Emanuel Tewolde
I am a third-year PhD student in the Computer Science Department of Carnegie Mellon University, where I am fortunate enough to be advised by Vincent Conitzer. My work is supported in part by the Cooperative AI PhD Fellowship.
I strive to understand how to enable artificial intelligence and humans to effectively achieve better (social) outcomes in strategic interactions with other agents. More specifically, my current research interests lie in algorithmic game theory and reinforcement learning, with an emphasis on cooperation and coordination of AI systems, trustworthy AI, and AI safety. The tools I enjoy using include mathematical optimization, learning in games, computational complexity, and foundation models.
Prior to CMU, I completed a master’s and bachelor’s degree in mathematics at Imperial College London and the Technical University Darmstadt respectively. In addition to that, I have also worked with the Fraunhofer-Gesellschaft (IEE) on machine learning methods for smarter renewable energy systems.
Feel free to reach out to me under emanueltewolde (at) cmu (dot) edu.
CV, Google Scholar, DBLP
In below, ‘ - αβ - |’ stands for alphabetical author ordering, and ‘*’ stands for equal contribution.
Working Papers
Learning and Computation of Φ-Equilibria at the Frontier of Tractability
Brian Hu Zhang*, Ioannis Anagnostides*, Emanuel Tewolde, Ratip Emin Berker, Gabriele Farina, Vincent Conitzer, Tuomas Sandholm[arXiv]
Expected Variational Inequalities
Brian Hu Zhang*, Ioannis Anagnostides*, Emanuel Tewolde, Ratip Emin Berker, Gabriele Farina, Vincent Conitzer, Tuomas Sandholm[arXiv]
Publications
Computing Game Symmetries and Equilibria That Respect Them
Emanuel Tewolde, Brian Hu Zhang, Caspar Oesterheld, Tuomas Sandholm, and Vincent ConitzerPublished in Association for the Advancement of Artificial Intelligence (AAAI) 2025
Oral (Top 4.6%)
Best Poster Award (out of 674 posters)
[arXiv] [video]
The Value of Recall in Extensive-Form Games
Ratip Emin Berker, Emanuel Tewolde, Ioannis Anagnostides, Tuomas Sandholm, and Vincent ConitzerPublished in Association for the Advancement of Artificial Intelligence (AAAI) 2025
Oral (Top 4.6%)
[arXiv]
Imperfect-Recall Games: Equilibrium Concepts and Their Complexity
Emanuel Tewolde, Brian Hu Zhang, Caspar Oesterheld, Manolis Zampetakis, Tuomas Sandholm, Paul W. Goldberg, and Vincent ConitzerPublished in International Joint Conference on Artificial Intelligence (IJCAI) 2024
[published version] [arXiv]
Game Transformations That Preserve Nash Equilibria or Best-Response Sets
Emanuel Tewolde and Vincent ConitzerPublished in International Joint Conference on Artificial Intelligence (IJCAI) 2024
[published version] [arXiv]
Social Choice Should Guide AI Alignment in Dealing with Diverse Human Feedback
- αβ - | Vincent Conitzer, Rachel Freedman, Jobst Heitzig, Wesley H. Holliday, Bob M. Jacobs, Nathan Lambert, Milan Mossé, Eric Pacuit, Stuart Russell, Hailey Schoelkopf, Emanuel Tewolde, and William S. ZwickerPublished in International Conference on Machine Learning (ICML) 2024
[published version] [arXiv] [video] [Featured on Interconnects]
The Computational Complexity of Single-Player Imperfect-Recall Games
Emanuel Tewolde, Caspar Oesterheld, Vincent Conitzer, and Paul W. GoldbergPublished in International Joint Conference on Artificial Intelligence (IJCAI) 2023
[published version] [arXiv] [video]
Teaching
Taught and supervised 5 – 10 new TAs per semester for the mathematics department