Presenter

Naoki Shitanda is a PhD student in the Graduate School of Information Science and Technology at the University of Tokyo. His research focuses on deep reinforcement learning for robotics, particularly large-scale learning algorithms in massively parallel simulation environments, robust sim-to-real transfer to real robotic systems, and 3D perception for robot understanding and control. He is interested in building scalable learning systems that enable robots to acquire complex skills autonomously in the real world.