Yann Le Cunff

Yann Le Cunff

Associate professor, Univ. Rennes 1
CNU Section 26
Dyliss team, Irisa / Inria Rennes-Bretagne Atlantique,
Campus de Beaulieu, 35042 Rennes Cedex, France.
Email: yann.lecunff@irisa.fr or yann.lecunff@univ-rennes1.fr
ORCID : 0000-0002-3068-5675

 

Short presentation

Assistant professor at the University Rennes 1 since 2013 and member of the Dyliss team since 2020. I am interested in the a priori knowledge integration into machine learning algorithms for (i) better performance and (ii) better interpretability. Current application domains functional annotation of proteins and microbiota data in Crohn’s disease patients.

Member of the life sciences faculty board since 2018.
Member of the University advisory group regarding the interface between numeric and education.

Keywords : Machine learning ; representation learning ; data integration ; microbiota ; Protein sequences

On-going collaborators outside Dyliss :

  • Sylvie Buffet-Bataillon, CHU Rennes et NuMeCan
  • Isabelle Luron, NuMeCan (INRAE)

Current PhD students

Baptiste Ruiz (October 2021- September 2024)

Title : “Machine Learning applied to Microbiota : Integrating a priori knowledge for better phenotypic predictions“. Co-supervized with Isabelle Luron (50%, INRAE, HDR).

Nicolas Buton (September 2020 – August 2023)

Title : “Functional annotation of proteins with Transformers : From sequences to interpretable predictions”. Co-supervized with François Coste (50%, INRIA).

Master students at Dyliss

Baptiste Ruiz (April 2021 – September 2021)

“Machine learning methods to associate medical phenotype and microbiota data in ovarian cancer”. Co-supervized with Sylvie Buffet-Bataillon (CHU Rennes) and in collaboration with the company Biofortis.

Léo Maury (March 2021 – May 2021)

“Prediction of cell death pathways depending on their liver localization”. Co-supervized with Jacques Le Seyc and Annaïg Hamon (IRSET, Rennes).

Nicolas Buton (March 2020 – August 2020)

“Functional annotation of proteins with Transformers : From sequences to interpretable predictions“. Co-supervized with françois Coste (Dyliss, INRIA Rennes).

François Fleury (March 2020 – August 2020)

“Linking microbiota and Crohn’s disease using non-supervised machine learning”. Co-supervized with Sylvie Buffet-Bataillon (CHU Rennes).

Teaching

Responsible of the courses (2017-2022) : 

  • Licence :  “Modélisation des phénomènes du vivant”, 30h, L2 Biologie, Univ. Rennes 1, France
  • Master: “Apprentissage statistique”, 110h, Master 1 in Bioinfortmatics Univ. Rennes 1, France
  • Master: “Biologie aux interfaces”, 25h, Master 1 in Biology, Univ. Rennes 1, France
  • Master:  “Simulating dynamic systems in biology”, Master 2 in bioinformatics, 20h, Univ. Rennes 1, France
  • Master:  “Applied Interdisciplinarity”, 20h, Master 2 in biology, Univ. Rennes 1, France
  • PhD program: “Introduction to Machine Learning”, 20h, FdV PhD Program, Sorbonne Paris Université, Paris, France

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