Hi, bonjour, yeia

I have a Computer Science background, and I work on Machine Learning, or more specifically at the intersection between Computer Science and Applied Mathematics.

Short bio: ...

Argyris Kalogeratos comes from Patras, Greece. He has BSc and MSc degrees in Computer Science from the University of Ioannina, Greece. He holds a PhD in Machine Learning and Information Technologies (2013, supervisor: Aristidis Likas), from the same Institution. Furthermore, he had been a post-doctorate researcher in the Centre of Applied Mathematics, ENS Cachan, France (2013-2018, collaborating with Nicolas Vayatis), and since 2018 he is a staff researcher in the Centre Borelli, ENS Paris-Saclay, Université Paris-Saclay, France. His interests include Machine Learning, Statistics, Network Science, Decision & Control, and Computational Social Systems. He has been involved in several synergistic projects between Academia and Industry, for problems related to multimedia mining, social network analysis and mining, computational epidemiology, marketing, transportation, communication systems, and bioinformatics. He is fond of multidisciplinary research and the fusion of ideas, concepts, viewpoints, originating from different domains.

Currently

Position: Permanent senior researcher at the Centre Giovanni Borelli1, Ecole Normale Supérieure Paris-Saclay (ENS Paris-Saclay), University Paris-Saclay, France, and member of the Learning and Information Processing Systems (LIPS) research group2. ...

1 ex Centre de Mathématiques et de Leurs Applications (CMLA).
2 ex Machine Learning and Massive Data Analysis (MLMDA).

Research interests & focus: Broad interest in statistical ML. Coordinator of the ML on Graphs research theme.

Research initiatives: Member of the Industrial Data Analytics and Machine Learning Chair, having as industrial partners SNCF, CEA, Michelin. Other Academia-Industry synergies: join probject with RTE&SNCF, and collaboration with EDF. — Other initiatives: Since 2017, (co-)organizer of the LIPS seminars.

Past funding: ...

In the past, the research position at CMLA had been funded in the past by the MORANE project (in collaboration with SNCF railway company) and the SODATECH project  (funded by the French state). See more details at the Projects section.

Current PhD students:

Alumni: ...

PhD students:

Post-docs:

Internships:

  • Master 2
    • Mateo Sesia (2014)
    • Xavier Lioneton (2016)
    • Stefano Sarao (2016)
    • Luca Corinzia (2016)
    • Mathilde Fekom (2017)
    • Matteo Neri (2017)
    • Amel Addala (2019)
    • Alexandro de la Concha (2019 MVA)
    • Anthea Mérida (2019 ENSIIE)
    • Thibaut Germain (2020)
    • Randa El Mrabet-Tarmach (2020 MVA)
    • Mohammed Hssein (2022 MVA)
    • Jules Tsukahara (2022 MVA)
    • Ivan Conjeaud (2022 PSE)
    • Perceval Beja-Battais (2023 MVA)
    • Gwendal Debaussart (2023 Math AI)
    • Eloi Campagne (2023 MVA – EDF)
    • Gaspard Abel (2023 ENS P.S. Physics)
    • Louise Allain (2024 MVA)
    • Yutai Zhao (2025 MHPC P.S.)
    • Ahmed El Fanaoui (2026, ENSTA Paris)
  • Master 1
    • Otávio Leite Bastos de Nazaré (2017 M1 ENSTA)
    • Marin Scalbert (2017)
    • Thales Loiola Raveli (2018 M1 ENSTA)
    • Ivan Conjeaud (2020a ENS ARIA)
    • Ivan Conjeaud (2021b ENS ARIA)
    • Mohamed El Khames (M1 ENSTA 2020)
    • Kais Cheikh (M1 ENSTA 2020)
    • Aaron MAMANN (2021)
    • Gaspard Abel (2021a M1 ENS P.S. Physics)
    • Gaspard Abel (2022b M1 ENS P.S. Physics)
    • Haytham Borchani (2022 M1 ENSTA Paris)
    • Mohamed Aymen Bouyahia (2023 M1 ENSTA Paris)
    • Jeanne Belly (2024 M1 ENS P.S. ARIA)
    • Teo Tessier (2024 M1 ENS P.S. ARIA)
    • Silviu-Adrian Predoi (2024 M1 ENS P.S. Physics)
    • Itai Zehavi (2025 M1 ENS P.S. ARIA)
    • Itai Zehavi (2025 M1 ENS P.S. ARIA – EDF)
    • Mahdi Hadj Taieb (2025 M1 ENSTA Paris)
    • Mohamed Benloughmari (2025 M1 ENSTA Paris)
    • Nicolas Bigeard (2026 École Supérieure d’Ingénieurs Léonard de Vinci, Quant. Finance)
    • Alexandre Autran (2026 M1 ENS Rennes, Math)
    • Maissa Frikha (2026 École Nationale des Ponts et Chaussées, Math)
  • L3 (mostly teams of two, ENS P.S. Maths)
    • Patrick Saux and David Marchand (2014)
    • Pierre Abgrall and Jules Baleyte (2015)
    • Suzanne Schlich and Julie Tourniaire (2015)
    • Emile Ciuperca and Mathieu Helfter (2018)
    • Antoine Prouff and Antoine Bordas (2018)
    • Vincent Laheurte and Ferdinand Campos (2019)
    • Rafael Gromit and Blandine Galiay (2019)
    • Martin Dhaussy (2020 ENS P.S. Economics)
    • Baptiste Loreau and Wendong Liang (2020)
    • Timothé Chambéry and Alexandre Surin (2021)
    • Florian Châtel (2022)
    • Antonin Casel and Ilyes Belkacem (2022)
    • Manon Gouttefangeas and David Pieroucci (2023)
    • Quentin Boiret and Amer Essakine (2023)
    • Tokinirina Hansen and Yorick Libiot (2024)
    • Yann Moinard and Nidhal Sellik (2025)
    • Ahmed Benamar and Bernard Emilien (2026)
    • Matine Alin (2026 SciencePo Paris)

