[PHOTO]             MICHAEL KEARNS

Professor and National Center Chair
Department of Computer and Information Science of the University of Pennsylvania
Founding Director, Warren Center for Network and Data Sciences
Faculty Founder, Penn program in Networked and Social Systems Engineering
Secondary Appointments in Statistics and Operations and Information Management in the Wharton School

509 Levine Hall, 3330 Walnut Street, Philadelphia, PA 19104-6389
Phone: (215)898-7888
Email: mkearns@cis.upenn.edu

Administrative Assistant:
Cheryl Hickey
Phone: (215)898-3538
Email: cherylh@cis.upenn.edu

                       

SITE DIRECTORY

Most of this site is organized as a single flat html file. The links below let you navigate directly to the various subsections.

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


RESEARCH INTERESTS

My research interests include topics in machine learning, algorithmic game theory, social networks, computational finance, and artificial intelligence. I often examine problems in 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 projects, including applications of machine learning to finance, spoken dialogue systems, and other areas. Most recently, I have been conducting human-subject experiments on strategic and economic interaction in social networks.


QUICK LINKS

Warren Center for Network and Data Sciences
Networked and Social Systems Engineering (NETS) Program
Penn-Lehman Automated Trading Project (inactive)
Tribute Day for Les Valiant, May 2009


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. I have secondary appointments in the Statistics and Operations and Information Management (OPIM) departments of the Wharton School. I am the Founding Director of the Warren Center for Network and Data Sciences, where my co-director is Rakesh Vohra. I am the Faculty Founder of Penn Engineering's Networked and Social Systems Engineering (NETS) Program, whose director is Ali Jadbabaie, and whose program's curriculum chair is Zack Ives. I am an active member of Penn's machine learning community PRiML, and am an affiliated faculty member of Penn's Applied Math and Computational Science graduate program. Until July 2006 I was the co-director of Penn's interdisciplinary Institute for Research in Cognitive Science.

With Yuriy Nevmyvaka, I run a trading team at Engineers Gate, a quantitative hedge fund based in New York City.

I currently serve as an advisor to the companies Yodle, Wealthfront, Activate Networks, and RootMetrics. I am also involved in the seed-stage fund Founder Collective. I am a member of the Technical Advisory Board of Microsoft Research Cambridge. I occasionally serve as an expert witness or consultant on technology-related legal and regulatory cases.

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 (later at Rutgers, now at Brown), 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 (later at Penn, now at Google), and included Michael Collins (later at MIT, now at Columbia), Sanjoy Dasgupta (now at UCSD), Yoav Freund (now at UCSD), Rob Schapire (now at Princeton), William Cohen (now at CMU), and Yoram Singer (later at Hebrew University, now at Google). Other friends and colleagues from Labs days include Sebastian Seung (later at MIT, now at Princeton), Lawrence Saul (later at Penn, now at UCSD), Yann LeCun (now at NYU), Roberto Pieraccini (now at SpeechCycle), Esther Levin (now at SAC Capital), Lyn Walker (now at UC Santa Cruz), 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.

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

From June 2009 through September 2013, I helped run a quantitative trading team in the MultiQuant division of SAC Capital in New York City. 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 first a consultant to, and later the head of, a quant prop trading team within the Equity Strategies group of Lehman Brothers in New York City.

I spent most of 2011 on sabbatical in Cambridge, England, where I visited the University of Cambridge Economics Department and was a visiting Fellow at Christ's College. I also spent time visiting Microsoft Research Cambridge.

In the past I have served as an advisor to the startups Convertro (acquired by AOL), Invite Media (acquired by Google), SiteAdvisor (founded by Chris Dixon; acquired by McAfee), PayNearMe (formerly known as Kwedit), and Riverhead Networks (acquired by Cisco). I was also involved in Dixon's startup Hunch (acquired by eBay), and have been a consultant to Bessemer Venture Partners, and a member of the Advanced Technology Advisory Council of PJM Interconnection. and the Scientific Advisory Board of Opera Solutions.


EDUCATION

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 (superb) 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).

Alongside my formal education, I was strongly influenced by being born into an academic family, including my father David Kearns (UCSD, Chemistry); his brother, and my uncle Tom Kearns (Amherst College, Philosophy); their father, and my paternal grandfather, Clyde Kearns (University of Illinois, Entomology); and my maternal grandfather Chen Shou-Yi (Pomona College, History and Literature).


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 was formerly on the steering committee for the Snowbird Conference on Learning (RIP).

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

I am currently a member of the Computer Science and Telecommunications Board of the National Academies.

