[PHOTO]                             MICHAEL KEARNS

Professor of Computer and Information Science
University of Pennsylvania
National Center Chair in Resource Management and Technology
Secondary Appointments in the Wharton School in Operations and Information Management and Statistics

509 Levine Hall
3330 Walnut Street
Philadelphia, PA 19104-6389
Phone: (215)898-7888
Fax: (215)573-8190

Mobile: (201)936-6924
Penn email: mkearns@cis.upenn.edu

CIS administrative assistant:
Cheryl Hickey
Phone: (215)898-3538
Email: cherylh@cis.upenn.edu

                        [PHOTO]

RESEARCH INTERESTS

My research interests include topics in machine learning, artificial intelligence, algorithmic game theory, social networks, and computational finance. I often examine problems from these areas using methods and models from theoretical computer science and related disciplines. While the majority of my work is mathematical in nature, I have also participated in a variety of empirical and experimental work, including applications of machine learning, spoken dialogue systems, and most recently, human-subject experiments in strategic and economic interaction.

SOME QUICK LINKS

Link to Publications
Link to information on the new Market and Social Systems Engineering (MKSE) Program at Penn
Web page for the graduate seminar course Social Networks and Algorithmic Game Theory, Fall 2009
Web page for the undergraduate course Networked Life (CIS 112), Spring 2009.
Web page for CIS 620, Fall 2006: Seminar on Sponsored Search.
Web page for Readings in Finance (Computational and Otherwise)
Web page for the Penn-Lehman Automated Trading Project. (Currently inactive, but hope to revive someday.)
Web page for the Tribute Day for Les Valiant, May 2009

SITE DIRECTORY

Out of either a heightened design aesthetic or laziness (you be the judge), most of this site is organized as a single flat html file. The links below let you navigate directly to the various subsections.

Research Interests
Brief Professional Bio
Educational Background
Editorial and Professional Service
Research Group Members
Teaching and Tutorial Material
Press
Publications

BRIEF PROFESSIONAL BIO

Current:

Since 2002 I have been a professor in the Computer and Information Science Department at the University of Pennsylvania, where I hold the National Center Chair in Resource Management and Technology. I am the Founding Director of Penn Engineering's new Market and Social Systems Engineering (MKSE) Program; my co-director is Ali Jadbabaie. I have secondary appointments in the Statistics and Operations and Information Management (OPIM) departments of the Wharton School. Until July 2006 I was the co-director of Penn's interdisciplinary Institute for Research in Cognitive Science.

I also work closely with a quantitative trading group at SAC Capital in New York City. (For SAC-related inquiries, please email michael.kearns@sac.com.)

I serve as an advisor to the companies Yodle, kaChing, Invite Media, and Kwedit (a payment system for digital content and virtual goods), and am a member of the Advanced Technology Advisory Council of PJM Interconnection. I am also actively involved in the nifty startup Hunch (try it out and contribute your favorite topic!), and in the seed-stage fund Founder Collective and several of its portfolio companies.

The Past:

I spent the decade 1991-2001 in basic AI and machine learning research at Bell Labs and AT&T Labs. During my last four years there, I was the head of the AI department, which conducted a broad range of systems and foundational AI work; I also served briefly as the head of the Secure Systems Research department. The AI department boasted terrific colleagues and friends that included Charles Isbell (now at Georgia Tech), Diane Litman (now at University of Pittsburgh), Michael Littman (now at Rutgers), David McAllester (now at TTI-Chicago), Satinder Singh (now at University of Michigan), Peter Stone (now at University of Texas), and Rich Sutton (now at University of Alberta). Prior to my time as its head, the AI department was shaped by the efforts of a number of notable figures, including Ron Brachman (who originally founded the department; now at Yahoo! Research), Henry Kautz (who led the department before heading to the University of Washington; now at the University of Rochester), and Bart Selman (now at Cornell). Before leading the AI group, I was a member of the closely related Machine Learning department at the labs, which was headed by Fernando Pereira (now also at Penn, currently on leave at Google), and included Michael Collins (now at MIT), Sanjoy Dasgupta (now at UCSD), Yoav Freund (now at UCSD), Rob Schapire (now at Princeton), William Cohen (now at CMU), and Yoram Singer (now at Hebrew University and Google). Other friends and colleagues from Labs days include Sebastian Seung (now at MIT), Lawrence Saul (now at UCSD), Yann LeCun (now at NYU), Roberto Pieraccini (now at SpeechCycle), Esther Levin (now at CCNY), Lyn Walker (now at the University of Sheffield), Corinna Cortes (now at Google), and Vladimir Vapnik (now at Columbia and NEC). Here is a nice photo wall of former AT&T Labs theory and algorithms researchers, compiled by the great David S. Johnson. Suffice to say we all had a great time together.

