23 June 2026

On 18.06.2026, our colleague Xiaowen Sun successfully defended her doctoral thesis “Active Clarification in Human-Robot Interaction via Object State Perception and Reasoning”. We congratulate her on her graduation and wish all the best in her next steps! Below is a brief overview of her thesis:

Embodied agents operate in human-centered environments such as homes and restaurants, where Human–Robot Interaction (HRI) is often affected by uncertainty, vagueness, and ambiguity. These challenges become more pronounced when interactions involve fine-grained object states (e.g., clean vs. dirty) rather than object categories alone. This thesis investigates how embodied agents can acquire and process object-state knowledge to enable robust interaction.

Selected publications from her doctorate:

Xiaowen Sun, Cornelius Weber, Matthias Kerzel, Josua Spisak, Stefan Wermter. Uncertainty, Vagueness, and Ambiguity in Human-Robot Interaction: Why Conceptualization Matters. 2nd Interactive AI for Human-Centered Robotics Workshop at the ACM/IEEE International Conference on Human-Robot Interaction (HRI), 2026.

Xiaowen Sun, Xufeng Zhao, Jae Hee Lee, Wenhao Lu, Matthias Kerzel, Stefan Wermter. Details Make a Difference: Object State-Sensitive Neurorobotic Task Planning. ICANN 2024 (Proceedings of the International Conference on Artificial Neural Networks), pp. 261–275, 2024.

Xiaowen Sun, Cornelius Weber, Matthias Kerzel, Tom Weber, Mengdi Li, Stefan Wermter. Learning Visually Grounded Human-Robot Dialog in a Hybrid Neural Architecture. ICANN 2022 (International Conference on Artificial Neural Networks), pp. 258–269, 2022.

Xiaowen Sun, Matthias Kerzel, Mengdi Li, Xufeng Zhao, Paul Striker, Stefan Wermter. StateVLM: A State-Aware Vision-Language Model for Robotic Affordance Reasoning. arXiv 2026.

We thank the committee and colleagues for their support and look forward to seeing Xiaowen’s future contributions to Human-Robot Interaction!