Emanuel Tewolde
Welcome to my academic website! It is work in progress, especially starting from the section “Working Papers”.
I am a second-year PhD student in the Computer Science Department of Carnegie Mellon University, where I am fortunate enough to be advised by Vincent Conitzer and to be part of the Foundations of Cooperative AI Lab (FOCAL).
My current research interests lie in algorithmic game theory and (multi-agent) reinforcement learning. I strive to understand how to enable artificial intelligence and humans to effectively achieve better (social) outcomes in strategic interactions with other agents. The methods I enjoy using include mathematical optimization, complexity theory, learning in games and deep learning.
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 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
Working Papers
Game Transformations that preserve Nash Equilibrium sets and/or Best Response sets
Emanuel Tewolde[arXiv]
Publications
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
[arXiv]
</p> --> </p> -->
Paper Title Number 3
Published in Journal 1
[published version]
This paper is about the number 3. The number 4 is left for future work.
Paper Title Number 2
Published in Journal 1
[published version]
This paper is about the number 2. The number 3 is left for future work.
Teaching
This is a description of a teaching experience. You can use markdown like any other post.
This is a description of a teaching experience. You can use markdown like any other post.