Hicham Janati

Hicham Janati is an Associate Professor affiliated with INSEA (Rabat) and Télécom Paris, Institut Polytechnique de Paris. His research focuses on machine learning, particularly optimal transport and diffusion models, with applications in data alignment, brain imaging, and domain adaptation. He has presented his work at top-tier conferences like NeurIPS, ICML, and AAAI.

He completed his Master’s and PhD degrees in 2021 at ENSAE Paris under Alexandre Gramfort and Marco Cuturi, focusing on optimal transport in machine learning. After his PhD, he held a postdoctoral position at École Polytechnique in Rémi Flamary’s lab, working on deep learning for domain adaptation.

• 2025: Published Spatio-Temporal Alignments in JMLR
• 2023: Presented Unbalanced Co-Optimal Transport at AAAI
• 2020: Published OT Closed-Form for Gaussians (NeurIPS) and Debiased Sinkhorn Barycenters (ICML)
• 2019: Developed Local OT for Brain Template Estimation (IPMI) and Wasserstein Regularization (AISTATS)

His work bridges theoretical machine learning with practical applications in computational neuroscience and domain adaptation, emphasizing algorithmic innovation and mathematical rigor.