I am a first-year PhD student in Societal Computing in the School of Computer Science at Carnegie Mellon University. I am very fortunate to be advised by Prof. Fei Fang. Prior to CMU, I graduated from Swarthmore College with a B.A. in Mathematics and Computer Science. My CV can be found here.
My research focuses on leveraging data to aid decision making in strategic interactions. Using tools from game theory, optimization, and machine learning, I develop algorithmic solutions to real-world problems in cybersecurity and sustainability. I have also worked on problems in public security, team collaboration, and information elicitation.
I am open to new ideas and possible domains of collaboration. You may reach me at ryanshi[attt]cmu[dottt]edu.
Deep Reinforcement Learning for Green Security Games with Real-Time Information
Yufei Wang, Zheyuan Ryan Shi, Lantao Yu, Yi Wu, Rohit Singh, Lucas Joppa, and Fei Fang
In AAAI-19: the Thirty-Third AAAI Conference on Artificial Intelligence
[Abstract][full version] [AAAI version and source code to be available soon]
Designing the Game to Play: Optimizing Payoff Structure in Security Games
Zheyuan Ryan Shi*, Ziye Tang*, Long Tran-Thanh, Rohit Singh, and Fei Fang
In IJCAI-ECAI-18: the 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence.
[Abstract] [IJCAI version] [full version] [source code]
Optimizing Peer Teaching to Enhance Team Performance
Zheyuan Ryan Shi and Fei Fang
In TEAMAS-17: First International Workshop on Teams in Multiagent Systems, at AAMAS-17
In Autonomous Agents and Multiagent Systems: AAMAS 2017 Workshops, Best Papers, Springer.
Winner of Best Paper
[Abstract] [Springer version]