Fotios Lygerakis

Fotios Lygerakis is a doctoral student and university assistant at the Chair of Cyber-Physical Systems, University of Leoben, Austria. He focuses on advancing machine learning and robotics, particularly in representation learning, visuotactile fusion, and robot learning through imitation and reinforcement learning. His work aims to enable robots to mimic human learning processes via abstraction and creativity, targeting tactile-rich manipulation tasks and human-robot interaction.

Education: Pursuing a doctoral degree in Cyber-Physical Systems at the University of Leoben.

Research Interests:

• Representation Learning and Visuotactile Fusion using self-supervised methods
• Robot Learning: Reinforcement Learning, Imitation Learning, Sim2Real Transfer
• Human-Robot Interaction and tactile-aware manipulation

Recent Achievements: Received the Best Student Paper Award at the 2024 Ubiquitous Robotics Conference for his work on M2CURL. His research has been presented at venues like ICRA, IROS, and NYU. He is also a contributor to projects like MViTaC and CR-VAE.

Engagement: Served on organizing committees for ECESCON 9 and PETRA 2021, and volunteered at TED AI Vienna 2024. Active in teaching as a Machine Learning lab assistant and through outreach initiatives like Neural Coffee Reading Group.