Can Pouliquen

PhD candidate, Engineer

News: I'm actively engaging with researchers and engineers in the industry and research institutions about working on large-scale deep learning systems in Switzerland. Don't hesitate to contact me for a quick chat if you think we might be a good fit ! :-)

Hello, I'm a final year PhD student in machine learning at the Ecole Normale Supérieure de Lyon under the supervision of Mathurin Massias, Titouan Vayer and Paulo Gonçalves in the Inria OCKHAM team led by Rémi Gribonval. My interests research interests lie at the intersection of deep learning, optimization and statistics. I also have a strong interest in software engineering and am very keen on Python.

Outside of research, I enjoy long-distance mountain running, weighted calisthenics and various types of outdoor activities.

Email  /  CV  /  Scholar  /  Github  /  Linkedin

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Research

I work on machine learning methods for structure discovery. Currently, I am trying to bridge the gap between optimization-based approaches and deep learning-based approaches to do so.

SPODNet Logo Schur's Positive-Definite Network: Deep Learning in the SPD cone with structure
Can Pouliquen, Mathurin Massias, Titouan Vayer
ICLR, 2025
paper / code

We introduce SpodNet, a deep learning layer that guarantees outputs as SPD matrices with additional controlable structure like sparsity.

SPODNet Logo Implicit differentiation for hyperparameter tuning the weighted Graphical Lasso
Can Pouliquen, Paulo Gonçalves, Mathurin Massias, Titouan Vayer
GRETSI, 2023
paper

We design an algorithm for computing optimal hyperparameter(s) of the Graphical Lasso by solving a bi-level optimization problem.

SPODNet Logo Can sparsity improve the privacy of neural networks ?
Antoine Gonon, Léon Zheng, Clément Lalanne, Quoc-Tung Le, Guillaume Lauga, Can Pouliquen
GRETSI, 2023
paper

We investigate whether sparsifying the weights of neural networks improves their robustness against membership inference attacks.

Skills

Programming

Around 5 years of experience with Python in prototyping and development in both research and industry environments. Proficient in various frameworks (PyTorch, NumPy, scikit-learn, SciPy, etc.) and version control (Git, GitHub). Experienced with development on computational clusters and GPUs.

Around 2 or 3 years of experience with C in low-level embedded systems development in academic and industry environments

Prior practical experience with C++, Rust, MATLAB, Assembly

Reviewing

NeurIPS 2023, 2024

ICLR 2024

ICML 2024, 2025

Electronic Journal of Statistics 2025

Gretsi 2023, 2025

Teaching

ENS de Lyon: Convex optimization M1 (2023-2024)
TA of Mathurin Massias, 12h

CPE Lyon: Optimization algorithms M1 (2023-2024)
TA of Marion Foare, 20h

Ecole Centrale de Lyon: Probability theory L3 (2023-2024)
TA of Céline Helbert and Christophette Blanchet, 32h

Spoken languages

French, Turkish: mother tongues

English: full proficiency

German, Spanish: working knowledge, I've passed B1 exams in both

Contact

E-mail: can \dot\ pouliquen \at\ ens-lyon \dot\ fr


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