Centre Borelli in a sentence

CB is a unique and dynamic environment where academic research is developed and challenged through real-world applications.

News [bits and pieces]

  • Preprints:
    • Algorithmic collusion under asynchronous price updating, co-authored with I. Conjeaud and G. Abel, 2026 [pdf].
    • A model for imbalanced label aggregation: A focus on minority-class detection, co-authored with G. Singer, S. Gruffaz, O. Vo Van, and N. Vayatis, 2026 [pdf].
  • SETN2026: the paper GLOBe: A Modular Global Optimization library, co-authored with G. Serré and N. Vayatis has been accepted to SETN 2026 conference. It releases a library providing a collection of global optimization algorithms implemented in C++ and linked with Python [pdf][code].
  • TMLR: the paper Generalized Dirichlet Energy and Graph Laplacians for Clustering Directed and Undirected Graphs has been accepted to the Transactions of Machine Learning Research. The work is co-authored with H. Sevi, G. Debaussart-Joniec, M. Jonckheere, and M. Hacini [pdf].
  • ICML2026: The following papers have been accepted
    • Parametrized Power-Iteration Clustering for Directed Graphs, co-authored with G. Debaussart-Joniec, H. Sevi, and M. Jonckheere, 2026 [pdf][code][poster].
    • Optimal Fair Aggregation of Crowdsourced Noisy Labels using Demographic Parity Constraints, co-authored with G. Singer, S. Gruffaz, O. Vo Van, and N. Vayatis, 2026 [pdf][poster].
  • New interns:
    • Ahmed El Fanaoui (M1 ENSTA Paris, Jun-Aug 2026) on approaches for graph profiling.
    • Nicolas Bigeard (M1 ESILV Paris, Jun-Jul 2026).
    • Matine ALIN (L3 SciencePo Paris, Jun-Jul 2026) on socioeconomic impact of certain social dilemmas.
    • Ahmed Benamar and Bernard Emilien (L3 ENS P.S. Maths, Mar-Jun 2026) on fairnsess.
  • Invited Talk: Talk about the paper Multi-view diffusion geometry using intertwined diffusion trajectories, in the Geometry, Topology and Machine Learning Conference 2026, 18-22 May, Paris. [slides].
  • ΤCSS: The article Uncovering Social Network Activity Using Joint User and Topic Interaction, co-authored with G. Abel, J.-P. Nadal, and J. randon-Furling, has been accepted to the journal IEEE Transactions on Computational Social Systems [pdf][code].
  • Preprints:
    • Dual-Criterion Curriculum Learning:
      Application to Temporal Data      , co-authored with G. Abel, E. Campagne, and M. Benloughmari, 2026. [pdf][code soon]
    • Enhancing LIME using Neural Decision Trees, co-authored with M. Aymen Bouyahia, 2026 [pdf][code].
    • Enhancing Exploration in Global Optimization by Noise Injection in the Probability Measures Space, co-authored with G. Serré, P. Germain, and S. Gruffaz, 2026. [pdf]
    • Cascaded Transfer: Learning Many Tasks under Budget Constraints, co-authored with E. Campagne, Y. Amara-Ouali, Y. Goude, and M. Mougeot, 2026. [pdf]
    • Reducing Recurrent Competitive Epidemics via Dynamic Resource Allocation, co-authored with G. Abel, and S. Sarao-Mannelli, 2025. [pdf]
