Yassine MHIRI

Yassine MHIRI is an Associate Professor at the LISTIC laboratory of Université Savoie Mont Blanc. His research focuses on statistical signal and image processing, computational imaging, and their applications in radio-interferometry, hyperspectral imaging, and sensor arrays. Key contributions include methodologies for robust statistical modeling, unrolled algorithms, and plug-and-play neural networks. He holds a Ph.D. from Université Paris-Saclay and conducted postdoctoral research at Université Paris Cité on hyperspectral imaging within the ANR project Fu-MultiSpoc.

• Education:
  • Ph.D. in Statistical Signal Processing (2023), Université Paris-Saclay
  • M.S. in Electronics and Signal Processing (2018), ENSEEIHT, Toulouse
• Professional Experience:
  • Associate Professor (2024–present), LISTIC, Université Savoie Mont Blanc
  • Postdoctoral Researcher (2023–2024), MAP5 Lab, Université Paris Cité
  • PhD Research (2020–2023), SATIE Lab, Université Paris-Saclay
  • Research Engineer (2019–2020), Phasics (wavefront sensor algorithms)

His research integrates statistical learning, inverse problems, and neural networks to address challenges in radio interferometry and hyperspectral imaging. Notable work includes developing the pfb-clean library for MeerKAT telescope imaging and advancing robust EM algorithms for outlier-resistant imaging. His recent focus includes hyperspectral denoising and Fourier-based reconstruction techniques.

Grants & Projects: ANR Fu-MultiSpoc (hyperspectral imager development), contributions to the Africanus imaging suite.

Labs & Collaborations: LISTIC (current), SATIE (PhD), MAP5 Lab (postdoc), and Gipsa-Lab (collaboration).