Short CV

Education

• Postdoctoral Researcher, Centre Borelli, Ecole Normale Superieure (ENS), Paris-Saclay, France, February 2024 - now
• Ph.D in CS & ML, Laboratoire d’Informatique (LIX), Ecole Polytechnique, IPP, France, October 2020 - January 2024
• BSc & MSc (5-year joint Diploma) in Electrical and Computer Engineering (major in Information Technology - top 15%), NTUA, Greece, 2014-2019

Research experience

• February 2024 - now: Postdoctoral Researcher
  • Centre Borelli, ENS Paris-Saclay
  • Projects under the Industrial Data Analytics and Machine Learning (IDAML) chair
  • Duties included: Research projects (ML for time series, ML for industrial applications), Supervision of students
• October 2020 - January 2024: PhD Candidate
  • DaSciM Group, LIX, Ecole Polytechnique
  • Duties included: Research projects (ML for time series, sequences, graphs), Teaching Assistant
  • Supervisors: Michalis Vazirgiannis & Jean-Marc Steyaert
• April - November 2019: MSc Thesis
  • Artificial Intelligence and Learning Systems Laboratory (NTUA)
  • ML for genomics and protein data

Publications

Time Series Forecasting Models Copy the Past: How to Mitigate

Kosma, C., Nikolentzos, G., Xu, N. and Vazirgiannis, M. (2022). "Time Series Forecasting Models Copy the Past: How to Mitigate." Proceedings of the 31st International Conference on Artificial Neural Networks (pp. 366-378). Cham: Springer International Publishing.

Neural Ordinary Differential Equations for Modeling Epidemic Spreading

Kosma, C., Nikolentzos, G., Panagopoulos, G., Steyaert, J.M. and Vazirgiannis, M. (2023). "Neural Ordinary Differential Equations for Modeling Epidemic Spreading.." Transactions on Machine Learning Research.

TimeGNN: Temporal Dynamic Graph Learning for Time Series Forecasting

Xu, N., Kosma, C. and Vazirgiannis, M. (2023). "TimeGNN: Temporal Dynamic Graph Learning for Time Series Forecasting." Proceedings of the 12th International Conference on Complex Networks and Their Applications. (to appear).

Reviewing

• AISTATS 2023, AISTATS 2024, AISTATS 2025
• ICLR 2024 (Tiny papers Track, DEI Initiative), ICLR 2025 (Main Track)
• ICANN 2023
• NeurIPS 2024 (Main Track, Awarded as Top Reviewer (~ 8%))
• ICML 2025
• Journals: Transactions on Machine Learning Research (TMLR) - since 2024, IEEE Transactions on Knowledge and Data Engineering (TKDE) - since 2023

Supervising

• Maxime Dehondt (Cifre PhD Student, 2024-), cosupervised with Charles Truong and Laurent Oudre
• Bastien Lhopitallier (Cifre PhD Student, 2024-), cosupervised with Charles Truong and Laurent Oudre
• Lucas Haubert (M2 MVA Student 2024), cosupervised with Thibaut Germain and Laurent Oudre

Teaching

Executive Education (X-EXED) Advanced AI Program

Ingénieur 3A, Master 1 - INF554 (Machine and Deep Learning) 2021-2022

Ingénieur 3A, Master 1 - INF554 (Machine and Deep Learning) 2022-2023

Programming Skills

• Python (PyTorch, Keras, Tensorflow)
• Java (OOP Principles), C/C++
• Matlab
• Git/Github, Linux

Languages

• Greek (native)
• English (fluent - C2)
• French (basic - B2)

Honours & Awards

• “IP Paris “Artificial Intelligence (AI)” programme”, IPP funding by ANR for PhD theses in AI, 2020
• “The Great Moment for Education” Award - Eurobank, excellence in university admissions exams, 2014
• Touramanoglou Scholarship - Municipality of Ilioupolis & Hymettus, Greece, top high school graduate, 2014