Sivakamasundari | Computer Science | Best Researcher Award

Published-on by Indian Scientist

Ms. Sivakamasundari | Computer Science | Best Researcher Award

SRM Institute of Science and Technology | India

Ms. P. Sivakamasundari is a dedicated academic and researcher in Computer Science and Engineering, recognized for her contributions to deep learning-based medical image analysis. With qualifications spanning Diploma, Bachelor’s, and Master’s degrees in Computer Science and Engineering, she is currently pursuing her Ph.D. at SRM Institute of Science and Technology. She has extensive teaching experience as an Assistant Professor for more than a decade, during which she has guided students in core computing subjects including algorithms, computation theory, compiler design, and image classification. Her research focuses on advanced deep learning frameworks for healthcare applications, particularly diabetic retinopathy and diabetic foot ulcer detection, resulting in book chapters, conference publications, and journal manuscripts under review. She has published and filed patents related to medical imaging and automated disease detection systems, demonstrating her innovation-driven approach. Her scholarly presence includes 1 citation, 1 h-index, and 0 i10-index, indicating emerging research visibility. She has completed multiple professional certifications and participated in workshops, FDPs, and internships in machine learning, biometrics, accelerated computing, and high-performance healthcare analytics. Her work reflects strong commitment toward applying AI for societal benefit, and she continues to advance her expertise through active research and academic contributions.

Profile: Google Scholar

Featured Publications

Sivakamasundari, P., Anandhi, S., Kumaran, A. A., Vijayakumar, K., Birnica, Y. J., & others. (2024). Early detection of glaucoma utilizing retinal nerve fiber layer (RNFL) investigation. International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems.

Sivakamasundari, P., & Niranjana, G. (2025). An automatic detection and classification of diabetic foot ulcers using Chebyshev chaotic ladybug beetle optimized extended Swin Transformer–InceptionV3 model. Biomedical Signal Processing and Control, 110, 108268.

Gomathi, G., Sumathy, V., Sivakamasundari, P., & Deepa, R. (2024). A various approaches of machine learning algorithms for kidney disease prediction. International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems.

Sivakamasundari, P., & Niranjana, G. (2024). Diabetic foot ulcer classification using deep learning approach. International Conference on Computer, Communication and Signal Processing (ICCCSP).

Sivakamasundari, P., & Niranjana, G. (2023). A critique on deep learning methodologies employed for the identification of diabetic retinopathy using fundus images. Intelligent Computing and Control for Engineering and Business Systems (ICCEBS).

Banushri S | Deep Learning | Best Researcher Award

Published-on by Indian Scientist

Mrs. Banushri S | Deep Learning | Best Researcher Award

Impact College of Engineering and Applied Sciences| India

Dr. Banushri S is an accomplished academician and researcher in Computer Science and Engineering, recognized for her contributions to machine learning, deep learning, image processing, and human activity recognition. She has published impactful research across reputed journals and conferences, contributing to the scientific community with multiple documents, citations, and an evolving h-index that reflects her growing influence in the field. Her academic journey includes strong foundational degrees in engineering and digital electronics, shaping her expertise in logic design, embedded systems, computer architecture, networking, operating systems, programming, and advanced AI-driven technologies. With extensive teaching experience as an Assistant Professor in leading engineering institutions, she has guided numerous undergraduate and postgraduate learners, supervised research projects, and supported curriculum development and departmental academic activities. Her research works span areas such as fall detection, wearable sensor data analysis, transfer learning, and long-range context modeling for human activity recognition, including contributions indexed in Scopus and other reputed platforms. She has actively participated in faculty development programs, workshops, and conferences focusing on artificial intelligence, computer vision, and full-stack technologies, while also being a member of professional bodies like ISTE and CSI. Her work reflects a commitment to advancing intelligent systems research and contributing to academic excellence.

Profile: Scopus

Featured Publications

Banushri, S. (2026). Attention-guided residual shrinkage with gated recurrent unit for human activity recognition. Information Processing and Management.

Asim Manna | Artificial Intelligence | Best Researcher Award

Published-on by Indian Scientist

Mr. Asim Manna | Artificial Intelligence | Best Researcher Award

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.

