Research interests I am interested in embodied intelligence, agents that learn how to act autonomously and perceive the world through egocentric observations. I study computationally efficient methods of training these agents in simulation, as well as problems of sim-to-real transfer. Right now I am actively working on: Highly optimized open-source software for deep reinforcement learning, such as RL algorithms and simulators. Advanced training scenarios such as population-based training and self-play. Reinforcement learning for quadrotor swarms. In the past I also worked on exploration in RL, memory in embodied agents, and stochastic future prediciton.