Deep Learning, Representation Learning, Generative Models, Latent Space Analysis, Alzheimer's Disease (AD) and Neurodegeneration, XAI (Explainable Artificial Intelligence), Imaging Genetics

• DeSBi: DFG KI-FOR 5363 Fusing Deep Learning and Statistics towards Understanding Structured Biomedical Data
• Syreal - Synthesizing realistic medical images: A BMBF-funded collaboration of 7 partners, aiming to generate realistic medical images to to address limitations in medical AI applications..

Chatterjee, Soumick, Mario Breitkopf, Chompunuch Sarasaen, Hadya Yassin, Georg Rose, Andreas Nürnberger, and Oliver Speck. "ReconResNet: Regularised residual learning for MR image reconstruction of Undersampled Cartesian and Radial data." Computers in Biology and Medicine 143 (2022): 105321.

Hecht, Nils, Hadya Yassin, Marcus Czabanka, Bettina Föhre, Klaus Arden, Thomas Liebig, and Peter Vajkoczy. "Intraoperative computed tomography versus 3D C-arm imaging for navigated spinal instrumentation." Spine 43, no. 5 (2018): 370-377.

Chatterjee, Soumick, Hadya Yassin, Florian Dubost, Andreas Nürnberger, and Oliver Speck. "Learning to segment brain tumours using an explainable classiêer." In: Conference: ISMRM-ESMRMB 2022, ResearchGATE - Cambridge, Mass.: ResearchGATE Corp. . - 2022, insges. 4 S.

Chatterjee, Soumick, Hadya Yassin, Florian Dubost, Andreas Nürnberger, and Oliver Speck. "Weakly-supervised segmentation using inherently-explainable classification models and their application to brain tumour classification." arXiv preprint arXiv:2206.05148 (2022).

• Tutor & Administration 23: Introduction to Deep Learning
• Lectures in block-seminar 22/23: Python for Data Science in Digital Health
• Master project 22/23: Genome-wide association studies of MRI imaging phenotypes
• Tutor for a project 22/23: Advanced Machine Learning Seminar