I spent 2001 as CTO of the European venture capital firm Syntek Capital, and joined the Penn faculty in January 2002.

From May 2007 through April 2009, I led a quantitative trading team at Bank of America in New York City, working on both proprietary and algorithmic trading strategies within BofA's Electronic Trading Services division. From the Spring of 2002 through May 2007, I was both a consultant to and the head of a quant prop trading team within the Equity Strategies group of Lehman Brothers in New York City.

In the past I have served on the technical advisory boards of SiteAdvisor (founded by Chris Dixon; sold to McAfee), Riverhead Networks (sold to Cisco), as a consultant to Bessemer Venture Partners, and as an expert witness/consultant in a few technology-related legal cases.  

EDUCATIONAL BACKGROUND

I did my undergraduate studies at the University of California at Berkeley in math and computer science, graduating in 1985. I received a Ph.D. in computer science from Harvard University in 1989. The title of my dissertation was The Computational Complexity of Machine Learning (see Publications below for more information), and Les Valiant was my (excellent) advisor. Following postdoctoral positions at the Laboratory for Computer Science at M.I.T. (hosted by Ron Rivest ) and at the International Computer Science Institute (ICSI) in Berkeley (hosted by Dick Karp ), in 1991 I joined the research staff of AT&T Bell Labs, and later the Penn faculty (see professional bio above).

EDITORIAL AND PROFESSIONAL SERVICE

In the past I have been program chair of NIPS, AAAI, COLT, and ACM EC. I have also served on the program committees of NIPS, AAAI, IJCAI, COLT, UAI, ICML, STOC, FOCS, and a variety of other acryonyms. I am a member of the NIPS Foundation and the steering committee for the Snowbird Conference on Learning.

I am currently on the editorial boards of Mathematics of Operations Research, Games and Economic Behavior, the Journal of the ACM, and the MIT Press series on Adaptive Computation and Machine Learning. In the past I have also served on the editorial boards of SIAM Journal on Computing, Machine Learning, the Journal of AI Research, and the Journal of Machine Learning Research.

From 2002-2008 I was a member, vice chair and chair of DARPA's Information Science and Technology (ISAT) study group.

RESEARCH GROUP MEMBERS

Current:

Postdoc Giro Cavallo
Postdoc Umar Syed (jointly hosted with Ben Taskar )
Postdoc Eugene Vorobeychik
Research scientist Stephen Judd
Doctoral student Kareem Amin
Doctoral student Mickey Brautbar
Doctoral student Tanmoy Chakraborty (jointly advised with Sanjeev Khanna )
MD/PhD student Renuka Nayak (works primarily in the lab of Vivian Cheung )
Doctoral student Jinsong Tan
Doctoral student David Weiss (jointly advised with Ben Taskar )

Alumni:

Former doctoral student Jenn Wortman Vaughan, now a postdoc at Harvard; joining UCLA CS faculty Fall 2010
Former postdoc Eyal Even-Dar, now at Google
Former doctoral student Sid Suri, now at Yahoo! Research
Former postdoc Sham Kakade, now on the faculty of TTI-Chicago; joining Wharton/Penn Statistics faculty January 2010
Former postdoc Ryan Porter, now at AMA Capital
Former postdoc Luis Ortiz, now at SUNY Stonybrook
Former summer postdoctoral visitor John Langford, now at Yahoo! Research

