Invited Speakers

Georgia Chalvatzaki leads the PEARL Lab at TU Darmstadt. Her research lies at the intersection of robot learning, planning under uncertainty, and human-robot interaction, with a focus on structured and geometrically-grounded representations for manipulation.

Arne Sachtler's research focuses on manifold-valued motor skills, Riemannian geometry for robot learning, and structure-preserving representations for manipulation, particularly in the context of bimanual and dexterous tasks.

Constantinos Chamzas works on learning-guided motion planning and geometric representations for robot manipulation, with emphasis on Experience-based Planning Domains and structured latent spaces that respect geometric constraints.

Jonathan Kelly leads the Space & Terrestrial Autonomous Robotic Systems (STARS) Laboratory at the University of Toronto. His research focuses on pervasive, persistent, and perceptive autonomous systems, with an emphasis on differential geometric methods in estimation and planning, robust computer vision for navigation, and collaborative mobile manipulation.

Katerina Fragkiadaki's research lies at the intersection of computer vision, machine learning, language understanding, and robotics. Her work focuses on building intelligent embodied agents that acquire predictive world models to reason through physical dynamics and interactions, with an emphasis on representation learning, video understanding, 2D/3D vision-language models, and sim2real robot learning.

Johannes Lachner's research focuses on geometric methods for robot control and manipulation, including task-space control on Lie groups, geometric fabrics, and structured optimization for compliant physical interaction.

Tobias Löw is a postdoctoral scholar advised by Prof. Siddhartha Srinivasa at the Personal Robotics Lab at the University of Washington. His research focuses on geometric representations for robotics, with the goal of enabling robots to better perceive, interact with, and adapt to complex human-centered environments. His work explores how geometry can support efficient computation, safe interaction, and scalable generalization across robotic tasks.