ACM SIGecom: Doctoral Dissertation Award

Doctoral Dissertation Award

The SIGecom Doctoral Dissertation Award recognizes an outstanding dissertation in the field of economics and computation. More details and nomination procedure…

Past and Present Members of the Doctoral Dissertation Award Committee

Ozan Candogan, Shuchi Chawla, Yiling Chen, Nima Haghpanah, Nicole Immorlica, Vahideh Manshadi, Renato Paes Leme, Noam Nisan, Sigal Oren, Ariel Procaccia, Aaron Roth, Inbal Talgam-Cohen, Éva Tardos, Alex Teytelboym, Michael Wellman

Doctoral Dissertation Award Winners

2021
- Ellen Vitercik
  - Automated Algorithm and Mechanism Configuration
  - advised by Maria-Florina Balcan and Tuomas Sandholm, Carnegie Mellon University
  "Ellen's thesis makes extensive contributions toward establishing the rigorous foundations of automated algorithm configuration, where data-driven machine learning and optimization are used to fine tune an algorithm's parameters for application-specific performance guarantees. Her ground-breaking thesis provides among the first provable generalization guarantees for automated algorithm configuration. An important application domain of automated algorithmic configuration analyzed in depth in Ellen's thesis is automated mechanism design where the goal is to design a mechanism from data to optimize for the mechanism's performance, such as revenue. Ellen's thesis includes additional applications of automated algorithmic configuration such as integer programming (linear and quadratic), and computational biology."
- Honorable Mention Manish Raghavan
  - The Societal Impacts of Algorithmic Decision-Making
  - advised by Jon Kleinberg, Cornell University
  "Manish's thesis consists of a set of highly visible and influential papers on topics concerning the societal impacts of algorithmic decision-making. Most notably, his work establishes the fundamental and unavoidable trade-offs between a number of intuitive notions of fairness in prediction-based decision-making. Manish's results, together with a closely related independent discovery, have substantially shaped the research directions in the field of algorithmic fairness. In addition to theory, Manish used qualitative research methods to perform deep, application-focused analyses of the consequences of algorithmic decision making in algorithmic hiring and consumer finance."
- Honorable Mention Mahsa Derakhshan
  - Algorithms for Markets: Matching and Pricing
  - advised by Mohammad Hajiaghayi, University of Maryland
  "Mahsa's thesis designs new models and algorithms for auctions and matching markets. Her work analyzes and improves markets using a mix of tools from operations research, economics, and computer science. Her improvements are in terms of both computational performance and economic value. Mahsa's thesis solves significant open problems, including achieving the first (1-ε) approximation to the stochastic matching problem, a problem with direct application to kidney exchange."
2020
- Manolis Zampetakis
  - Statistics in High Dimensions without IID Samples: Truncated Statistics and Minimax Optimization
  - advised by Constantinos Daskalakis, MIT
  "Manolis's thesis includes stellar theoretical contributions to learning from data that are subject to strategic manipulations (e.g., showing that finding a local approximate min-max equilibria is PPAD-complete) and from data that are truncated or censored. Manolis's work brilliantly exploits connections to high-dimensional probability, harmonic analysis and optimization to provide innovative tools for handling truncated or censored data in high-dimensional settings. This outstanding thesis is likely to have a major impact on game theory, econometrics, machine learning, and statistics."
- Honorable Mention Nikhil Garg
  - Designing Marketplaces and Civic Engagement Platforms
  - advised by Ramesh Johari and Ashish Goel, Stanford University
  "Nikhil's thesis offers wide-ranging methodological contributions to platform design with applications to surge pricing, rating systems, and preference elicitation for participatory budgeting. Nikhil's work combines elegant theoretical modelling with impressive experimental and empirical analysis. His deep engagement with real-world platforms makes his work a wonderful example of applied research on the intersection of operations research, economics, and computer science."
- Honorable Mention Yuan Deng
  - Dynamic Mechanism Design in Complex Environments
  - advised by Vincent Conitzer, Duke University
