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New York Computer Science and Economics Day


for Members

New York Computer Science and Economics Day

Monday, November 9, 2009

The New York Academy of Sciences

NYCE 2009 is the Second Annual New York Computer Science and Economics Day. The goal of the meeting is to bring together researchers in the larger New York metropolitan area with interests in Computer Science, Economics, Marketing and Business and a common focus in understanding and developing the economics of internet activity. Examples of topics of interest include theoretical, modeling, algorithmic and empirical work on advertising and marketing based on search, user-generated content, or social networks, and other means of monetizing the internet.

Steering Committee

  • Robert Kleinberg, Cornell University (Committee Chair)
  • Eva Tardos, Cornell University (Committee Chair)
  • Anindya Ghose, New York University, Stern School of Business
  • S. Muthu Muthukrishnan, Google
  • David Pennock, Yahoo! 
  • Sergei Vassilvitskii, Yahoo! 


Presented by


NYCE Day 2008


*Presentation times are subject to change.

9:00 AM     Stable Internet Routing Without Global Coordination
                  Jennifer Rexford, PhD, Princeton University

10:00 AM    Approximations and Truthfulness - The case of Multi-Unit Auctions
                   Shahar Dobzinski, PhD, Cornell University

11:00 AM    Break

11:30 AM    Censored Exploration in Dark Pools
                   Michael Kearns, PhD, University of Pennsylvania

12:30 PM    Lunch On your own

2:30 PM      Rump Session

    • Beibei Li  (Stern School of Business), NYU Towards Designing Ranking Systems for Hotels on Travel Search Engines
    • Sharad Goel (Yahoo! Research), Contract Auctions for Sponsored Search
    • Eyal Carmi (Tel Aviv University and Stern School of Business), Spreading the Oprah Effect: The Diffusion of Exogenous Demand Shocks in Recommendation Networks
    • Mickey Brautbar (University of Pennsylvania), Local Algorithms for Finding Interesting Individuals in Large Networks
    • Aaron Jaggard (Rutgers University), Towards a unified approach to (in)decition, with implications for divergence of game dynamics
    • Vahab Mirrokni (Google Research), Quasi-Proportional Mechanisms: Prior-free Revenue Maximization
    • Ruggiero Cavallo, (University of Pennsylvania) In Auctions, Small Amounts of Altruism Bear Great Fruit
    • Jacomo Corbo (University of Pennsylvania), Designing Optimal Discriminatory and Non-Discriminatory Marketing Strategies in the Presence of Network Effects
    • Peter Booth (Manhattan College), Has Internet Traffic Flow Been Decentralizing Over Time?
    • Soumya Sen (University of Pennsylvania), Dynamics of Network Technology Competition: The Role of Gateways
    • Fiona Maclachlan (Manhattan College), Random Division and the Size Distribution of Business Firms

3:30 PM      Break

4:00 PM      Expressive Rational Choice
                  Larry Blume, PhD, Cornell University

5:00 PM      End of Program


Larry Blume, PhD

Cornell University

Larry Blume is an external professor at the Santa Fe Institute, a visiting research professor at IHS, VIenna, and Goldwin Smith Professor of Economics at Cornell University. He is a Fellow of he Econometric Society. His BA degree in economics is from Washington University in St. Louis, and he received his Ph.D. in economics from the University of California at Berkeley. His current research includes topics in evolutionary finance, social capital, and decision theory.

Shahar Dobzinski, PhD

Cornell University

Shahar Dobzinski is a postdoc at Cornell. He completed his PhD in Summer 2009 at the Hebrew University under the supervision of Prof. Noam Nisan. His main research interest is algorithmic game theory.

Michael Kearns, PhD

University of Pennsylvania

Since 2002, Michael Kearns has been a professor in the Computer and Information Science Department at the University of Pennsylvania, where he holds the National Center Chair in Resource Management and Technology. Dr. Kearns has secondary appointments in the Statistics and Operations and Information Management (OPIM) departments of the Wharton School. Until July 2006, he was the co-director of Penn's interdisciplinary Institute for Research in Cognitive Science. Dr. Kearns also works closely with a quantitative trading group at SAC Capital in New York City. He serves as an advisor to the companies Yodle, kaChing and Invite Media, and is a member of the Advanced Technology Advisory Council of PJM Interconnection. He is also actively involved in the very cool startup Hunch.

