The long-term goal of my research is to develop a new generation of data-driven decision-making methods, theory, and systems, which tailor artificial intelligence towards addressing pressing societal challenges. To this end, my research aims at:
making deep reinforcement learning more efficient, both computationally and statistically, in a principled manner to enable its applications in critical domains;
scaling deep reinforcement learning to design and optimize societal-scale multi-agent systems, especially those involving cooperation and/or competition among humans and/or robots.