  "Yuan's thesis pushes the frontiers of dynamic mechanism design in a way that is notable for its combination of technical strength and practical motivation. In his thesis, Yuan develops a new framework for designing robust dynamic mechanisms in complex environments which makes major advances in bridging the theory and practice. His thesis also contains an ingenious statistical test which leads to a metric quantifying the extent to which a mechanism is dynamically incentive compatible. This is an important step towards making dynamic mechanisms transparent."
2019
- Hongyao Ma
  - Mechanism Design for Coordinating Behavior
  - advised by David C. Parkes, Harvard University
  "An impressive combination of theory and practice for complex mechanism design settings — this thesis identifies key problems, develops sophisticated mathematical models to tackle them and ultimately influences the practice in the industry via direct collaborations. Hongyao's work on Spatio-temporal pricing provides key operational insight that has been adopted by ridesharing platforms and is considered one of the best papers in ridesharing by experts in the field. Her work on optimizing trade-offs between participants and societal value also addresses a key problem faced by many companies allocating scarce resources and the solutions identified are both principle and practical."
- Honorable Mention Rediet Abebe
  - Designing Algorithms for Social Good
  - advised by Jon Kleinberg, Cornell University
  "This thesis introduces important new themes to the algorithmic economics community: how can algorithms play a role in increasing access to opportunity for historically underserved populations. Rediet's work on measuring and designing interventions generated practical impact through collaborations with NGOs and the public health community. The work in the thesis also offers the foundations of the emerging area of Mechanism Design for Social Good."
- Honorable Mention Eric Balkanski
  - The Adaptive Complexity of Submodular Optimization
  - advised by Yaron Singer, Harvard University
  "This thesis makes substantial progress in an old and well-studied area of submodular optimization where only very technically hard problems remain. The thesis contains a breakthrough result that provides exponential speedup in parallel runtime of submodular maximization. The new results in Eric's thesis open exciting new areas of inquiry in the intersection of optimization and learning theory."
2018
- Yannai A. Gonczarowski
  - Aspects of Complexity and Simplicity in Economic Mechanisms
  - advised by Sergiu Hart and Noam Nisan, The Hebrew University of Jerusalem
- Honorable Mention Nika Haghtalab
  - Foundation of Machine Learning, by the People, for the People
  - advised by Avrim Blum and Ariel D. Procaccia, Carnegie Mellon University
- Honorable Mention Haifeng Xu
  - Information as a Double-Edged Sword in Strategic Interactions
  - advised by Shaddin Dughmi and Milind Tambe, University of Southern California
2017
- Aviad Rubinstein
  - Hardness of Approximation Between P and NP
  - advised by Christos Papadimitriou, UC Berkeley
- Honorable Mention Rachel Cummings
  - The Implications of Privacy-Aware Choice
  - advised by Katrina Ligett, California Institute of Technology
- Honorable Mention Christos Tzamos
  - Mechanism Design: From Optimal Transport Theory to Revenue Optimization
  - advised by Constantinos Daskalakis, MIT
2016
- Peng Shi
  - Prediction and Optimization in School Choice
  - advised by Itai Ashlagi, MIT
- Honorable Mention Bo Waggoner
  - Acquiring and Aggregating Information from Strategic Sources
  - advised by Yiling Chen, Harvard University
- Honorable Mention James Wright
  - Modeling Human Behavior in Strategic Settings
  - advised by Kevin Leyton-Brown, University of British Columbia
2015
- Inbal Talgam-Cohen
  - Robust Market Design: Information and Computation
  - advised by Tim Roughgarden, Stanford University
2014
- S. Matthew Weinberg
  - Algorithms for Strategic Agents
  - advised by Constantinos Daskalakis, MIT
- Honorable Mention Xi (Alice) Gao
  - Eliciting and Aggregating Truthful and Noisy Information
  - advised by Yiling Chen, Harvard University
2013
- Balasubramanian Sivan
  - Prior Robust Optimization
  - advised by Shuchi Chawla, University of Wisconsin
- Honorable Mention Yang Cai
  - Mechanism Design: A New Algorithmic Framework
  - advised by Constantinos Daskalakis, MIT
- Honorable Mention Sigal Oren
  - An Algorithmic Approach to Analyzing Social Phenomena
  - advised by Jon Kleinberg, Cornell University