My research focuses on multi-agent interactions that arise in combating societal challenges, especially in the areas of conservation and public health. These interactions often involve challenges of uncertainty in the environment and the utility functions of the agents, necessitating approaches that handle scarce data. To achieve this end, I combine methodologies from game theory and multi-agent systems with machine learning, robust planning and optimization techniques.
I am Postdoctoral Fellow with Milind Tambe at Teamcore at the Center for Research on Computation and Society at Harvard. I completed my PhD in September 2018 under the supervision of Craig Boutilier at University of Toronto.
I am on the job market this year. My CV is here.
Research interests: decision-making in uncertain multi-agent systems with social good applications (game theory, sequential decision-making, machine learning, optimization, agent-based modeling)
- Two papers on restless-bandit based scheduling of community health workers accepted at AAMAS-21.
- Our paper on dual mandate patrols for green security was accepted at AAAI-21. Update: it was selected as Best Paper Runner-Up!
- Our preprint on efficient contact tracing was just released on medRxiv and NBER. Explainer thread here.
- I have two papers that will appear at NeurIPS 2020: one on using surrogate models to efficiently differentiate through non-convex optimization and another on restless multi-armed bandits applied to the problem of medication adherence monitoring.
- I am hosting the virtual AI for Social Impact Seminar Series at CRCS this fall.
- I am co-organizing the AI for Social Good workshop at IJCAI 2020.
- Fei Fang, Bo Li, and I will be giving a tutorial on work at the intersection of machine learning and game theory at IJCAI 2020.