Soumick Chatterjee

Dr Soumick Chatterjee is a postdoctoral researcher at the Glastonbury group, part of the Genomics Research Centre, focusing on learning latent phenotypes from multimodal imaging primarily using self-supervised deep learning.

Born in the “City of Joy” Calcutta (Kolkata) in India, he started his career as a software entrepreneur in 2011 while finishing his bachelor’s in computer application and a diploma in software engineering at the same time. Then he went on to finish his master’s degree in computer science from St. Xavier’s College, Kolkata, in 2017 and obtained a PhD in computer science (summa cum laude) from Otto von Guericke University Magdeburg, Germany, in 2022. The title of his thesis was “Reducing Artefacts in MRI using Deep Learning: Enhancing Automatic Image Processing Pipelines”. During his PhD, he worked on different applications of deep learning in the field of MRI, and he has developed approaches for undersampled MRI reconstruction, motion correction, supervised and weakly-supervised brain tumour classification and segmentation, automatic vessel segmentation using semi-supervised learning, unsupervised anomaly detection, image registration, etc. His research interest also includes the interpretability and explainability of black-box deep learning models, and he has developed the TorchEsegeta pipeline for the same.

Dr Chatterjee has been part of the winning and second runner-up teams of the CHAOS challenge (IEEE ISBI 2019) and MOOD challenge (MICCAI 2021), respectively, while being part of the team which was one of the Dubai regional finalists at the Hult Prize 2017. He holds several professional certificates from Microsoft and Oracle. He has been a member of the organising committee of the eXabyte 2017 – the tech-fest organised by St. Xavier’s College, Kolkata, has been a co-organiser of IEEE SMC’s ISACT 2021 and 2022 , and of the vessel segmentation challenge “SMILE-UHURA” at IEEE ISBI 2023.” He has published 23 manuscripts (as of January 2023) in major journals and conferences, including Medical Image Analysis, Artificial Intelligence in Medicine, Computers in Biology and Medicine, Magnetic Resonance in Medicine, Journal of Imaging, IEEE EMBC, IEEE EUSIPCO, IEEE IPAS, and many more. Further 6 manuscripts are in review for different journals and are currently published as ArXiv preprints. He has also presented 28 short papers and abstracts at top conferences like MIDL, IEEE ISBI, ISMRM, and ESMRMB. A strong advocate of open science, all of the codes related to his research are publicly available on GitHub.

Email: /
For all his codes, visit his GitHub:
For the complete list of publications, visit his Google scholar profile: or his ResearchGate profile:

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