Nomination details here: https://aaai.org/about-aaai/aaai-awards/aaai-acm-sigai-doctoral-dissertation-award/aaai-acm-sigai-doctoral-dissertation-award-call/
Winner of 2025 AAAI/ACM SIGAI Joint Dissertation Award
ACM SIGAI and AAAI are pleased to announce the winner of the 2025 AAAI/ACM SIGAI Dissertation Award:
The award goes to Noah Golowich (Ph.D. from Massachusetts Institute of Technology) for the dissertation titled “Theoretical Foundations for Learning in Games and Dynamic Environments”, and Akari Asai (Ph.D. from University of Washington) for the dissertation titled “Beyond Scaling: Frontiers of Retrieval-Augmented Language Models”
The committee also awards the following Honorable Mentions:
Sarah Alyami (Ph.D. from King Fahd University of Petroleum and Minerals; Current Affiliation: Imam Abdulrahman Bin Faisal University) for the dissertation titled “Continuous Sign Language Recognition: Dataset Development and Novel Frameworks”
Thom Badings (Ph.D. from Radboud University) for the dissertation titled “Robust Verification of Stochastic Systems: Guarantees in the Presence of Uncertainty”
Brian Hu Zhang (Ph.D. from Carnegie Mellon University) for the dissertation titled “New Solution Concepts and Algorithms for Equilibrium Computation and Learning in Extensive-Form Games and Beyond”
Winner of 2024 AAAI/ACM SIGAI Joint Dissertation Award
ACM SIGAI and AAAI are pleased to announce the winner of the 2024 AAAI/ACM SIGAI Dissertation Award: The award goes to Shunyu Yao (Ph.D. from Princeton University), whose dissertation “Language Agents: From Next-Token Prediction to Digital Automation” is recognized for foundational contributions to the study and design of autonomous intelligent agents incorporating large language models.
The committee also awards Honorable Mentions to Frederik Kunstner (Ph.D. from the University of British Columbia), and Sewon Min (Ph.D. from the University of Washington)
Frederik Kunstner’s dissertation “Why Do Machine Learning Optimizers That Work, Work?” is recognized for resolving a long-standing open question on the complexity of EM, one of the most widely used AI algorithms, and for theoretical explanations of the behavior of popular neural network optimization routines..
Sewon Min’s dissertation “Rethinking Data Use in Large Language Models” is recognized for pioneering work on the science and engineering of language models, including better understanding in-context learning and designing nonparametric models for improved retrieval capabilities.
Winner of 2023 AAAI/ACM SIGAI Joint Dissertation Award
ACM SIGAI and AAAI are pleased to announce the winners of the 2023 AAAI/ACM SIGAI Dissertation Award: The award is shared by Gabriele Farina (Ph.D. from Carnegie Mellon University) and Jonathan Frankle (Ph.D. from Massachusetts Institute of Technology).
Gabriele Farina’s dissertation “Game-Theoretic Decision Making in Imperfect-Information Games” is recognized for fundamental contributions, in both theory and practice, to learning and equilibrium computation in imperfect-information games.
Jonathan Frankle’s dissertation “The Lottery Ticket Hypothesis: On Sparse, Trainable Neural Networks” is recognized for significantly advancing our understanding of neural network sparsity, pruning, and training dynamics, including the formulation of the lottery ticket hypothesis.
The committee also awards an Honorable Mention to Ulrike Schmidt-Kraepelin (Ph.D. from Technische Universität Berlin), whose dissertation “Models and Algorithms for Scalable Collective Decision Making” is recognized for significant contributions to problems of scaling in computational social choice.
Winner of 2022 AAAI/ACM SIGAI Joint Dissertation Award
ACM SIGAI and AAAI are pleased to announce the winners of the 2022 AAAI/ACM SIGAI Dissertation Award: The award is shared by Alane Suhr (Ph.D. from Cornell University) and Erik Wijmans (Ph.D. from Georgia Tech).
Alane Suhr’s dissertation “Reasoning and Learning in Interactive Natural Language Systems” is recognized for developing foundational algorithms for continual natural language learning through interaction.
Erik Wijmans’ dissertation “Emergence of Intelligent Navigation Behavior in Embodied Agents from Massive-Scale Simulation” is recognized for pioneering advances in reinforcement learning for robotics from ultra-large scale simulations.
Winner of 2021 AAAI/ACM SIGAI Joint Dissertation Award
ACM SIGAI and AAAI are pleased to announce the winner of the 2021 AAAI/ACM SIGAI Dissertation Award is Shibani Santurkar (MIT thesis, currently at Stanford) for her work entitled “Machine Learning Beyond Accuracy: A Features Perspective On Model Generalization”.
Honorable mention: Bryan Wilder (Harvard thesis, currently at CMU) for his work entitled “AI for Population Health: Melding Data and Algorithms on Networks”
Winner of 2020 ACM SIGAI Dissertation Award
ACM SIGAI and AAAI are pleased to announce the winner of the 2020 AAAI/ACM SIGAI Dissertation Award is David Abel, of Brown University for his work entitled A Theory of Abstraction in Reinforcement Learning.
Runner-Up: Abhishek Das, Georgia Institute of Technology for his work entitled Building Agents that Can See, Talk, and Act
Winner of 2019 ACM SIGAI Dissertation Award
ACM SIGAI and AAAI are pleased to announce the winner of the 2019 AAAI/ACM SIGAI Dissertation Award is Jiajun Wu, of the Massachusetts Institute of Technology, for his work entitled Learning to See the Physical World.
Two runners-Up were also honored: Aishwarya Agrawal of the Georgia Institute of Technology for Visual Question Answering and Beyond, and Li Dong of the University of Edinburgh for Learning Natural Language Interfaces with Neural Models. All winners will be honored during AAAI-21.