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Jason D. Hartline Assistant Professor Dr. Hartline's current research interests lie in the intersection of the fields of theoretical computer science, game theory, and economics. With the Internet developing as the single most important arena for resource sharing among parties with diverse and selfish interests, traditional algorithmic and distributed systems approaches are insufficient. Instead, in protocols for the Internet, game-theoretic and economic issues must be considered. A fundamental research endeavor in this new field is the design and analysis of auction mechanisms and pricing algorithms. His hobbies include playing sports such as ice hockey, soccer, volleyball, and ultimate; appreciating arts such as fashion, theater, and dance; and participating in sporty-arts such as lindy hop and aerial acrobatics. Dr. Hartline joined the EECS department (and MEDS, by courtesy) in January of 2008. He was a researcher at Microsoft Research, Silicon Valley from 2004 to 2007, where his research covered foundational topic of algorithmic mechanism design and applications to auctions for sponsored search. He was an active researcher in the San Francisco bay area algorithmic game theory community and was a founding organizer of the Bay Algorithmic Game Theory Symposium. In 2003, he held a postdoctoral research fellowship at the Aladdin Center at Carnegie Mellon University. He received his Ph.D. in Computer Science from the University of Washington in 2003 with advisor Anna Karlin and B.S.s in Computer Science and Electrical Engineering from Cornell University in 1997. Publications. (in reverse-chronological order)
Reducing Mechanism Design to Algorithm Design via Machine Learning,
with Nina Balcan, Avrim Blum, and Yishay Mansour.
Selling Banner Ads: Online Algorithms with Buyback,
with Moshe Banaioff and Robert Kleinberg.
Workshop on Ad Auctions 2008
Position Auctions and Non-uniform Conversion Rates,
with Liad Blumrosen and Shuzhen Nong.
Workshop on Ad Auctions 2008
Optimal Mechanism Design and Money Burning,
with Tim Roughgarden.
Optimal Marketing Strategies over Social Networks,
with Vahab Mirrokni and Mukund Sundararajan.
Auctions for Structured Procurement,
with Matthew Cary, Abraham Flaxman, and Anna Karlin.
Book Chapter: Profit Maximization in Mechanism Design,
with Anna Karlin. In Algorithmic Game Theory, Editors: Noam Nisan, Tim Roughgarden, Eva Tardos, and Vijay Vizarani, October 2007.
[web site] (Based loosely on Topics in Algorithmic Game Theory course notes
Algorithmic Pricing via Virtual Valuations,
with Shuchi Chawla and Robert Kleinberg.
Bayesian Optimal No-deficit Mechanism Design,
with Shuchi Chawla, R. Ravi, and Uday Rajan.
Transcript of panel discussion:
Models for Sponsored Search: What are the right questions? Speakers: Kamal Jain, David Pennock, Michael Schwarz, and Rakesh Vohra.
Competitive Auctions,
with Andrew Goldberg, Anna Karlin, Mike Saks, and Andrew Wright,
Games and Economic Behavior, 2006.
Knapsack Auctions,
with Gagan Aggarwal,
On the competitive ratio of the random sampling auction,
with Uriel Feige, Abraham Flaxman, and Robert Kleinberg,
Mechanism Design via Machine Learning,
with Maria-Florina Balcan, Avrim Blum, and Yishay Mansour,
Near-Optimal Pricing in Near-Linear Time,
with Vladlen Koltun,
From Optimal Limited to Unlimited Supply Auctions,
with Robert McGrew,
Derandomization of Auctions,
with Gagan Aggarwal, Amos Fiat, Andrew Goldberg, Nicole Immorlica,
and Madhu Sudan,
Near-Optimal Online Auctions,
with Avrim Blum,
On Profit-Maximizing Envy-Free Pricing,
with Venkat Guruswami, Anna Karlin, David Kempe, Claire Kenyon,
and Frank McSherry,
Collusion-Resistant Mechanisms for Single Parameter Agents,
with Andrew Goldberg,
A Lower Bound on the Competitive Ratio of Truthful Auctions,
with Andrew Goldberg, Anna Karlin, and Mike Saks,
Optimization in the Private Value Model: Competitive Analysis Applied to Auction Design,
Ph.D. Thesis, Aug. 2003.
Envy-Free Auctions for Digital Goods,
with Andrew Goldberg,
Competitiveness via Consensus,
with Andrew Goldberg,
Characterizing History Independent Data Structures,
with Edwin Hong, Alexander Mohr, William Pentney, and Emily Rocke,
Truthful and Competitive Double Auctions,
with Kaustubh Deshmukh, Andrew Goldberg, and Anna Karlin,
Competitive Generalized Auctions,
with Amos Fiat, Andrew Goldberg, and Anna Karlin,
Competitive Auctions for Multiple Digital Goods,
with Andrew Goldberg,
An Experimental Study of Data Migration Algorithms,
with Eric
Anderson, Joe Hall, Michael Hobbes, Anna Karlin, Jared
Saia, Ram Swaminathan, and John Wilkes. Workshop on Algorithm
Engineering,
Competitive Auctions and Digital Goods,
with Andrew Goldberg and Andrew Wright,
On Algorithms for Efficient Data Migration,
with Joe Hall, Anna Karlin, Jared Saia, and John Wilkes,
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