Publications can be found here (original link not provided).
Research Experience
Focused on developing learning-based methods for multi-agent robotics, specifically: scaling MARL in partially observable systems, long-horizon planning for multi-agent robotics, and creating human-interpretable communication protocols for MARL methods.
Education
PhD - AeroAstro Department, Massachusetts Institute of Technology (MIT)
Background
PhD candidate in the AeroAstro Department at MIT. Research interests lie in multi-agent robotics, especially in partially observable settings with limited communication bandwidth, and the interpretability of learning-based methods for autonomous navigation.
Miscellany
Enjoys playing musical instruments such as guitar, bass, piano, drums, and recorder, and shares some guitar videos on Instagram. Also interested in sketching, astrophotography, playing tennis, badminton, cricket, and swimming.