Hi, I'm Hadrien.

I am currently pursuing a PhD at MyFit Solutions, in the HEKA team of Inria Paris, under the supervision of Professor Stéphanie Allassonnière, Dr. Jean Feydy and Jeremy Adoux for the last
.

I am also contributing to scikit-shapes, an open-source Python library for shape analysis and statistical learning on geometric data, designed to facilitate research and applications in computational anatomy, morphometrics, and related fields.

Additionally, I have been serving as a Teaching Assistant of Probability Theory at Lyon 2 Lumière University, working in collaboration with Professor Stephane Chretien and Zied Gharbi.

NEWS

Sep–Oct 2026 Presenting our work on Optimal Steps for Fast Diffeomorphic Shape Registration at MICCAI 2026.
Jun 2026 Presenting our work on Optimal Steps for Fast Diffeomorphic Shape Registration at Curves and Surfaces 2026.
May 2026 Our team (with Jean Delhaye and Pierre-André Mikem) won 1st place at the MathTech challenge organized by the Fondation Hadamard.
May 2026 Presenting our work on Optimal Steps for Fast Diffeomorphic Shape Registration at the Shape Seminar.
Mar 2026 Presented our work on Optimal Steps for Fast Diffeomorphic Shape Registration at IABM 2026.
Feb 2025 Participated in the thematic programme Infinite-dimensional Geometry: Theory and Applications at the Erwin Schrödinger International Institute for Mathematics and Physics (ESI), Vienna.
2024 Started contributing to scikit-shapes, an open-source library for geometric data analysis.
Oct 2023 Started my PhD at MyFit Solutions & Inria Paris HEKA, working on shape analysis for medical imaging.
2022 Teaching Assistant for Probability Theory (L2 MIASHS) at Lyon 2 Lumière University.
2019 Completed an internship at Laboratoire ERIC on Hodge Laplacian Clustering and Deep Neural Networks through the lens of Sobolev and Neuberger.

PUBLICATIONS

Optimal Steps for Fast Diffeomorphic Shape Registration thumbnail
Optimal Steps for Fast Diffeomorphic Shape Registration
Hadrien Bigo--Balland, Jean Feydy and Tom Boeken
MICCAI 2026

CODE

Open-source Python library for shape analysis and statistical learning on geometric data. Contributor.

TEACHING RESOURCES

Probability Theory course materials for Lyon 2 students (credit to Zied Gharbi and Professor Stephane Chretien):

Cours — Probabilités et ses applications
TD Préliminaire — Ensembles, limites, dérivation
TD1 — Probabilités et probabilités conditionnelles
TD2 — Probabilités et probabilités conditionnelles
TD3 — Lois de probabilités sur les entiers et la droite réelle
TD4 — Variables aléatoires et leurs lois

EDUCATION

Lyon 2 Lumière University

Machine Learning pour l'Intelligence Artificielle

2022–2023

Paris-Saclay University

Mathématiques de l'Aléatoire

2021–2022

Paris-Saclay University

Agrégation de Mathématiques

2020–2021