After a PhD at the Institut Pasteur, I am now a postdoctoral researcher in the CQSB @Sorbonne-Université in Paris. Overall work focuses on applying machine learning techniques to biological sequence data. More recently I have been working on deep-learning methods for phylogenetic inference.

I have written my thesis in an open source fashion. You can read it, of you wish, as an HTML website here or as a PDF document here.
The slides I used for the defense are also available here.

PDF resumes short & long

Publications ¹

Find the full list on Google Scholar or ORCID.

Preprints:

• Garot Vincent, Blassel Luc, Nesterenko Luca, Zhukova Anna, Alizon Samuel, Jacob Laurent, Teddy: Neural Inference of Epidemiological Parameters from Viral Sequences. bioRxiv (2026)
• Blassel Luc, Boussau Bastien, Lartillot Nicolas, Jacob Laurent, Likelihood-Free Inference of Phylogenetic Tree Posterior Distributions. arXiv (2025)

Published Works:

• Nesterenko Luca*, Blassel Luc*, Veber Philippe, Boussau Bastien, Jacob Laurent. Phyloformer: Fast, Accurate, and Versatile Phylogenetic Reconstruction with Deep Neural Networks. Molecular Biology and Evolution 42,msaf051 (2025).
• Blassel Luc, Medvedev Paul, Chikhi Rayan. Mapping-Friendly Sequence Reductions: Going beyond Homopolymer Compression. iScience,105305 (2022).
• Zhukova Anna*, Blassel Luc*, Lemoine Frédéric, Morel Marie, Voznica Jakub, Gascuel Olivier. Origin, Evolution and Global Spread of SARS-CoV-2. Comptes Rendus. Biologies 344,57-75 (2021).
• Blassel Luc, Tostevin Anna, Villabona-Arenas Christian Julian, Peeters Martine, Hué Stéphane, Gascuel Olivier. Using Machine Learning and Big Data to Explore the Drug Resistance Landscape in HIV. PLOS Computational Biology 17,e1008873 (2021).
• Blassel Luc, Zhukova Anna, Villabona-Arenas Christian J, Atkins Katherine E, Hué Stéphane, Gascuel Olivier. Drug Resistance Mutations in HIV: New Bioinformatics Approaches and Challenges. Current Opinion in Virology 51,56-64 (2021).
• Lemoine Frédéric, Blassel Luc, Voznica Jakub, Gascuel Olivier. COVID-Align: Accurate Online Alignment of hCoV-19 Genomes Using a Profile HMM. Bioinformatics 37,1761-1762 (2020).

Talks

• “Likelihood-free inference of phylogenetic tree posterior distributions”
  Dec 11 2025, LEGEND 2025 (slides)
• “Likelihood-free inference of phylogenetic tree posterior distributions”
  Nov 27 2025, LEGO 2025 (slides)
• “Deep end-to-end likelihood-free inference of phylogenetic trees”
  Sep 11 2025, MLCB 2025 (slides)
• “Deep likelihood-free inference of phylogenetic trees”
  Sep 08 2025, MASAMB 2025 (slides)
• “Deep likelihood-free inference of phylogenetic trees”
  Jun 17 2025, CQSB Seminar (slides)
• “Deep likelihood-free inference of phylogenetic trees”
  Jun 13 2025, DEELOGENY meeting (slides)
• “PhyloFormer and phylogenetic reconstruction with deep neural networks”
  Nov 21 2024, LISN Bioinfo seminar (slidessource)
• “Phyloformer: fast, accurate and versatile phylogenetic reconstruction with deep neural networks”
  Jun 20 2024, MCEB 2024 (slidessource)
• “Can we improve analyses by transforming DNA ?”
  May 21 2022, RECOMB-SEQ/CCB Joint Communication Session 2022 (slides)
  second place award for jargon-free scientific communication
• “Mapping-friendly sequence reductions: Going beyond homopolymer compression”
  May 21 2022, RECOMB-SEQ 2022 (slides)

Teaching

• “Data Structures in C”
  2023-2024, L2@Sorbonne Université
  Semester-long theory and practical implementation courses.
• “Phylogenetics and comparative genomics”
  2023-2025, M2@Sorbonne Université ( Notebook )
  Yearly 2h practical sessions on deep learning for phylogenetics.