Martin Zach

Martin Zach is a postdoctoral researcher at the Center for Biomedical Imaging (CIBM), EPFL, specializing in inverse problems in biomedical imaging. He joined the Mathematical Imaging Section under the supervision of Prof. Michael Unser in September 2024.

• PhD: Graz University of Technology (2024), advised by Thomas Pock

Martin’s research bridges model-based reconstructions and data-driven approaches in imaging, with a focus on MRI reconstruction and diffusion models. His work explores regularization techniques, energy-based priors, and probabilistic modeling. Recent publications highlight advancements in Gaussian mixture models, non-linear inversion, and Langevin sampling for biomedical imaging.

His Google Scholar profile reveals a strong focus on inverse problems (2020–2025), with applications in MRI, CT, and quantitative phase imaging. Key methodologies include diffusion models, generative priors, and regularization algorithms, spanning disciplines from machine learning to computational biology.

Martin’s current role at EPFL involves collaborative research in mathematical imaging, with affiliations to the BioMedical Imaging (BIG) Group in Lausanne, Switzerland.