About Me
📢 I am on the job market and planning to defend my PhD thesis in Fall 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.
- Causal Discovery
- Structure Learning
- Machine Learning
- Probabilistic Methods
- Information Theory
- Bioinformatics
PhD in Computer Science
Sorbonne University
M.Sc. in Bioinformatics & Modelling
Sorbonne University
B.Sc. in Life Sciences
Sorbonne University
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 efficiency and robustness of causal discovery algorithms, particularly when applied to complex and non-linear biomedical data.
Beyond that, I am interested in developing new machine learning algorithms that are more grounded in human reasoning and are interpretable.
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
Representative of doctoral students on the EDITE doctoral school board
Participation in the board and involvement in key decision-making processes.
Reviewer for the NeurIPS BDU Workshop 2024
Reviewed two submissions for the NeurIPS 2024 Workshop on Bayesian Decision-making and Uncertainty.
Publication of a paper on synthetic health data generation with Institut Roche in npj Digital Medicine 🎉 !
Publication of a paper on the CausalXtract tool, which extracts features from time series to reconstruct temporal causal networks in eLife 🎉 !
Publication of the preprint on the extension of the MIIC algorithm to a search-and-score approach applied to categorical data in arXiv 🎉 !
📧 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