• R. Srikant, Fredric G. and Elizabeth H. Nearing Endowed Professor, Department of Electrical and Computer Engineering and Professor, Coordinated Science Lab, University of Illinois at Urbana-Champaign
    • Keynote talk: “Potential Games, Generalized Graph Coloring, and Distributed Resource Allocation”

    Consider a wireless network where users are spatially distributed, each user is within communication range of a few other users, and the network is connected. The users have access to multiple channels of varying quality, and the goal of each user is to select a channel and the probability of transmission over that channel in order to either maximize an individual utility or achieve a system-wide fairness objective. We will design and analyze distributed algorithms to solve the problem, using both cooperative and non-cooperative game theory. Joint work with Kobi Cohen and Angelia Nedich.

    • Speaker's bio:

    R. Srikant is the Fredric G. and Elizabeth H. Nearing Professor in the Department of Electrical and Computer Engineering, and a Professor in the Coordinated Science Lab at the University of Illinois at Urbana-Champaign. His research focuses on the application of probability, optimization, and game theory to problems in communication networks, cloud computing and machine learning. He is a coauthor of the book “Communication Networks: An Optimization, Control and Stochastic Networks Perspective.” He is currently the Editor-in-Chief of the IEEE/ACM Transactions on Networking.

  • Rakesh V. Vohra, George A. Weiss and Lydia Bravo Weiss University Professor, Department of Economics and Department of Electrical and Systems Engineering, University of Pennsylvania
    • Keynote talk: “Network Formation and Systemic Risk”

    This paper introduces a model of endogenous network formation and systemic risk. In it, strategic agents form networks that efficiently trade-off the possibility of systemic risk with the benefits of trade. Efficiency is a consequence of the high risk of contagion which forces agents to endogenize their externalities. Second, fundamentally `safer' economies generate much higher interconnectedness, which in turn leads to higher systemic risk. Third, the structure of the network formed depends crucially on whether the shocks to the system are believed to be correlated or independent of each other.This underlines the importance of specifying the shock structure before investigating a given network as a particular network and shock structure could be incompatible.

    • Speaker's bio:

    Professor Vohra is a leading global expert in mechanism design, an innovative area of game theory that brings together economics, engineering and computer science. His economics research in mechanism design focuses on the best ways to allocate scarce resources when the information required to make the allocation is dispersed and privately held, an increasingly common condition in present-day environments. His work has been critical to the development of game, auction and pricing theory — for example, the keyword auctions central to online search engines — and spans such areas as operations research, market systems and optimal pricing mechanisms.

    He formerly taught at Northwestern University, where he was the John L. and Helen Kellogg Professor of Managerial Economics and Decision Sciences in the Kellogg School of Management, with additional appointments in the Department of Economics and the Department of Electrical Engineering and Computer Science. He taught from 1985 to 1998 in the Fisher College of Business at Ohio State University. He earned a Ph.D. in mathematics in 1985 from the University of Maryland, an M.Sc. in operational research in 1981 from the London School of Economics and a B.Sc. (Hon.) in mathematics in 1980 from University College London.

    He came to Penn as part as of the Penn Integrates Knowledge program that President Amy Guttmann established in 2005 as a University-wide initiative to recruit exceptional faculty members whose research and teaching exemplify the integration of knowledge across disciplines. His appointment is shared with the Department of Electrical and Systems Engineering in the School of Engineering and Applied Science.

  • Éva Tardos, Jacob Gould Schurman Professor, Department of Computer Science, Cornell University
    • Keynote talk: “Learning and Efficiency in Games with Dynamic Population”

    We study the quality of outcomes in games when the population of players is dynamically changing, and where participants have to adapt to the dynamic environment. Price of Anarchy has originally been introduced to study the Nash equilibria of one-shot games, but has been extended since to repeated setting, assuming all players use learning strategies, and the environment, as well as the player population is stable. We show that in large classes of games (including congestion games), if players use a form of learning that helps them to adapt to the changing environment, this guarantees high social welfare, even under very frequent changes. Joint work with Thodoris Lykouris and Vasilis Syrgkanis.

    • Speaker's bio:

    Éva Tardos is a Jacob Gould Schurman Professor of Computer Science Professor, at Cornell University, and was department chair 2006-2010. She received her BA and PhD from Eotvos University in Budapest. She has been elected to the National Academy of Engineering, the National Academy of Sciences, the American Academy of Arts and Sciences, is an external member of the Hungarian Academy of Sciences, and is the recipient of a number of fellowships and awards including the Packard Fellowship, the Goedel Prize, Dantzig Prize, Fulkerson Prize, and the IEEE Technical Achievement Award. She was editor editor-in-Chief of SIAM Journal of Computing 2004-2009, and is currently editor of several other journals including the Journal of the ACM and Combinatorica, served as program committee member and chair for many conferences.

    Tardos's research interest is algorithms and algorithmic game theory, the subarea of theoretical computer science theory of designing systems and algorithms for selfish users. Her research focuses on algorithms and games on networks. She is most known for her work on network-flow algorithms, approximation algorithms, and quantifying the efficiency of selfish routing.