Marc Plantevit



Laboratoire LRDE, EPITA

EPITA, 86 Bd Marius Vivier Merle, 69003 Lyon.

Email: marc(at)

Phone: +33 4 84 34 02 34

Short Bio

I have been a professor at EPITA and member of LRDE since January 2022. Before joining EPITA, I was an associate professor at University Claude Bernard Lyon 1 for twelve years, leading Data Mining & Machine Learning research group in LIRIS lab (UMR CNRS 5205) during 2 years. I received received the PhD degree in computer science in 2008 from the University of Montpellier, which I did under the supervision of Maguelonne Teisseire and Anne Laurent in LIRMM Lab. My research is mainly concerned with foundation of data mining, graph mining, subgroup discovery and explainable artificial intelligence. I am on the editorial board of Data Mining and Knowledge Discovery Journal.


  • April 2022, our paper untitled "What does my GNN really capture? On exploring internal GNN representations" has been accepted at IJCAI-ECAI 22. Out of the 4535 full-paper submissions, about 15% of the papers were accepted. Congratulations to Luca (PhD student) and Ataollah (Master Student).
  • February 2022, our paper "Electricity price forecasting on the day-ahead market using machine learning" has been accepted for publication at Applied Energy journal. Congratulations to Leonard (PhD Student) for this work.
  • January 2022, our paper untitled "Qu'est-ce que mon GNN capture vraiment ? Exploration des représentations internes d'un GNN" has received the best paper award at EGC'22. Congratulations to Luca (PhD student) and Ataollah (Master Student).
  • January 3rd 2022, Happy and excited to become a full professor at EPITA.

Research Interests

Data Mining, Machine Learning, Artificial Intelligence, Data Science, knowledge Discovery in Databases

  • Explainable Artificial Intelligence (Explaining GNN decision, Explaining Recommendations, ...)
  • Foundation of data mining
  • Constraint-based pattern mining
  • (attributed|dynamic) graph mining
  • Sequences / Time Series
  • Subgroup Discovery / Exceptional Model Mining


Current Projects

Past Projects


Program Committees

  • ECMLPKDD: 2022(JT,PC), 2021(JT,PC), 2020(JT,PC), 2019(JT,PC), 2018(JT,PC), 2017, 2016, 2015, 2014, 2013, 2012
  • IDA: 2022, 2021, 2019, 2018, 2017, 2016, 2015
  • IEEE ICDM: 2022, 2021
  • DSAA: 2021
  • SIAM DM: 2022, 2021, 2020, 2019, 2018, 2017
  • IJCAI: 2022, 2021, 2020, 2017, 2015, 2013
  • EGC (French Conference): 2022 (SPC), 2021 (SPC), 2020 (SPC), 2019 (SPC), 2018, 2017, 2016, 2015, 2014, 2013, 2012, 2011
  • SFC: 2022




PhD Students

  • Luca Veyrin-Forrer, on GNN explainability with Céline Robardet (INSA Lyon) and Stefan Duffner (INSA Lyon) since Sept. 2019
  • Maëlle Moranges, Understanding the olfactory perceipt with a neuroinformatics approach, with Moustafa Bensafi (CRNL, CNRS) since jan. 2020
  • Léonard Tschora, on Electricity price forecasting, with Céline Robardet (INSA Lyon) since Sept. 2020
  • Jean-Baptiste Guimbaud, Machine Learning and Exposome, with Rémy Cazabet (Univ. Lyon 1) and Léa Maitre (ISGlobal, Barcelona), since April 2021

Former PhD Students


  • Ataollah Kamal (Master Informatique Fondamentale, ENS Lyon, 2022): xAI and graphs.
  • Ataollah Kamal (Master1 Informatique Fondamentale, ENS Lyon, 2021): Explaining Graph Neural Networks.
  • Mouloud Iferroudjene (ESI Alger, 2021): Explaining Recommender Systems.
  • Youcef Remil (ESI Alger, 2020): Explaining black box models.
  • Guillaume Coiffier (Master Informatique Fondamentale, ENS Lyon, 2019): Deep Neural Network simplication.
  • Adrien Jarretier-Yuste (Master IA, Université Lyon 1, 2019): Machine learning for early identification of immune cell subtypes.
  • Maëlle Moranges (Master Bioinformatique, Université Lyon 1, 2018): Subgraph mining for understanding the olfactory perceipt.
  • Anes Bendimerad (INSA Lyon, IF 2016) : Analyse descriptive de la dynamique urbaine à l’aide de la fouille de graphes attribués.
  • Duc Duong (Master recherche, Université National du Vietnam, Institut Francophone International, 2015): Fouille de Graphes Dynamiques Attribués : Découvertes de phénomènes périodiques et exceptionnels.
  • Guillaume Bosc (INSA Lyon, IF 2014): Associating odor qualities to their molecular properties with redescription mining.
  • Roland Kotto Kombi (Master Informatique, parcours TIWE, Université Lyon 1, 2014): Olfactory qualities characterization with subgroup discovery.
  • Clarisse Uwizeye (Master Systèmes Complexes, ENS Lyon 2014): Mining dynamic attributed graphs for describing the use of the Velo’v system.


Up-to-date publication lists available on: