Félix Chavelli

Ph.D. Student · Inria Paris & ENS – PSL

Hi there! I am Félix Chavelli, a second year Ph.D. student in Computer Science at Inria Paris and École normale supérieure - PSL University, within the VALDA team. My research focuses on segmentation, representation and interpretability in time series. I am supervised by Paul Boniol and Michael Thomazo.

Prior to this, I completed a double M.Sc. program in Computer Science at the National University of Singapore and in Applied Mathematics at ENSTA Paris - Institut Polytechnique de Paris. I previously earned a B.Sc. in Applied Mathematics at Université de Toulouse. See my full CV for details.

ECML-PKDD 2026

tsseg: An Interactive Toolkit for Time Series Segmentation Félix Chavelli, Arik Ermshaus, Fan Yang, Patrick Schäfer, John Paparrizos, Paul Boniol European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases Code Demo
NeurIPS 2025

Toward Interpretable Evaluation Measures for Time Series Segmentation Félix Chavelli, Paul Boniol, Michaël Thomazo Thirty-Ninth Conference on Neural Information Processing Systems PDF Code
NeurIPS 2024

Physics-informed Discovery of State Variables in Second-Order and Hamiltonian Systems Félix Chavelli, Zi-Yu Khoo, Dawen Wu, Jonathan Sze Choong Low, Stéphane Bressan Machine Learning and the Physical Sciences Workshop, NeurIPS PDF

tsseg
Python library · time series segmentation
30+ segmentation algorithms, evaluation metrics, data loaders and real-world benchmarks behind a single unified API, covering both change point detection and state detection.
GitHub Try it online
tsseg-eval
Python package · interpretable evaluation
Interpretable evaluation measure for time series segmentation. Reference implementation for the NeurIPS'25 paper.
GitHub Paper

All software

I lecture The Art of Computer Programming in the International Bachelor of Science in AI at PSL University. Algorithms, data structures and object-oriented programming in Python and C++.