Hassan Maissoro

I am a third-year PhD student at the CREST lab and Datastorm data science consultancy, under the supervision of Valentin Patilea and Myriam Vimond of CREST-ENSAI.

My PhD research focuses on dependent functional data with rough sample paths. Functional data analysis (FDA) involves observations where each unit is a complete curve or trajectory, resulting in a data set comprising N trajectories corresponding to N observation units, modeled by the same underlying stochastic process over a certain domain. Dependent functional data are typically collected sequentially at irregular or regular intervals (e.g., days, weeks, or years) and exhibit serial dependence. These curves, often from fields such as energy, environment, chemistry, physics, medical devices, meteorology, and finance, tend to be highly irregular. My work aims to capture this irregularity through local regularity parameters, enhancing the estimation of key parameters such as the mean function, autocovariance function, and linear predictors for curve reconstruction.

I have a broad interest in statistics, particularly in functional time series (FTS) and their applications in finance, energy, sports, and other areas. I am also interested in the optimal numerical implementation of statistical methods to facilitate their use in professional contexts. Additionally, I aim to explore topics at the intersection of statistics and machine learning.

As I approach the completion of my PhD in Applied Mathematics, I will be available for new opportunities starting February 2025. I am actively seeking post-doctoral positions or roles in industry or finance where I can leverage my expertise to contribute to innovative projects.