معرفی
Yanis Djebra is a Researcher at Yale University's Yale School of Medicine, Department of Radiology & Biomedical Imaging. He holds a PhD in Medical Imaging from Télécom Paris (2022). His research focuses on advancing medical imaging techniques, particularly in MRI and PET technologies. Key areas include manifold learning (via LTSA models), motion correction in PET/MR, and Bayesian methods for kinetic parameter estimation. Collaborations with experts like Chao Ma, Georges El Fakhri, and Thibault Marin highlight his interdisciplinary work. His publications span journals like Magnetic Resonance in Medicine and IEEE Transactions on Medical Imaging. Djebra is affiliated with the Center for Molecular Imaging and Translation (CMITT) and contributes to projects in accelerated imaging, cardiac T1/ECV mapping, and sparse sampling optimization.
