I am currently a Postdoctoral Research Associate in the Knowledge Technology Group at Universität Hamburg, with Prof. Stefan Wermter. My research focuses on developing data-efficient deep reinforcement learning algorithms for robot motor control by applying biological principles of self-organization and intrinsic motivation. I also work on meta-decision making, strategy selection and adaptive integration of model-based and model-free control for robot skill learning. My research interests include:
Announcements & News:
Jul 2021 - My paper titled "Behavior Self-Organization Supports Task Inference for Continual Robot Learning" was accepted to IROS 2021.
Apr 2021 - Our paper titled "Improving Model-Based Reinforcement Learning with Internal State Representations through Self-Supervision" was accepted to IJCNN 2021.
Nov 2020 - My article titled "Improving robot dual-system motor learning with intrinsically motivated meta-control and latent-space experience imagination" was published in Robotics and Autonomous Systems.
May 2020 - I successfully defended my PhD thesis "Intrinsically Motivated Actor-Critic for Robot Motor Learning" with magna cum laude.
Dec 2019 - Invited talk on "Robot Motor Learning with Intrinsically Motivated Actor-Critic" at TU-Delft, the Netherlands.