TEACHING AND TUTORIAL MATERIAL

Web page for a new graduate course on Computational Learning Theory, Fall 2008 (jointly taught with Koby Crammer)
Web page for CIS 620, Fall 2007: Seminar on Foundations of Cryptography.
Web page for Networked Life, Spring 2009. See also the Spring 2008,   Spring 2007,   Spring 2006,   Spring 2005, and Spring 2004 offerings.
Web page for CIS 620, Fall 2006: Seminar on Sponsored Search.
Web page for the graduate seminar CIS 700/04: Advanced Topics in Machine Learning (Fall 2004).
Web page for CIS 700/04: Advanced Topics in Machine Learning (Fall 2003).
Web page for a course on Computational Game Theory (Spring 2003). This was a joint course between CIS and Wharton (listed as CIS 620 and Wharton OPIM 952).
Course web page for CIS 620: Advanced Topics in AI (Spring 2002)
Course web page for CIS 620: Advanced Topics in AI (Spring 1997)
Web page for NIPS 2002 Tutorial on Computational Game Theory.
ACL 1999 Tutorial Slides [Postscript] [Compressed Postscript] [PDF]
Course Outline and Material for 1999 Bellairs Institute Workshop
Theoretical Issues in Probabilistic Artificial Intelligence (FOCS 98 Tutorial) [Postscript] [Compressed Postscript] [PDF]
A Short Course in Computational Learning Theory: ICML '97 and AAAI '97 Tutorials [Postscript] [Compressed Postscript] [PDF]

PRESS

Below are links to press articles related to my work. (Some links are unfortunately now dead.)

Philadelphia Business Journal article on the MKSE program and Networked Life, October 2009
Philadelphia Inquirer article on networked voting experiments, March 2009
The Trade magazine article natural language processing for algorithmic trading, September 2007
Bloomberg Markets magazine article on AI on Wall Street, June 2007
SIAM News article on behavioral graph coloring, November 2006
Philadelphia Inquirer article on network science and NSA link analysis, May 2006
Chicago Tribune article on privacy in blogs and social networks, November 2005
Chronicle of Higher Education article on Facebook and social networks, May 2004
Star-Ledger article on the demise of AT&T Labs, March 2004
Business Week Online article on technology in NASDAQ and NYSE, September 2003
Philadelphia Inquirer article on ISTAR, interdependent security, and games on networks, January 2003
Washington Post article on web-based chatterbots, September 2002
New Scientist article on the Cobot spoken dialogue system, August 2002
Tornado Insider article on DDoS attacks, January 2002 [Cover]
Tornado Insider article on biometric security, January 2002
Audio of COMNET panel "Staving Off Denial-of-Service Attacks and Detecting Malicious Code"
Tornado Insider article on natural language technology, September 2001
Tornado Insider article on robotics, July 2001
Il Sole 24 Ore profile, June 2001 [English Translation]
Corriere Della Sera profile, May 2001 [English Translation]
Associated Press article on software robots, February 2001
New York Times article on TAC, August 2000
New York Times on Cobot, February 2000
TIME Digital Magazine (now Time On) on Cobot, May 2000
Washington Post article on Cobot, December 2000
New York Times article on boosting, August 1999

PUBLICATIONS:BOOKS

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PUBLICATIONS: RESEARCH ARTICLES

What follows is a listing of almost all of my research papers, downloadable in several file formats. I have recently converted to listing them in (approximately) reverse chronological order. For papers with both a conference and journal version, the paper is usually placed by its first (conference) date. Acronyms for conferences and journals include: AAAI: Annual National Conference on Artificial Intelligence; COLT: Annual Conference on Computational Learning Theory; EC: ACM Conference on Electronic Commerce; FOCS: IEEE Foundations of Computer Science; ICML: International Conference on Machine Learning; IJCAI: International Joint Conference on Artificial Intelligence; NIPS: Neural Information Processing Systems; PNAS: Proceedings of the National Academy of Science; SODA: ACM Symposium on Discrete Algorithms; STOC: ACM Symposium on the Theory of Computation; UAI: Annual Conference on Uncertainty in Artificial Intelligence; WINE: Workshop on Internet and Network Economics.

In addition to the list below, this DBLP query or this "faceted" version seem to do a pretty good job of finding my publications that appeared in mainstream CS venues, and can be useful for generating bibtex citations.

Here is what Wordle thinks I work on.

Last Edited: November 18, 2009


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