Hugues Van Assel

My primary research interests are in unsupervised and self-supervised learning. I develop computational methods that leverage optimal transport and probabilistic modeling to compute robust and grounded data representations suitable for real-world applications. I am especially interested in applying these methods to tackle challenges in cell biology.

I am a strong advocate for open and accessible science through projects such as:

• TorchDR : a modular, GPU-friendly toolbox for dimensionality reduction (DR) that offers a unified interface for state-of-the-art DR methods.
• Stable-SSL : a library offering essential boilerplate code for a wide range of self-supervised learning tasks.

While finalizing my PhD thesis in the math department of ENS Lyon, I am currently a visiting research fellow at Brown University working with Randall Balestriero. Prior to my PhD, I was a student at Ecole polytechnique and MVA master (CV).