Dr. Kearns did his undergraduate studies at the University of California at Berkeley in math and computer science, graduating in 1985. He received a Ph.D. in computer science from Harvard University in 1989 with Les Valiant as his 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 he joined the research staff of AT&T Bell Labs, and later the Penn faculty.

Jennifer Rexford, PhD

Princeton University

Jennifer Rexford is a Professor in the Computer Science department at Princeton University. From 1996-2004, she was a member of the Network Management and Performance department at AT&T Labs--Research. Jennifer is co-author of the book "Web Protocols and Practice" (Addison-Wesley, May 2001). She served as the chair of ACM SIGCOMM from 2003 to 2007. Jennifer received her BSE degree in electrical engineering from Princeton University in 1991, and her MSE and PhD degrees in computer science and electrical engineering from the University of Michigan in 1993 and 1996, respectively. She was the 2004 winner of ACM's Grace Murray Hopper Award for outstanding young computer professional.


Presented by


Academy Friend

National Science Foundation



Stable Internet Routing Without Global Coordination

Jennifer Rexford, PhD, Princeton University

The Internet is the interconnection of tens of thousands of independently-administered networks, each acting in their own self-interest. Yet, these networks must cooperate to compute the paths that traffic traverses from one end of the Internet to the other. Responsibility for stitching the disparate parts of the Internet together falls to interdomain routing---embodied for the past twenty years in the Border Gateway Protocol (BGP). BGP allows each network, or "Autonomous system" (AS), to apply diverse local policies for selecting paths and deciding who else can direct traffic over these paths. In fact, BGP permits ASes to have conflicting policies that can lead to global routing instability, where ASes keep changing their routing decision indefinitely. Yet, in practice, we know that the Internet (mostly) "works." In this talk, we prove that each AS acting in its own self-interest ensures a stable global system. Our results capitalize on the bilateral business relationships between neighboring ASes and the hierarchical structure of the Internet's AS-level topology. We also propose an incrementally-deployable extension to BGP that enables ASes to have more flexible routing policies - including offering customized route selection as a service to their customers - without sacrificing global stability.

Approximations and Truthfulness - The case of Multi-Unit Auctions

Shahar Dobzinski, PhD, Cornell University*

In this talk we study the clash between computational efficiency and truthfulness: are polynomial-time truthful mechanisms better than polynomial-time (non-truthful) algorithms? To simplify the discussion, we restrict our attention to the problem of multi-unit auctions. We present a truthful algorithm that provides an approximation ratio of 2 for this problem, and argue that this is probably the best ratio achievable by a truthful deterministic polynomial-time algorithm. We then show that if randomization is allowed then there exists a polynomial-time randomized truthful (1+epsilon)-approximation algorithm.

*Based on a joint work with Noam Nisan and a joint work with Shaddin Dughmi.

Censored Exploration in Dark Pools

Michael Kearns, PhD, University of Pennsylvania*

Dark pools are a relatively recent type of equities exchange in which transparency is deliberately limited in order to minimize the market impact of large-volume trades. The success and proliferation of dark pools has also led to a challenging and interesting problem in algorithmic trading --- namely, optimizing the distribution of a large trade over multiple competing dark pools. In this work we formalize this as a problem of multi-venue exploration from censored data, and provide a provably efficient and near-optimal algorithm for its solution. This algorithm and its analysis has much in common with well-studied algorithms for exploration-exploitation in reinforcement learning, and is evaluated on dark pool execution data from a large brokerage.

*Joint work with Kuzman Ganchev, Yuriy Nevmyvaka, and Jennifer Wortman Vaughan.

Expressive Rational Choice

Larry Blume, PhD, Santa Fe Institute

According to the pundits, the financial crises was caused by Wall Streets excessive reliance on mathematical models that assume all market participants are rational. Rationality, it is alleged, precludes bubbles, crashes, and all the things we seen in the last few years. So, what exactly is "rationality"? Economists, computer scientists and others have been exploring different notions of rationality, and provided many different models of rational choice. Contemporary rational choice models are much more expressive than their critics contend. This talk will survey some recent developments in decision theory, with particular emphasis on rational choice representations of decision makers who do not reason probabilistically.

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