PhD Student in Statistics and Machine Learning at Université de Lorraine.

email: raphael dot mignot at univ-lorraine dot fr

I am a PhD Student in the IECL lab at Université de Lorraine (Nancy, France) since January 2021. I am focusing on Statistics and Machine Learning, and especially time series analysis. My advisors are Pr. Marianne Clausel and Pr. Konstantin Usevich. Before that, I earned a BS degree in Mathematics and a MS degree in Applied Mathematics and Data Science both from Sorbonne Université (Paris, France). Moreover, through internships, I have been practicing Data Science at leading companies and research institutes.

I am working on the use of the signature, a tool from rough paths theory, for time series analysis and statistical learning. This tool extract intrinsic information about multidimensional time series and more precisely the dependencies in variations along the space dimensions. Find here an introduction to this tool.

**April 2024:**Workshop Mathematics of data streams: signatures, neural differential equations, and diffusion models in Greifswald, Germany !

**2023/12 Seminar:**Signature, applications and Machine Learning (website). University of Pau and the Adour Region. Pau, France.**2023/11 Group seminar.**University of British Columbia, Dpt. Mathematics. Vancouver, Canada.**2023/11 Probability & Stat. Seminar**(website) Univ. Luxembourg, Dpt. Mathematics. Luxembourg.**2023/10 Workshop:**Mathematical Founding Principles of AI (website) Sorbonne University.**2023/09 Lorraine - Luxembourg Workshop**in Probability and Statistics (website). University of Lorraine & University of Luxembourg.**2023/07 Group seminar**(website). University Lyon 2. Data Science Lab (ERIC). Lyon, France.**2023/06 GDR TRAG**(Research group on Rough Paths) (website). Paris Dauphine University.**2023/01 Group seminar.**University Grenoble–Alpes, Computer Sc. Lab (LIG). Grenoble, France.**2022/09 Annual national conference:**28th GRETSI (Signal and Image Processing) (website). France.**2022/08 Annual national conference:**MAS (Modeling, Stochastic and Statistics) (website). France.**2022/07 Group seminar.**Japan Agency for Marine-Earth Science and Technology. Tokyo, Japan.**2022/06 Annual national conference:**French Statistics Society (website). France.

- J. Cugliari, E. Devijver, A. Meynaoui, and R. Mignot, “Some recent developments on functional data
analysis,” in
*ESAIM: Proceedings and Surveys*, EDP Sciences, 2024, to appear. - R. Mignot, M. Clausel, and K. Usevich, “Principal geodesic analysis for time series encoded with signature features,” preprint hal-04392568, 2024. Software.
- M. Clausel, J. Diehl, R. Mignot, L. Schmitz, N. Sugiura, and K. Usevich, “The barycenter in free nilpotent Lie groups and its application to iterated-integrals signatures”, preprint arXiv:2305.18996, 2023. Software.

- 2022 - 2024 :
**Data Analysis**(Tutorials, 25h each year). Ecole des Mines de Nancy. Level: Graduate.*Topics: R, Linear models, Principal Component Analysis, Factor analysis, Classification, Linear discriminant analysis, Logistic regression, Association rule learning.* - 2021 - 2024 :
**Probability and Statistics**(Tutorials, 20h each year). University of Lorraine. Level: Graduate.*Topics: Point estimation, Confidence intervals, Hypothesis testing (parametric tests, two-sample tests, chi-square tests), Python.*

See Software links in publications.