معرفی
Prof. Fabienne Comte is a Professor at Paris Descartes University, affiliated with the MAP5 Laboratory (UMR 8145) within the UFR of Mathematics and Computer Science. Her research focuses on nonparametric statistics, stochastic processes, and statistical inference, with a strong emphasis on methodological advancements in areas such as diffusion processes, measurement error models, and Lévy processes. She has contributed extensively to peer-reviewed journals, including Electronic Journal of Statistics, Stochastic Processes and Their Applications, and Annals of the Institute of Statistical Mathematics. Comte is also actively involved in academic leadership, co-organizing the Statistics Seminar at Paris Descartes from 2002 to 2009. Her work bridges theoretical developments with practical applications in fields such as econometrics and biostatistics.
- Education: Doctoral thesis on continuous-time stochastic modeling (1994), Habilitation thesis on dependence in statistics and econometrics (2000).
- Research Interests: Nonparametric estimation, stochastic differential equations, multiplicative measurement error models, and kernel-based methods.
Her recent articles highlight advancements in nonparametric methods for McKean-Vlasov equations, diffusion processes, and particle systems. Comte collaborates widely, with co-authors including Valentine Genon-Catalot, Nicolas Marie, and Céline Duval. She has contributed to methodological frameworks for regularization, projection estimators, and adaptive techniques in high-dimensional and complex data settings.
Comte’s academic service includes editorial roles and contributions to international conferences, reflecting her commitment to advancing statistical theory and practice.
