Anees Kazi

Research Fellow in Radiology at Harvard Medical School
Research Fellow at Massachusetts General Hospital
Department of Radiology, MGH

akazi1@mgh.harvard.edu

Ph.D., Technical University of Munich

My project mainly is about analyzing brain connectomes using graph deep learning dealing with diffusion MRI-based brain connectome data which will be extended to the interpretability of Graph-based methods. During my time at the Technical University of Munich (Ph.D. and a short postdoc), I worked on deep learning methods for fracture detection, graph deep learning for brain imaging applications, and federated learning methods for histopathology. My goal is to develop expertise in AI for Medical Imaging in general with a niche in graph deep learning in healthcare. I also spent some time at Imperial College London working with prof. Michael Bronstein developed methods for learning graph structures from data. I am deeply involved in organization committees from 2019-present. This includes member (2019), president (2020), and advisory member (2021) of the Student Board @ MICCAI society. Area Chair IPCAI 2022-2023, Area Chair MICCAI 2023, member of Career Development and Mentorship Program 2023 @MICCAI Society, member of the organization committee MICCAI 2024-2025.