Transactions on Knowledge and Data Engineering; Decision Analysis; Journal of Parallel and Distributed Computing; Management Science; Organizational Behavior and Human Decision Processes; ACM Conference on Electronic Commerce, 2005; National Conference on Artificial Intelligence, 2002; International Joint Conference on Autonomous Agents and Multi-Agent Systems, 2002; International Joint Conference on Artificial Intelligence, 1999, 2001; Conference on Uncertainty in Artificial Intelligence, 1998, 1999; International Conference on Distributed Computing Systems, 199

Professional Society Memberships

Senior Member, Association for Computing Machinery (ACM)
American Association for Artificial Intelligence (AAAI)

Scientists co-Managed
As Assistant Managing Director of Microsoft Research New York City, I co-managed thirty researchers over five years, participating in all evalutations and promotions.

Scientists Managed
Arpita Ghosh (now tenured professor at Cornell)
Sebastien Lahaie (now at Google)
Mohammad Mahdian (now at Google)
Daniel Reeves (now co-founder of Beeminder.com)

Students Managed or Co-Managed

     Rachel Cummings, Caltech
Abe Othman (dissertation committee) and Nisarg Shah, Carnegie Mellon
Mingyu Guo, Lirong Xia, and Rupert Freeman, Duke
Alice Gao, Harvard
Da
n Cosley and Shyong Lam, U. Minnesota
Varsha Dani, U. Chicago
Kushal Davé and Rahul Sami, Yale
Sandip Debnath, Jane Feng, Seung-Taek Park, and Secil Ugurel, Pennsylvania State
Rodrigo Lopes Cançado Fonse
ca, U. Federal de Minas Gerais
Eric Glover, Quang Duong, and Elaine Wah, U. Michigan
Hoda Heidari,
A. Khrabrov, Alexandrin Popescul, and Jenn Wortman Vaughan, U. Pennsylvania
Finn Årup Nielsen, Technical U. Denmark
Nicolas Lambert & Paat Rusmevichientong, Stanford
Sumit Sanghai, U. Washington

 

Academic Service (cont’d)

Postdocs Managed or co-Managed

Ruggiero Cavallo (now Researcher at Yahoo Research)
David Rothschild (now Researcher at Microsoft Research)
Yiling Chen (now tenured Professor at Harvard University)
Seung-Taek Park (now head of AI Labs, Shinhan Card Co.)
Tracy Mullen (was Assistant Professor at
Penn State University; now at AccuWeather)
Dmitry Pavlov (now VP at Walmart)
Sarah Bird (now at Facebook)
Ceren Budak (now Assistant Professor at University of Michigan)
Tzu-Kuo Huang (now at Uber Research Pittsburgh)
Thomas Pajor (now at Apple)
Amit Sharma (now Researcher at Microsoft Research India)
Vasilis Syrgkanis (now Researcher at Microsoft Research New England)
Akshay Krishnamurthy (now Assistant Professor at University of Massachussetts-Amherst)
Ashton Anderson (now Assistant Professor at University of Toronto)
Raf Frongillo (now Assistant Professor at University of Colorado)
Andrew Mao (now Assistant Professor at Aarhus University)
Etan Green (now Assistant Professor at University of Pennsylvania)
Hussam Abu-Libdeh (now at Jet.com)
Solon Barocas (now Assistant Professor at Cornell)
Haipeng Luo (now Assistant Professor at University of Southern California)
Furong Huang (now Assistant Professor at University of Maryland)
Chicheng Zhang
Dean Knox (will be Assistant Professor at Princeton University)
James Wright
Jia Liu (will be Assistant Professor at University of Hong Kong)
Junchen Jiang
Ming Yin (will be Assistant professor at Purdue University)
Nan Jiang (will be Assistant Professor at University of Illinois at Urbana-Champaign)
Steven Wu (will be Assistant Professor at University of Minnesota)
Timnit Gebru

 

Technical Background

Computer Science

Artificial Intelligence
Economics and computation, recommender systems, machine learning, information retreival, decision theory, Bayesian networks, game theory, complex systems, constraint satisfaction, satisfiability, and neural networks

Theory
Parallel algorithms, cellular automata, and computational complexity

Languages
C++, C, PERL, PASCAL, PROLOG, LISP, C*, BASIC, Fortran, assembly, SuperCard, others

Physics

Chaos, non-linear dynamics, quantum mechanics, relativity, optics, holography, percolation theory, thermal (statistical) physics, electronics, classical dynamics, and electricity and magnetism

Math

Probability, non-linear time series analysis, differential equations, financial engineering, fractals, topology, linear algebra, and calculus

 

 

 

 

References

Available on request