Indian Institute of Technology Kharagpur, India
Author Profile
GOOGLE SCHOLAR
🎓 EARLY ACADEMIC PURSUITS
Mr. Asim Manna embarked on his academic journey with a robust foundation in mathematics, earning his Bachelor’s degree from the University of Burdwan and a Master’s in Pure Mathematics from the University of Calcutta. His pursuit of interdisciplinary excellence led him to the Indian Statistical Institute (ISI), Kolkata, where he transitioned into the realm of technology through an M.Tech in Computer Science. Currently, he is pursuing his Ph.D. at the Indian Institute of Technology (IIT) Kharagpur, focusing on Artificial Intelligence with a specialization in computer vision and medical imaging, a domain where he continues to thrive as a research scholar.
🏢 PROFESSIONAL ENDEAVORS
Mr. Manna is presently engaged as a Research Intern at Samsung Research Institute Bangalore, working on cutting-edge image signal processing pipelines. He has previously contributed to the field as a Research Intern at IIT Bhilai, where he explored cryptographic algorithm implementations. His experience as a Teaching Assistant for NPTEL courses on Deep Learning showcases his commitment to academic mentorship and knowledge dissemination.
Mr. Manna’s core research lies in deep learning, hash-based medical image retrieval, and generative models for computer vision, with emphasis on:
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Structured deep neural hashing
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Multimorbidity image retrieval using chest X-rays
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Multi-modal and multi-label medical imaging systems
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Generative methods for HDR imaging and signal fusion
His work has significantly advanced the development of efficient, content-aware, organ-specific, and pathology-sensitive retrieval systems, essential for evidence-based medicine (EBM) and healthcare diagnostics.
🏅 ACADEMIC CITATIONS, ACCOLADES AND RECOGNITION
Mr. Manna’s publications in high-impact, peer-reviewed journals such as Computers in Biology and Medicine, Scientific Reports, and the Journal of Medical Imaging have garnered academic recognition. His collaborative research on OPHash, MeDiANet, and structured hashing for modality-organ-disease retrieval contributes to the growing body of literature in medical AI systems. His participation in international conferences like Pattern Recognition (Springer, Cham) reflects scholarly acknowledgment.
He has also received:
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CSIR-UGC NET Lectureship (AIR-94)
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Swami Vivekananda Merit-cum-Means Scholarship
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Qualified for NBHM Scholarship and Fellowship Exams
🌍 IMPACT AND INFLUENCE
Asim’s research contributes to the transformative role of AI in healthcare, particularly by improving content-based retrieval systems for medical diagnostics. His participation in global competitions like the NTIRE 2025 Image Denoising Challenge, where he achieved a top 5 global ranking, reflects the practical excellence and competitiveness of his work. His leadership as a Plenary Chair at the Kharagpur Digital Health Symposium further exemplifies his influence within academic and industrial circles.
🧭 LEGACY AND FUTURE CONTRIBUTIONS
Mr. Manna’s body of work stands at the intersection of mathematical rigor and real-world AI applications, aiming to revolutionize healthcare imaging through scalable, explainable, and secure AI solutions. With a strong foundation in hash learning, generative AI, and medical image understanding, he is poised to contribute toward building intelligent clinical decision systems, federated diagnostic networks, and resource-optimized AI pipelines for edge deployment.
His long-term vision includes:
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Expanding AI applications to resource-constrained medical infrastructures
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Enhancing interpretability in deep learning frameworks
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Contributing to open-source medical imaging libraries for global researchers
✅CONCLUSION
Mr. Asim Manna exemplifies the emerging class of researchers who are pioneering the convergence of mathematics, artificial intelligence, and healthcare. Through his innovative research, academic leadership, and global collaboration, he is contributing meaningfully to both theoretical advancements and practical solutions in AI for medical image analysis. With a track record of technical mastery, scholarly excellence, and impactful contributions, his future as a thought leader in AI-driven medical technologies is both promising and transformative.
🔬NOTABLE PUBLICATION:
Title: The tenth NTIRE 2025 image denoising challenge report
Authors: L. Sun, H. Guo, B. Ren, L. Van Gool, R. Timofte, Y. Li
Journal/Conference: Proceedings of the Computer Vision and Pattern Recognition Conference, pp. 1342–1369
Year: 2025
Title: FedERA: Framework for Federated Learning with Diversified Edge Resource Allocation
Authors: A. Borthakur, A. Kasliwal, A. Manna, D. Dewan, D. Sheet
Journal/Conference: 2024 2nd International Conference on Federated Learning Technologies and Applications (FLTA)
Year: 2024
Title: Structured hashing with deep learning for modality, organ, and disease content sensitive medical image retrieval
Authors: A. Manna, D. Dewan, D. Sheet
Journal/Conference: Scientific Reports, Volume 15 (1), Article 8912
Year: 2025
Title: Deep neural hashing for content-based medical image retrieval: A survey
Authors: A. Manna, R. Sista, D. Sheet
Journal/Conference: Computers in Biology and Medicine, Volume 196, Article 110547
Year: 2025
Title: OPHash: Learning of organ and pathology context-sensitive hashing for medical image retrieval
Authors: A. Manna, R. Sathish, R. Sethuraman, D. Sheet
Journal/Conference: Journal of Medical Imaging, Volume 12 (1), Article 017503-017503
Year: 2025