- Paper: Application of Convolution Neural Network for Unfolding Simulated Neutron Spectra of an Activation Spectrometer (Submitted)
- Paper: Unmixing Mean Embeddings for Domain Adaptation with Target Label Proportion (Submitted)
- Paper: Bounds in Wasserstein Distance for Locally Stationary Functional Time Series (Submitted)
- Paper: PatchTrAD: A Patch-Based Transformer focusing on Patch-Wise Reconstruction Error for Time Series Anomaly Detection (EUSIPCO 2025)
- Paper: Sparsified-Learning for Heavy-Tailed Locally Stationary Processes (Preprint)
- Paper: Adversarial Semi-Supervised Domain Adaptation for Semantic Segmentation: A New Role for Labeled Target Samples (Computer Vision and Image Understanding)
Research Experience
- 2020 - Present: Maître de Conférences, LMAC, Department of Computer Science, UTC
- 2018 - 2020: Postdoctoral Researcher, LITIS Laboratory, University Rouen Normandy, involved in OATMIL Project
- 2017 - 2018: Postdoctoral Researcher, Modal'X Laboratory, University Paris Nanterre, working with Olga Klopp on collective matrix completion project
- 2017 - 2016: Temporary Teaching Researcher Assistant, Modal'X Laboratory, University Paris Nanterre
Education
- Ph.D. in Statistical Machine Learning, University Pierre and Marie Curie, 2016, Advisors: Stéphane Gaïffas and Agathe Guilloux
- Master of Sciences in Statistics, University Pierre and Marie Curie, 2012
- Master of Sciences in Probabilities and Random Modelling, University Pierre and Marie Curie, 2011
- Magisterium of Mathematics, University Gabes Tunisia, 2010
Background
- Research Interests: Statistics and Machine Learning
- Specialization: Supervised learning in high-dimensional settings, Bridging optimal transport and machine learning
- Brief Introduction: Since September 2020, Assistant Professor of Statistics and Machine Learning at the Université de Technologie de Compiègne (UTC), Department of Computer Science, Laboratory of Applied Mathematics (LMAC).