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I am a PhD candidate in the Computer Science department at Brown University advised by Prof. George Konidaris. My research centers on generalization and transfer in Reinforcement Learning (RL), with the goal of building general and adaptive sequential decision-making agents. I am particularly interested in compositional generalization—the ability to understand and produce novel combinations of known components or concepts—for its tractability and utility in solving increasingly complex tasks. My recent work studies how factored structure can facilitate this type of generalization. I am currently exploring world modeling and model-based RL, specifically addressing questions such as: How can one learn transferable world models? What level of abstraction is suitable for world modeling? When is learning a world model fundamentally preferable to model-free approaches? Prior to pursuing my PhD I completed a M.Sc. in Electrical and Computer Engineering advised by Prof. Aviv Tamar and a B.Sc. in Electrical Engineering and Physics at the at the Technion - Israel Institute of Technology. Outside of research, I enjoy hiking, snowboarding, basketball and traveling. Before beginning my academic journey, I spent two defining years traveling in East Asia, Europe and America. |
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