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


RESEARCH GROUP

Current (alphabetical):

Doctoral student Kareem Amin
Doctoral student Lili Dworkin
Doctoral student Hoda Heidari (jointly advised with Ali Jadbabaie )
Doctoral student Shahin Jabbari
Doctoral student Ryan Rogers (jointly advised with Aaron Roth )
Doctoral student Steven Wu (jointly advised with Aaron Roth )
Research scientist Stephen Judd
Visiting scientist Yuriy Nevmyvaka

Alumni (reverse chronological):

Former doctoral student Mickey Brautbar, currently a postdoc at MIT
Former postdoc Jake Abernethy, now on the University of Michigan CS faculty
Former postdoc Kris Iyer, now on the Cornell ORIE faculty
Former MD/PhD student Renuka Nayak, now a medical resident at UCSF
Former doctoral student Tanmoy Chakraborty, now at Facebook
Former postdoc Umar Syed, now at Google NYC
Former doctoral student Jinsong Tan, now at Citadel
Former postdoc Eugene Vorobeychik, now on the Vanderbilt CS faculty
Former postdoc Giro Cavallo, now at Yahoo! NYC
Former doctoral student Jenn Wortman Vaughan, now at Microsoft Research NYC
Former postdoc Eyal Even-Dar, now at Final Israel
Former doctoral student Sid Suri, now at Microsoft Research NYC
Former postdoc Sham Kakade, now at Microsoft Research New England
Former postdoc Ryan Porter, now at AMA Capital
Former postdoc Luis Ortiz, now on SUNY Stonybrook CS faculty
Former summer postdoctoral visitor John Langford, now at Microsoft Research NYC


TEACHING AND TUTORIAL MATERIAL

Web page for the undergraduate course Networked Life (NETS 112), Fall 2013 and a condensed online version at Coursera.
(See also the Fall 2012,   Fall 2011 (hosted at Lore),   Spring 2010,   Spring 2009,   Spring 2008,   Spring 2007,   Spring 2006,   Spring 2005, and Spring 2004 offerings.)

Web page for MKSE 150: Market and Social Systems on the Internet, Spring 2013, taught jointly with Aaron Roth.

Web page for the graduate seminar No Regrets in Learning and Game Theory, Spring 2013, run jointly with Aaron Roth.
Here are the slides for my STOC 2012 tutorial on Algorithmic Trading and Computational Finance
Web page for a graduate course on Computational Learning Theory, Fall 2012 (jointly taught with Jake Abernethy). Here is an earlier version (jointly taught with Koby Crammer).
Web page for the graduate seminar course Social Networks and Algorithmic Game Theory, Fall 2009
Web page for CIS 620, Fall 2007: Seminar on Foundations of Cryptography.
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/MEDIA

Below are links to some press/media articles related to my work, or in which I am quoted. (Some links are unfortunately now dead.)

Bloomberg News article on HFT and hybrid quant funds, March 2014
Discussions of PAC and SQ learning and their relevance to evolution in Les Valiant's book "Probably Approximately Correct", June 2013
NPR text and audio on Coursera, online education, and Penn, October 2012
Australian radio program "Future Tense" on "The Algorithm", March 2012
Chapter on biased voting experiments in Garth Sundem's book "Brain Trust", 2012.
ScienceNews article on Princeton fish consensus experiments, December 2011.
A profile of and an interview with Les Valiant upon his receiving the 2010 Turing Award, CACM June 2011.
Profile and lecture overview, Christ's College Pieces, Lent Term 2011.
Fiscal Times article on machine learning and technology in trading, March 2011,
Wired Magazine article on algorithmic trading, January 2011, and some more extensive remarks and one-year follow-up on the author's blog.
Science News article on light speed propagation delays in trading, October 2010
Economist article on flash crash autopsy, October 2010
WSJ online post on HFT research, September 2010
Discussion of behavioral social network experiments in Peter Miller's "The Smart Swarm" (Chapter 3, page 139 forward)
Atlantic article on HFT "crop circles", August 2010
Nature News article on "distributed thinking", August 2010
Wall Street Journal article on machine learning in quant trading, July 2010 and a related interview on CNBC
New Scientist article on "Why Facebook friends are worth keeping", July 2010; here is a free reproduction
Philadelphia Business Journal article on the MKSE program and Networked Life, October 2009
Discussion of behavioral social network experiments in Christakis and Fowler's "Connected" (page 165 foward)
Philadelphia Inquirer article on networked voting experiments, March 2009
Science Daily article on networked voting experiments, February 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: ARTICLES

What follows is a listing of (almost) all of my research papers in (approximately) reverse chronological order. For papers with both a conference and journal version, the paper is usually placed by its first (conference) date. Also, as per the honored tradition of the theoretical computer science community, on almost all of the papers below that are primarily mathematical in content, authors are listed alphabetically.

Acronyms for conferences and journals include: AAAI: Annual National Conference on Artificial Intelligence; AISTATS: International Conference on Artificial Intelligence and Statistics; ALT: Algorithmic Learning Theory; COLT: Annual Conference on Computational Learning Theory; EC: ACM Conference on Electronic Commerce; FOCS: IEEE Foundations of Computer Science; HCOMP: AAAI Conference on Human Computation and Crowdsourcing; ICML: International Conference on Machine Learning; IJCAI: International Joint Conference on Artificial Intelligence; ITCS: Innovations in Theoretical Computer Science; 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 (albeit with a bit of time lag), and can be useful for generating bibtex citations. And here is a listing of my publications generated by Google Scholar.

Last Modified: June 18, 2014


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