CV

Basics

Name Quentin Fournier
Email quentin.fournier@mila.quebec
Phone +1(438) 722-3154
Summary I’m a Research Fellow at Mila, where I’m leading a thematic lab on language models for drug discovery. I'm currently focusing on understanding how to adapt all aspects of the LLM pipeline, from data processing and pre-training to alignment and evaluation, to the unique characteristics of biological data such as genomes, proteins, and small molecules.

Work

  • 2024 - Present

    Montréal, CA

    Consultant as Senior Machine Learning Scientist
    Amgen
    Designing novel machine learning solutions for the drug discovery pipeline.
  • 2024 - Present

    Montréal, CA

    Research Fellow
    Mila
    Leading a thematic research lab focused on advancing machine learning for drug discovery.
  • 2019 - 2022

    Montréal, CA

    Lecturer
    Polytechnique Montréal
    • Taught INF8111-Data Mining (Graduate-level) for Fall 2019, Summer 2020, Fall 2020, and Fall 2022 semesters.
  • 2018 - 2018

    Rennes, FR

    Research and Development Internship
    IT Link
    • Supervised by Nicolas Ménard and Christian Raymond.
  • 2018 - 2021

    Montréal, CA

    Teacher Assistant
    Polytechnique Montréal
    • INF8111 - Data Mining (Summer 2021, Fall 2021) (graduate-level)
    • INF8215 - Artificial Intelligence: Methods and Algorithms (Fall 2018) (graduate-level)
  • 2017 - 2017

    Rennes, FR

    Research Internship
    Institut de Recherche en Informatique et Système Aléatoire (IRISA)
    • Supervised by Christian Raymond.

Volunteer

  • 2016 - 2016

    Rennes, FR

    Lead Developer
    Club'Dev
    Developed the student association website and tutored computer science students.
  • 2016 - 2016

    Rennes, FR

    Webmaster
    Rock'n Solex
    Developed the website for a student festival combining Solex racing and music since 1967.
  • 2014 - 2014

    Rennes, FR

    Member of the Network Team
    INSALAN
    Contributed to the deployment of hardware and software for a LAN tournament with over 100 players.

Education

  • 2023 - 2024

    Montréal, CA

    Postdoctoral Fellow
    Mila, University of Montréal
    Computer Science and Operations Research
  • 2018 - 2022

    Montréal, CA

    Ph.D.
    Polytechnique Montréal
    Computer and Software Engineering
    • Supervisors: Daniel Aloise and Michel R. Dagenais
    • Award: Nominated for Best Thesis Award
  • 2013 - 2018

    Rennes, FR

    Master of Engineering
    Institut National des Sciences Appliquées Rennes
    Computer Science
  • 2008 - 2013

    Fougères, FR

    Scientific Baccalauréat
    Lycée Jean Guéhenno
    Mathematics Specialty

Awards

  • 2022
    Nominated for Best Thesis Award
    Polytechnique Montréal
    Nominated for outstanding doctoral research and thesis in the Computer and Software Engineering department.

Skills

Data Mining & Machine Learning
Deep Learning: Transformers, Low-Complexity Transformers, Deep and Variational Autoencoders
Machine Learning: SVM, LDA, QDA, KNN, Naive Bayes, Decision Trees, KMeans, DBSCAN, OPTICS, Gaussian Mixture Models
Data Mining: Logging and tracing, data munging, statistical analysis, data visualization
Programming, Libraries & Tools
Languages: Python, LaTeX, Bash
Libraries: PyTorch, WandB, Hydra, Scikit-learn, Scipy, Matplotlib, Seaborn
Tools: Git, Slurm, VS Code

Languages

French
Native Speaker
English
Proficient

References

Available upon request

Projects

  • 2023 - Present
    Supervision of Ph.D. Students
    • Gabriele Prato (Mila, UdeM, 2025-Present): LLMs Groundness - with Sarath Chandar
    • Davide Baldelli (Mila, PolyMTL, 2025-Present): Computer-Aided Design (CAD) with LLMs - with Sarath Chandar
    • Léa Kaufman (Mila, UdeM, 2025-Present): Gene Expression Across Cell Lines - with Sébastien Lemieux
    • Darshan Patil (Mila, PolyMTL, 2024-Present): Lifelong Pre-trained Language Models - with Sarath Chandar
    • Prashant Govindarajan (Mila, PolyMTL, 2024-Present): Computer Aided Design (CAD) with LLMs - with Sarath Chandar
    • Lola Le Breton (Mila, PolyMTL, 2023-Present): Protein Language Models - with Sarath Chandar
    • David Heurtel-Depeiges (Mila, PolyMTL, 2023-Present): Diffusion Protein Language Models - with Sarath Chandar
    • Pranshu Malviya (Mila, PolyMTL, 2023-Present): Neural Network Expansion & Lifelong PLMs - with Sarath Chandar
    • Jerry Huang (Mila, UdeM, 2023-Present): Role of Memory & Protein State-Space Models - with Sarath Chandar
  • 2021 - Present
    Supervision of Master's, Researchers & Interns
    • Istabrak Abbes (Mila, UdeM, Master, 2024-Present): LLMs Groundness - with Sarath Chandar
    • Megh Thakkar (Mila, UdeM, Master, 2023-2025): Safety Alignment & Model Merging - with Sarath Chandar and Amal Zouaq
    • Maziar Sargordi (Mila, PolyMTL, Master, 2023-2024): NN with Constraint Programming - with Sarath Chandar and Amal Zouaq
    • Behnoush Khavari (Mila, Researcher, 2023-Present): Role of Memory; Protein State-Space Model - with Sarath Chandar
    • Kamran Chitsaz (Mila, Researcher, 2023-Present): Transformer Quantization; Molecule Language Models - with Sarath Chandar
    • Alex Aselstyne (PolyMTL, Intern, 2025-Present): Antimicrobial Resistance Prediction - with Sarath Chandar
    • Can (Sam) Chen (Mila, UdeM, Intern, 2025): Structure Alignment for Protein Language - with Yoshua Bengio
    • Annabel Adeyeri (Mila, MIT, Intern, 2023): Fairness in Pre-Trained Language Models - with Sarath Chandar
    • Julia Rolland (UTBM, PolyMTL, Intern, 2021): ML to Detect Anomalies in Traces - with Daniel Aloise