    • Multi-view diffusion geometry using intertwined diffusion trajectories, co-authored with G. Debaussart-Joniec, 2025. [pdf][code]
    • Formal equivalence between global optimization consistency and random search, co-authored with G. Serré and N. Vayatis, 2025. [pdf][Lean code]
  • ARCOM conf.: Gaspard Abel presented our work on multivariate Hawkes processes for social interactions and visualization at ARCOM’s event (co-organized with ENS P.S.). His talk had the title Analyse multi-échelle de la diffusion d’informations dans les réseaux sociaux [read more].
  • PhD position: We are actively looking to fill an open PhD position on online change-point detection for structured multivariate time series. Read more.
  • Preprint: the new preprint Graph Neural Networks for Electricity Load Forecasting consolidates two works that has been earlier presented in two ECML Workshops (2024 & 2025). Co-authored with E. Campagne, Y. Amara-Ouali, Y. Goude, and I. Zehavi. [pdf][code]
  • Code: The GraphToolbox is a Python package designed for graph machine learning focused on time-series forecasting. It provides tools for data handling, model building, training, evaluation, and visualization. Developed as part of the work of our PhD student Eloi Campagne.
  • JMLR: The paper Collaborative likelihood-ratio estimation over graphs, co-authored with A. de la Concha and N. Vayatis has been accepted in the Journal of Machine Learning Research. [pdf][code]
  • New pre-doc: Gabriel Singer has started a pre-doc with us and in collaboration with SNCF (in the frame of the IDAML Chair).
  • New intern:
    • Mohamed Ben Loughmari (M1 ENSTA Paris) on advanced learning techniques for temporal point processes (Oct–Dec).
  • Pattern Recognition: The paper UniForCE: The unimodality forest method for clustering and estimation of the number of clusters, co-authored with G. Vardakas and A. Likas, has been accepted to the Pattern Recognition journal (Elsevier) and will appear soon. [pdf][code]
  • ECML 2025: the paper Plugging Attention Matrices into Power Grids: Towards Transparent Forecasting, co-authored along with E. Campagne, I. Zehavi, Y. Amara-Ouali, and Y. Goude, will appear at the ECML 2025 Workshop on Machine Learning for Sustainable Energy Systems (ML4SPS). [pdf]
  • ANR oroject: The project SCOPED has been accepted by the ANR (the french national research agency). We are excited for the excellent potential offered by this project for exchanges and collaborations. The project is led by Cédric Richard, Laboratoire Lagrange, Université Côte d’Azur, and from Centre Borelli there will be involvement by L. Oudre, N. Vayatis, and myself.
  • Code: Check the MultiLayerNetViz tool, which is developed in our team by Gaspard Abel, for visualization of social interaction data in a multilayer network layout.
  • Preprint: a new version of the working paper Efficient stream-based Max-Min diversification with minimal failure rate has been posted on arxiv [pdf]. Initially a project initiated during Mathilde Fekom’s PhD, advances now after the M2 intern Yutai Nazir Zhao has joined forces.

See all news...