📚 CONTRIBUTIONS AND RESEARCH FOCUS IN ARTIFICIAL INTELLIGENCE

Mr. Manna’s core research lies in deep learning, hash-based medical image retrieval, and generative models for computer vision, with emphasis on:

  • Structured deep neural hashing

  • Multimorbidity image retrieval using chest X-rays

  • Multi-modal and multi-label medical imaging systems

  • 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:

  • CSIR-UGC NET Lectureship (AIR-94)

  • Swami Vivekananda Merit-cum-Means Scholarship

  • 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:

  • Expanding AI applications to resource-constrained medical infrastructures

  • Enhancing interpretability in deep learning frameworks

  • 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

Vaibhav C. Gandhi | Computer Science | Best Researcher Award

Published-on by Indian Scientist

Mr. Vaibhav C. Gandhi | Computer Science | Best Researcher Award

Madhuben and Bhanubhai Patel Institute of Technology (MBIT) The Charutar Vidya Mandal (CVM) University, India

Author Profile

GOOGLE SCHOLAR

🎓 EARLY ACADEMIC PURSUITS

Prof. Vaibhav C. Gandhi embarked on his academic journey with a Bachelor’s degree in Computer Engineering from Gujarat University in 2011. Fuelled by a keen interest in computing and intelligent systems, he completed his Master’s degree in Computer Engineering from Gujarat Technological University in 2013. His foundational education laid a robust platform for a future steeped in academic inquiry and technological innovation.

🏢 PROFESSIONAL ENDEAVORS

Prof. Gandhi brings over 13 years of rich academic experience and 1.5 years in the IT industry. His academic career includes tenure at esteemed institutions such as:

  • Charusat University

  • Navrachana University

  • Parul University

  • Gujarat Technological University

  • MBIT – Charutar Vidya Mandal University, where he currently serves as Assistant Professor.

In the IT domain, he worked as a Software Developer at Odysseus Solutions, Vadodara, acquiring critical skills in:

  • ASP.NET, MVC, C#

  • Scrum Master methodologies

  • SQL Server, GitHub, Postman, and Web Services

📚 CONTRIBUTIONS AND RESEARCH FOCUS IN COMPUTER SCIENCE

Prof. Gandhi’s research bridges core areas of Computer Vision, Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), and Data Mining, with a strong interdisciplinary emphasis on healthcare applications—notably the early detection of Glaucoma Disease using CNNs and image processing.

He is currently pursuing his Ph.D. in Machine Learning and Deep Learning from Gujarat Technological University, further solidifying his specialization in medical diagnostics powered by intelligent algorithms.

🏅 ACADEMIC CITATIONS, ACCOLADES AND RECOGNITION

Prof. Gandhi has authored over 25+ publications, including research papers and book chapters in internationally reputed platforms such as:

  • Springer

  • Web of Science

  • Wiley Scrivener Publishing

  • Apple Academic Press – CRC, Taylor and Francis Group

He is a recognized member of notable global and national bodies:

  • ISTE – Indian Society for Technical Education

  • IAENG – International Association of Engineers

  • SDIWC – Society of Digital Information and Wireless Communications

🌍 IMPACT AND INFLUENCE

Prof. Gandhi’s influence extends beyond the classroom. He has delivered numerous expert sessions and FDP lectures at prestigious institutions such as:

  • IIT Roorkee (Image Processing & Pattern Recognition)

  • M.S. University, Vadodara

  • Shri Vishnu Engineering College for Women, Andhra Pradesh

  • Bonam Venkatachalamayya Engineering College, Andhra Pradesh

Through these platforms, he has mentored faculty, researchers, and students, sharing deep insights into:

  • Generative AI

  • Convolutional Neural Networks (CNNs)

  • MLOPs (Machine Learning Operations)

  • Medical Image Enhancement and Analysis

🧭 LEGACY AND FUTURE CONTRIBUTIONS

Prof. Gandhi’s legacy lies in his hybrid academic-industry background, his pedagogical innovations, and his pioneering research in AI for healthcare. His future contributions are expected to further evolve the use of ML/DL in biomedical diagnostics, enhance faculty training in AI systems, and build collaborative research ecosystems across institutions.

 ✅CONCLUSION

Prof. Vaibhav C. Gandhi exemplifies a committed academician and technologist whose work harmonizes rigorous scholarship, impactful teaching, and real-world problem solving. With a visionary outlook toward AI-led healthcare diagnostics, he continues to shape minds, mentor scholars, and drive innovation in computer science.

🔬NOTABLE PUBLICATION:

Title: A Survey: Background Subtraction Techniques
Authors: H.M. Desai, V. Gandhi
Journal: International Journal of Scientific & Engineering Research
Year: 2014

Title: Review on Comparison between Text Classification Algorithms
Authors: Vaibhav C. Gandhi, Jignesh A. Prajapati
Journal: International Journal of Emerging Trends & Technology in Computer Science
Year: 2012

Title: A Survey – Insights of ML and DL in Health Domain
Authors: V.C. Gandhi, P.P. Gandhi
Conference: 2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS)
Year: 2022

Title: Forecasting Maternal Women’s Health Risks using Random Forest Classifier
Authors: D. Thakkar, V.C. Gandhi, D. Trivedi
Conference: 2024 International Conference on Inventive Computation Technologies (ICICT)
Year: 2024

Title: Cloud Computing with Data Warehousing
Authors: V.C. Gandhi, J.A. Prajapati, P.A. Darji
Journal: International Journal of Emerging Trends & Technology in Computer Science
Year: 2012