Bikash Santra

About

I'm an Assistant Professor at the IIT Jodhpur - School of AI and Data Science, where I lead the Machine and Medical Vision Group (MMVG). Previously I was a Postdoc Fellow at NIH, USA. My area of research includes computer vision, machine learning and medical image analysis.

Employment

• Indian Institute of Technology Jodhpur Assistant Professor
  2023 - Present

Education

• Indian Statistical Institute Ph. D.
  2016 - 2021

Projects & Funding

Projects & funding information is unavailable.

Publications (16)

• DINOv2KAN: Kolmogorov–Arnold Network with DINOv2 Vision Transformer for enhanced characterization of Alzheimer’s Disease
  Biomedical Signal Processing and Control 2026 DOI: 10.1016/j.bspc.2026.109975
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• Weakly supervised detection of pheochromocytomas and paragangliomas in CT using noisy data
  Computerized Medical Imaging and Graphics 2024 DOI: 10.1016/j.compmedimag.2024.102419
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• Utilizing domain knowledge to improve intravenous contrast phase classification of CT scans
  Medical Imaging 2024: Computer-Aided Diagnosis 2024 DOI: 10.1117/12.3008785
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• Weakly supervised detection of pheochromocytomas and paragangliomas in CT
  Medical Imaging 2024: Computer-Aided Diagnosis 2024 DOI: 10.1117/12.3008833
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• Anatomical Location-Guided Deep Learning-Based Genetic Cluster Identification of Pheochromocytomas and Paragangliomas from CT Images
  Lecture Notes in Computer Science 2024 DOI: 10.1007/978-3-031-47076-9_7
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• Isolating Features of Object and Its State for Compositional Zero-Shot Learning
  IEEE Transactions on Emerging Topics in Computational Intelligence 2023 DOI: 10.1109/TETCI.2022.3232816
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• Bi-Modal Compositional Network for Feature Disentanglement
  2022 IEEE International Conference on Image Processing (ICIP) 2022 DOI: 10.1109/icip46576.2022.9897457
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• Graph-based modelling of superpixels for automatic identification of empty shelves in supermarkets
  Pattern Recognition 2022 DOI: 10.1016/j.patcog.2022.108627
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• An end-to-end annotation-free machine vision system for detection of products on the rack
  Machine Vision and Applications 2021 DOI: 10.1007/s00138-021-01186-6
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• Graph-based non-maximal suppression for detecting products on the rack
  Pattern Recognition Letters 2020 DOI: 10.1016/j.patrec.2020.09.023
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