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  • Ecole Normale Supérieure Paris-Saclay, AgroParisTech, Université Paris-Saclay & Université Paris-Cité
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raphaelrubrice/README.md

Hi, I'm Raphaël Rubrice !


I'm a Master's student at the intersection of computational biology and machine learning, specializing in generative models for biological systems.


Currently finishing the MVA Master program at ENS Paris-Saclay & Paris-Cité University where I'm focusing on the mathematics behind ML and reinforcing my knowledge and skills to prepare for a future PhD in AI for Biology and/or Biomedical discovery.

I previously completed an MSc in Artificial Intelligence and Computational Biology at Paris-Saclay University and AgroParisTech.

I am constantly trying to improve my data science and programming skills which makes me eager to contribute to impactful and ground-breaking projects involving AI and computational biology.

I am fascinated by these research fields (lot of work ahead to truly get there though 🤓):

  • Single-cell & spatial biology: Latent diffusion models (e.g scLDM, SquiDiff), perturbation prediction (e.g, STATE), generative models for cellular dynamics
  • Foundation & Generative models for biology: Protein language models (e.g, BoltzGen), multi-omic integration, virtual cell systems
  • Geometric & generative ML: Optimal transport (e.g, GWOT, GrALe), diffusion models, representation learning for biological data
  • AI for precision medicine: Multi-modal integration for patient stratification and biomarker discovery

💻Operating Systems I've worked with :

ubuntu logo windows8 logo apple logo

🧰📊What I use to contribute to projects :

vscode logo git logo github logo docker logo rstudio logo jupyter logo anaconda logo postgresql logo latex logo

💻📚Programming Languages :

python logo nextflow logo rstudio logo bash logo

🧪⌨️Current/Recent projects :

🤓😁Cool stuff :

  • Master's thesis in the TheisLab @ Helmoltz Munich
  • Got accepted into ENS Paris-Saclay's MVA coursework
  • Laureate of the PR[AI]RIE Institute Excellence Scholarship
  • Published in the Journal Artificial Intelligence in the Life Sciences : A machine learning framework for the prediction and analysis of bacterial antagonism in biofilms using morphological descriptors
  • Got an internship at Dassault Systèmes, the topic ? Explainable clustering for clinical data
  • Our main project of the year during IODAA got accepted for presentation at the 1st AI for Animal Science Conference at ETH Zurich (2025)
  • With a few friends from AgroParisTech, we won the AI Methodology Award at the 2025 Owkin & Servier AI Hackathon for Glioblastoma Research
  • Gave a presentation at the Micalis Institute on the work I've done on the biofilm antagonism prediction model

📫Contacts :

Email

linkedin logo

googlescholar logo


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  1. scVAE_mva2025 scVAE_mva2025 Public

    Github for the project on VAEs for single cell data for the "Introduction to Probabilistic Graphical Models and Deep Generative Models" course of the MVA.

    Jupyter Notebook

  2. HVAE HVAE Public

    Hyperspherical Variational Auto-Encoders

    Jupyter Notebook

  3. ReproHackathon_G6 ReproHackathon_G6 Public

    Repository made for the ReproHackathon course of the Master 2 AMI2B program (Computational Biology) at Paris-Saclay University. The goal is to reproduce part of the results shown in : https://doi.o…

    R 2 1

  4. TELLAM TELLAM Public

    Pipeline for Transposable Elements Locus Level Analysis.

    Python

  5. lauronta/projet_fil_rouge_afz lauronta/projet_fil_rouge_afz Public

    Jupyter Notebook 3