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Curriculum vitae of Saikat Roy — education, experience, publications, and awards.
General Information
| Full Name | Saikat Roy |
| Location | Heidelberg, Germany |
| contact@saikatroy.me |
Education
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2023 - 2026 Ph.D., Computer Science
Heidelberg University, Heidelberg, Germany - Thesis: Transformers and Self-Attention for Medical Image Segmentation
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2017 - 2021 M.Sc., Computer Science
University of Bonn, Bonn, Germany - Thesis: Fully-3D Deep CNNs for Segmentation of Neuroanatomy
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2013 - 2015 M.E., Software Engineering
Jadavpur University, Kolkata, India - Thesis: Supervised-Layerwise Training of Deep CNNs for Classification
Experience
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May 2026 - Present Senior Machine Learning Engineer
mediaire GmbH, Berlin, Germany - Leading AI development for MRI-based medical image analysis products.
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Oct. 2025 - Present Visiting Researcher
Diagnostic Image Analysis Group (DIAG), Radboud University Medical Center, Nijmegen, Netherlands - AI for prostate cancer diagnosis.
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Mar. 2021 - Feb. 2026 Doctoral Researcher (Full-Time)
German Cancer Research Center (DKFZ), Heidelberg, Germany - Developed one of the highest-cited CNN architectures of the last 2 years, using Transformer-based insights, for 3D medical image segmentation.
- Research topics: semantic segmentation, Transformers, representation learning, transfer learning, self-supervised training, foundation models.
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Jul. 2024 - Nov. 2024 Research Intern (Full-Time)
Siemens Healthineers, Princeton, USA - Developed patch-based diffusion models for medical image denoising and super-resolution at 25% less memory with no performance loss.
- Research topics: diffusion models, denoising, super-resolution.
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Nov. 2018 - Feb. 2021 Research Assistant (Half-Time)
German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany - Developed spatially ensembled 3D deep convolutional neural networks for state-of-the-art segmentation of 95 structures in brain MRIs in 30 seconds.
- Research topics: semantic segmentation, deep CNNs, neuroimaging.
Publications (Selected)
- Primus: Enforcing Attention Usage for 3D Medical Image Segmentation. TMLR, 2026. Details
- Investigating the Feasibility of Patch-Based Inference for Generalized Diffusion Priors in Inverse Problems for Medical Images. IEEE ISBI, 2025. Oral Presentation. Details
- Skeleton Recall Loss for Connectivity Conserving and Resource Efficient Segmentation of Thin Tubular Structures. ECCV, 2024. 100+ citations. Details
- Touchstone Benchmark: Are We on the Right Way for Evaluating AI Algorithms for Medical Segmentation? NeurIPS, 2024. Benchmark Win: MedNeXt. Details
- nnU-Net Revisited: A Call for Rigorous Validation in 3D Medical Image Segmentation. MICCAI, 2024. Benchmark Win: MedNeXt, 700+ citations. Details
- MedNeXt: Transformer-driven Scaling of ConvNets for Medical Image Segmentation. MICCAI, 2023. Early Accept: Top 14%, 700+ citations. Details
- See the full publications page for the complete list.
Open Source Projects
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Author & maintainer MIC-DKFZ/MedNeXt
- 500+ stars.
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Contributor MIC-DKFZ/nnUNet (nnunetv1 branch)
- 1000+ stars.
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Contributor MIC-DKFZ/batchgenerators
- 500+ stars.
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Contributor Deep-MI/3d-neuro-seg
- 250+ stars.
Talks and Research Visits
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2026 Speaker on MedNeXt-v2 at Raysearch Laboratories, Sweden
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2026 Speaker at Sprint AI Training for African Medical Imaging Knowledge Translation (SPARK) Academy
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2025 Research visit to Diagnostic Image Analysis Group (DIAG), Radboud UMC, Netherlands
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2025 Speaker at Machine Learning Galore Talks, Heidelberg University, Germany
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2024 Keynote speaker, MICCAI 2024 Challenge: "Body Maps: Towards a 3D Atlas of the Human Body"
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2023 Research talk and visit to Luxembourg Centre for Systems Biomedicine, University of Luxembourg
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2023 Invited talk at Medical and Environmental Computing Lab, TU Darmstadt, Germany
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2022 - 2023 Tutorial: "Transformers in Medical Image Analysis", BVM, Germany
Honors and Awards
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2021 - Oxford Machine Learning (OxML) Summer School
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2015 - Erasmus Mundus FUSION Scholarship for PhD mobility to University of Evora, Portugal (offer not accepted)
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2013 - 2015 - GATE Scholarship for Master's Degree, Ministry of Human Resources & Development, Government of India
Academic Interests
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Research
- Machine Learning
- Semantic Segmentation
- Transformers
- Diffusion Models
- Representation Learning
- Transfer Learning
- Predictive and Generative Problems in Medical Image Analysis
Skills
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Proficient
- Python
- NumPy
- PyTorch
- Scikit-Learn
- Git
- LaTeX
- Matplotlib
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Familiar
- Shell Scripting
- Pandas
- SciPy
- Docker
- PyTest
- C
- SQL
- Matlab
- Keras
- HPC (LSF, SLURM)
Reviewer Assignments
- Conference on Neural Information Processing Systems (NeurIPS), 2026
- International Conference on Learning Representations (ICLR), 2025 - Present
- IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2025 - Present
- International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024 - Present
- IEEE Transactions on Image Processing, 2024 - Present
- IEEE Transactions on Neural Networks and Learning Systems, 2023 - Present
- IEEE Transactions on Medical Imaging, 2023 - Present