About me

I’m currently pursuing my P.hD in Reinforcement Learning at the Technion Institute of Technology, Israel, under the supervision of Prof. Shie Mannor.

Reinforcement Learning (RL) is a learning paradigm that highly resembles how we, as humans, learn. The agent, i.e., the learning algorithm, learns through interaction with the environment. By observing the current state of the system, it decides what action to take, after which the environment transitions to a new state and produces the agent with a reward. The goal of the agent is to maximize the accumulative reward.

In my research I focus on deep reinforcement learning (DRL), where we use deep learning techniques (neural networks) to solve reinforcement learning problems.

Specifically, I am interested in finding the problems that are unique to DRL (e.g., which occur due to non-linear function approximation) and how they can be solved or mitigated in order to improve empirical performance.