Fotios Lygerakis

Fotios Lygerakis is a doctoral student and university assistant at the Department of Cyber-Physical Systems (CPS) at Montanuniversität Leoben, Austria. His research focuses on advancing machine learning and robotics, particularly in representation learning, visuotactile fusion, and reinforcement learning for robotic manipulation. He holds a Diploma in Electrical and Computer Engineering from the Technical University of Crete (2019) and has held roles including teaching assistant at the University of Texas at Arlington, research assistant at Demokritos (Athens), and research intern at Toshiba Research Europe.

His research interests span representation learning, multimodal fusion, reinforcement learning, and healthcare robotics. Notable contributions include work on CR-VAE and M2CURL, earning a Best Student Paper Award at the 2024 Ubiquitous Robotics Conference. Lygerakis actively supervises theses in areas like human-robot interaction and self-supervised learning, and teaches courses on machine learning and deep learning.

Lygerakis maintains active engagement in the scientific community through reviewing for journals/conferences (e.g., IROS, IJRR), organizing workshops, and leading the Neural Coffee Reading Group. He has presented invited talks at institutions like New York University and Technical University of Crete, and his work has been featured in outlets like Computer Vision News.