Resume

PhD Student in Statistics

DataStorm

Research on estimation and prediction for irregular trajectories through functional data analysis. Projects for DataStorm clients.

• Application: Load curves of electricity production and consumption.
• Implementation of developed methods in C++, R, and Python.
• Supervisor of an Intership on the estimation of the regularity of noisy functional data.
• Short- and medium-term forecasts of hydroelectric park production.
• R package for deploying hydroelectric production forecast models.
• MCO of a Shiny app for forecasting calls for an energy provider's call centers.
• MCO of a Shiny app for analyzing simulations of the electrical grid's behavior.
• Data preparation and student supervision for the ENSAE Business Data Challenge.

Data Scientist Intern

DataStorm

Anomaly detection in a collection of noisy curves.

• Theoretical study and R implementation of depth functions for data.
• Curve clustering
• Functional linear modeling.

Data Scientist Intern

Inserm - Délégation Régionale Paris 5

Improvement of a Shiny application for medical literature mining.

• Queried PubMed REST API to retrieve articles and extracted keywords using NLP.
• Clustered articles based on keywords.

Research Intern

Consortium pour la Recherche Économique et Sociale (CRES)

Study of income inequality and its evolution in Togo.

• Econometric methods and decomposition of inequality indices.
• Programming in Stata and R.

Application Intern

Institut National de la Statistique du Niger

Study of determinants of food insecurity in Niger.

• Survey data cleaning, imputation, reweighting, GLM.
• Programming in Stata and R.

Application Intern

Institut National de la Statistique du Niger

Descriptive analysis of early marriages in Niger.

• Handling survey data, Descriptive Statistics.
• Programming in SPSS, Stata, and R.

PhD in Applied Mathematics

École Nationale de la Statistique et de l'Analyse de l'Information (ENSAI - Rennes)

Applied Mathematics

• Topic: Robust approach to functional data analysis.
• Supervisors: Valentin Patilea & Myriam Vimond

Research Master's Degree

Université de Rennes 1

Research Master’s in Mathematics and Applications, Fundamental Mathematics track

• Parametric statistics, Non-parametric statistics, Process statistics, etc.

Data Scientist Engineer (Master’s Degree)

École Nationale de la Statistique et de l'Analyse de l'Information (ENSAI - Rennes)

Data Science & Statistical Engineering

• Statistical modeling, Machine learning, Deep learning, Non-linear modeling, Image processing, Processes and forecasting, Quality/Reliability, etc.

Statistician engineer

École Nationale de la Statistique et de l'Analyse Économique (ENSAE-Dakar)

Statistics and decision-making IT

• Statistics, Data mining, Econometrics, Micro/Macroeconomics, Survey methods, IT, etc.

Adaptive prediction for Functional Time Series

In the process of finalization

Soon to be submitted to a journal

Adaptive estimation for Weakly Dependent Functional Time Series

arXiv preprint arXiv:2403.13706

Submitted to a journal