cv

PhD Candidate

Orange Labs / INRIA - IRISA

PhD program in partnership with Orange Innovation Labs and the IRISA Research Institute.

• Deep generative modeling with applications on tabular data.

Work-study program

Kurmi Software

Work-study program as part of my master's degree in big data

• Developed connectors for the Microsoft Office 365 suite (Powershell, Java, Javascript)
• Developed and correcting tests for the software suite Kurmi
• Extraction of usage patterns from Kurmi logs to segment users (Python, Java, KNIME, Power BI)
• Identified improvement opportunities and participated in prioritizing functional developments for Kurmi

DRUID team trainee

INRIA - IRISA

Trainee to validate my Bachelor's degree. Technical environment: python and common libraries for data analysis and visualization (NLTK, BeautifulSoup, NetworkX, Pandas, Numpy, Scikit‑learn, Matplotlib, Seaborn, etc.).

• Studied the evolution of science through large graph exploration and natural language processing (NLP - NetworkX)
• Retrieved and preprocessed arXiv scientific articles through API integration, leveraging Python, NLTK, and BeautifulSoup
• Performed intensive processing using a high-performance computing (HPC) platform

Artificial intelligence intern, then technical management assistant.

Machine Intelligence For You (MIFY)

Post-graduate work experience in machine learning.

• Collected data using a graphics tablet and exported it to support a machine learning algorithm for forged signature detection
• Jointly delivered a Microsoft Excel training program within the company SUNU Assurances
• Facilitated brainstorming sessions and managed team coordination
• Improved the company's website SEO and page loading times

PhD

University of Rennes, Rennes, France

Computer science

• Deep generative modeling with applications on tabular data

Bachelor's and master's degrees

University of Rennes, Rennes, France

Computer science

• Training professionals to lead large-scale projects at the intersection of business management and IT, leveraging databases and big data technologies.

Bachelor's degree

National School of Applied Economics and Management, Cotonou, Benin

Computer science

• Training professionals in software development and management, focusing on designing, implementing, and overseeing IT solutions for business operations..

Robust Detection of Synthetic Tabular Data under Schema Variability

ArXiv Preprint

Proposed a novel detection method for AI-generated tabular data, employing state-of-the-art generative models.

Synthetic Tabular Data Detection In the Wild

In International Symposium on Intelligent Data Analysis, May 2025

Employed state-of-the-art tabular data generation models to evaluate encoding strategies and detection methods for AI-generated content.

Cross-table Synthetic Tabular Data Detection

Proceedings of the 1st Workshop on GenAI Content Detection (GenAIDetect)

Developed baseline models for synthetic tabular data detection with a cross-table shift (i.e deploying on unseen tables).

Tabular Data Generation Models: An In-Depth Survey and Performance Benchmarks with Extensive Tuning

Neurocomputing Journal

Conducted an extensive benchmark of generative models for tabular data, optimizing hyperparameters, feature encodings, and architectures across 16 datasets, demonstrating the importance of dataset-specific tuning and confirming the competitive performance of diffusion-based models under constrained resources.