Nikita Lagrange

PhD Student

Institut Curie

About Me

I am on the job market and planning to defend my PhD thesis between late September and early October 2025 - feel free to reach out !

I am Nikita Lagrange, a PhD student at Institut Curie in Paris under the supervision of Dr. Hervé Isambert and the co-supervision of Dr. Barbara Bravi. My thesis focuses on the development of a new search-and-score algorithm for causal discovery in the presence of latent variables using information theory.

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Interests
  • Causal Discovery
  • Structure Learning
  • Machine Learning
  • Probabilistic Methods
  • Information Theory
  • Bioinformatics
Education

  • PhD Computer Science

    Sorbonne University

  • M.Sc. Bioinformatics & Modelling

    Sorbonne University

  • B.Sc. Sciences of Live

    Sorbonne University

📚 Research
I am a PhD student at Institut Curie in Paris. My thesis focuses on causal discovery. More specifically, I am working on extending the MIIC algorithm, developed within the Isambert Lab to a search-and-score mode. The goal is to improve the performance of causal discovery algorithms with the aim of applying this method to biomedical data, which are known to be complex and non-linear.

Beyond that, I am interested in developing new machine learning algorithms that are more grounded in human reasoning and are interpretable.

📝 Publications
Nadir Sella, Florent Guinot, Nikita Lagrange, Laurent-Philippe Albou, Jonathan Desponds, Hervé Isambert (2025). Preserving information while respecting privacy through an information theoretic framework for synthetic health data generation. npj Digital Medicine.
PDF Cite Code DOI URL
Franck Simon, Maria Colomba Comes, Tiziana Tocci, Louise Dupuis, Vincent Cabeli, Nikita Lagrange, Arianna Mencattini, Maria Carla Parrini, Eugenio Martinelli, Hervé Isambert (2025). CausalXtract, a flexible pipeline to extract causal effects from live-cell time-lapse imaging data. eLife.
PDF Cite Code DOI URL
Nikita Lagrange, Hervé Isambert (2024). An efficient search-and-score algorithm for ancestral graphs using multivariate information scores. arXiv.
PDF Cite DOI URL
Talks
Reliable Causal Discovery from Information Theoretic Principles (State of the art & ongoing project)
Reliable Causal Discovery from Information Theoretic Principles (State of the art & ongoing project)

Presentation of my thesis work at the retreat for young researchers from Institut Curie, Centre des Cordeliers, and Institute of Biotechnology of the Czech Academy of Sciences in Prague, Czech Republic

Sep 22, 2024

Improving Graphical Models Through Data Generative Approaches

Presentation of my thesis project and preliminary results to the AI-DSCY team

Sep 27, 2023

Academic Services
  • Representative of doctoral students on the EDITE doctoral school board
    • Participation in the doctoral school board and decision-making processes
  • Reviewer for the NeurIPS BDU Workshop 2024
    • Reviewed two submissions for the NeurIPS 2024 Workshop on Bayesian Decision-making and Uncertainty
📰 News
  • 📅 January 23, 2025 - Publication of a paper on synthetic health data generation with Institut Roche in npj Digital Medicine 🎉 !
  • 📆 January 17, 2025 - Publication of a paper on the CausalXtract tool, which extracts features from time series to reconstruct temporal causal networks in eLife 🎉 !
  • 📆 December 23, 2024 - Publication of the preprint on the extension of the MIIC algorithm to a search-and-score approach applied to categorical data in arXiv 🎉 !
  • 📆 October 2024 - Second stay in Dr. Barbara Bravi's team at Imperial College London 🇬🇧
  • 📆 September 2024 - Participation in the retreat of young researchers from Institut Curie, Centre des Cordeliers, and Institute of Biotechnology of the Czech Academy of Sciences in Prague 🇨🇿
  • 📆 September 2023 - Presentation of my thesis project and preliminary results at the workshop of the AI-DSCY team at Centre Borelli in Paris 🇫🇷
  • 📆 June 2023 - First stay in Dr. Barbara Bravi's team at Imperial College London 🇬🇧
  • 📆 October 2022 - Start of my PhD at Institut Curie under the supervision of Dr. Hervé Isambert and co-supervised by Dr. Barbara Bravi 🎉 !
Contact

📧 nikita.lagrange@curie.fr or nikita.lagrange@tutanota.com

📍Institut Curie, Research Center, CNRS-UMR168
Pavillon Curie, 1st floor, Office 01.09.b
11, rue Pierre et Marie Curie
75005 Paris