Assistant Professor at the Electrical and Computer Engineering Department, University of Patras, teaching undergraduate courses: Robotic Systems I, Robotic Systems II, Intelligent Control, and Introduction to Robotics.
Principal Investigator of the NOSALRO project, implemented at the Computational Intelligence Laboratory, Department of Mathematics, University of Patras, in collaboration with Prof. Michael N. Vrahatis.
Robotics Engineer at Ragdoll Dynamics, integrating state-of-the-art model-based control algorithms into Maya characters to improve the workflow of animators.
Leader of the R&D Computer Vision Team at Metargus, a pre-seed funded startup, building a cutting-edge basketball coaching tool.
Taught undergraduate courses 'Introduction to Artificial Intelligence' and 'Robotics and Intelligent Agents' at the Computer Engineering & Informatics Department of University of Patras (2020-2022).
Post-doctoral fellow in Machine Learning and Robotics at the Computer Technology Institute, Patras, collaborating with Prof. Paul Spirakis and Theodoros Komninos.
Post-doctoral fellow in Machine Learning and Robotics at the LASA team, EPFL, under the supervision of Prof. Aude Billard.
Participated in research projects funded by ERC such as 'SAHR' and CHIST-ERA 'CORSMAL'.
Conducted PhD studies supported by the ERC 'ResiBots' project, focusing on enabling autonomous robots to compensate for unknown situations using machine learning techniques and evolutionary computation.
Education
PhD in Robotics and Machine Learning, titled ''Micro-Data Reinforcement Learning for Adaptive Robots'', defended on December 14th, 2018 at University of Lorraine and Inria Nancy, LARSEN Team, supervised by Dr. Jean-Baptiste Mouret.
Background
Robotics and Machine Learning Researcher and Engineer, currently an Assistant Professor at the Electrical and Computer Engineering Department (Systems and Control Division), University of Patras, Greece. Research interests include using evolutionary and machine learning methods combined with simulations to develop trial-and-error methods that work on physical robots.