I’m a PhD candidate at the University of Massachusetts. I am also a member of the Autonomous Learning Lab (ALL) and am fortunate to be advised by Prof. Philip Thomas.
My primary interest is in continual learning, a branch of Artificial Intelligence, which aims at teaching machines
new concepts over time. My research is mostly at the intersection of reinforcement learning and machine learning, with a focus on challenges of real-world applications. I enjoy reading and looking out for inspirations from neuroscience as well.
- Our paper on providing high-confidence off-policy variance estimates got accepted at AAAI’21!
- Our paper on ensuring safe policy improvement for non-stationary MDPs got accepted at NeurIPS’20!
- Our papers on (a) Optmizing for the future in non-stationary MDPs, and (b) Evaluating the performance of RL algorithms, got accepted at ICML’20!
- Received Outstanding Student Paper Honorable Mention by AAAI’20 for our paper on Lifelong Learning with a Changing Action Set.
- Our papers on (a) lifelong learning with a changing action set, and (b) RL when all actions are not always available, got accepted at AAAI’20!
- I will be interning at Adobe Research under Sridhar Mahadevan and Georgios Theocharous during Summer 2019.
Click here for all the publications.