I am working towards my Ph.D. at the intersection of Reinforcement Learning, Meta-Learning, and AutoML as a doctoral researcher at Leibniz University since October 2021. Previously, I attained my Master's degree from Technische Universität Berlin and EURECOM where my thesis focused on using Meta-Learning and Reinforcement Learning to train an agent to adapt to the playing styles of diverse partners in the game of Hanabi, under the supervision of Dr. Klaus Obermayer.
I am interested in developing generalizable and deployable Reinforcement Learning pipelines that can abstract useful structures from multiple kinds of environments, and then use these structures for prediction, planning, and learning. Hence, I am interested in applying RL to domain adaptation, zero-shot policy transfer, e.t.c.
My long-term goal is to develop autonomous agents that can operate in sparse data regimes and integrate seamlessly into existing value chains fairly and equitably.
