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About me

I am a researcher in applied mathematics, working at the intersection of robust statistics, Riemannian geometry and statistical learning, with applications in signal processing, in particular, electroencephalography (EEG) and brain–computer interfaces.

My PhD research focuses on developing robust statistical and geometric methods for learning from covariance matrices, motivated by real-world noisy and heterogeneous data.

Research interests

• Robust statistics
• Riemannian geometry
• Statistical learning on manifolds
• Covariance matrix modeling
• Out-of-distribution generalization
• Signal processing (in particular EEG)
• Information geometry
• Also interested in: diffusion models, Physics-informed neural network (PINN), geometry-aware architectures, quantification of information flow

Contact

• Email: imenayadi3005@gmail.com
• GitHub: https://github.com/IA3005
• Google Scholar: https://scholar.google.com/citations?user=3MCnxlgAAAAJ&hl=fr