I am currently a Postdoctoral Researcher at Centre Borelli, École normale supérieure (ENS) Paris-Saclay, working with the team of Prof. Laurent Oudre on ML/DL methods for time series. I am passionate about the efficient and scalable application of ML to solving real-world problems, involving complex and dynamically evolving data, particularly for industrial and engineering applications. In November 2023, I completed my PhD in Computer Science & Machine Learning at École Polytechnique, Institut Polytechnique de Paris, in France. During my PhD, I worked under the supervision of Prof. Michalis Vazirgiannis, at the Dascim Group, focusing on robust deep learning methods for time series data and dynamical systems. In October 2020, I was selected to receive partial funding for my PhD by the IP Paris “PhD theses in Artificial Intelligence” (IA IPP 2020) program, provided by ANR. Before this, I obtained a 5-year joint diploma (BSc & MSc equivalent) in Electrical and Computer Engineering from National Technical University of Athens (NTUA), Greece.

News

• 2024/05: We presented our TMLR paper “Neural Ordinary Differential Equations for Modeling Epidemic Spreading” in Vienna at ICLR 2024! The poster can be found here.
• 2023/10/04: Our paper with Xu N., Vazirgiannis M., “TimeGNN: Temporal Dynamic Graph Learning for Time Series Forecasting” has been accepted at The 12th International Conference on Complex Networks and their Applications, 2023, Menton Riviera, France.
• 2023/08/19: Our paper entitled “Neural Ordinary Differential Equations for Modeling Epidemic Spreading” has been accepted for publication at Transactions on Machine Learning (TMLR) journal, awarded with Featured Certification (equivalent to oral/spotlight).
• 2022/10: Happy to serve as a teaching assistant (lab sessions) for the INF554 - Machine and Deep Learning class of 2022-2023 - Computer Science M1 programme, at Ecole Polytechnique!