
Soumya Ranjan Nayak
Assistant Professor
Dr. Soumya Ranjan Nayak is currently working as Senior Assistant Professor in the School of Computer Engineering, Kalinga Institute of Industrial technology (KIIT) Deemed to be University, Odisha. He received his Ph.D and M.Tech degree in Computer Science and Engineering under MHRD Govt. of India fellowship from CET, BPUT Rourkela, India; with a preceded degree of B. Tech and Diploma in Computer Science and Engineering. He has published more than 100 articles in peer-reviewed journals and conferences of international repute like Elsevier, Springer, World Scientific, IOS Press, Taylor & Francis, Hindawi, Inderscience, IGI Global, etc.. Apart from that, 16 Book Chapter, 6 Books and 7 Indian patents (4 patents granted) and two International patents (two patents granted) under his credit. His current research interests include medical image analysis and classification, machine learning, deep learning, pattern recognition, fractal graphics and computer vision. Dr. Nayak serves as an associate editor of Journal of Electronic Imaging (SPIE), Mathematical Problems in Engineering (Hindawi), Journal of Biomedical if Imaging (Hindawi), Applied Computational Intelligence and Soft Computing (Hindawi), and PLOS One. He is also serving as Guest editor for special issues of the journal like Springer Nature, Elsevier, and Taylor & Franchise. He has associated as reviewer of many peer-reviewed reputed journals such as Applied Mathematics and Computation, Journal of Applied Remote Sensing, Mathematical Problems in Engineering, International Journal of Light and Electron optics, Journal of Intelligent and Fuzzy Systems, Future Generation Computer Systems, Pattern Recognition Letters, etc. He has also served as Technical Program Committee Member of several conferences of international repute.
B.Tech, M.Tech, Ph.D
Projects
1. Device for Segregating Objects in Limited Illumination, Application No-201911041599, Grant No-354455 (Indian Patent). 2. Device for Surface Roughness Measurement of an Object, Application No-201911043717, Grant No-366328 (Indian Patent). 3. Machine Learning Based Hand Sanitizer making and Dispensing Machine, Grant No-2021100049 (International Patent). 4. Machine Learning Based Water Purifier and Dispenser, Grant No-2021100437 (International Patent).
Administrative Responsibility
Hostel Dy. Superintendent
Awards & Honours
1. Received MHRD Govt. of India Fellowship (TEQIP-II), 2013-2017 2. Received the Best Teacher award from Odisha Technological Concleve-2024 3. Keynote Speaker in the International Conference on Sustainable Computing-2024 in SBCET, Jaipur, Rajasthan, India. 4. Associate Editor at PLOS One (Scopus, and Web of Science-SCIE). IF-2.9 5. Associate Editor at Journal of Electronic Imaging – SPIE, (Scopus, and Web of Science-SCIE). IF-0.98 6. Academic Editors) at Mathematical Problems in Engineering (MPE) – Hindawi, (Scopus, Web of Science-SCI). IF-1.305 7. Academic Editors at Applied Computational Intelligence and Soft Computing (ACIS) – Hindawi, (Scopus, and Web of Science-ESCI). IF-2.4 8. Academic Editors at International Journal of Biomedical Imaging (JBI) – Hindawi, 2022, (Scopus, and Web of Science-ESCI). IF-3.3 9. Associate Editor at Journal of Cyber Security Technology-Taylor & Francis (Scopus)
Memberships
IEEE, ISTE, IAENG
Outreach Activity
1. National seminar on “Future Trends in Data Warehousing” (NSFTDW-2012) during 29th Sept. 2012 at Vivekananda Institute of Technology, Bhubaneswar. 2. Faculty development programme in “loophole ethical hacking” conducted by AIESEC IIT Kharagpur during December 2012, held at Vivekananda Institute of Technology, Bhubaneswar.
patents:-
1. Safety System for Prenenting Motorcycle Accidents due to Loose Garments (Application No. 202431093604 )
2. AquaVision: Computer Vision-Based Drain Water Leakage Detection System (Application No. 202431083103 )
3. Customer Movement-Based Product Visibility Optimization System for Retail Spaces (Application No. 202431095870 )
4. Real-Time Student Engagement and Comprehension Monitoring System using Computer Vision and Facial Emotion Recognition (Application No. 202431099438 )
Journals/Conferences :
1. Chauhan, S., Edla, D. R., Boddu, V., Rao, M. J., Cheruku, R., Nayak, S. R., ... & Nigat, T. D. (2024). Detection of COVID-19 using edge devices by a light-weight convolutional neural network from chest X-ray images. BMC Medical Imaging, 24(1), 1.
2. Panda, S. K., Barik, R. C., Nayak, S. R., & Panda, G. (2024). Internet of Medical Things-enabled brain tumor classification using GWO-based optimized RBF network. Journal of Electronic Imaging, 33(6), 063046-063046.
3. Nayak, S. R., Selvarasu, S., Sripathy, B., Singh, P., Diwakar, M., Gupta, I., ... & Al Mazroa, A. (2024). A New-fangled Classification Algorithm for Medical Heart Diseases Analysis using Wavelet Transforms. The Open Public Health Journal, 17(1).
4. Swain, K. P., Mohapatra, S. K., Ravi, V., Nayak, S. R., Alahmadi, T. J., Singh, P., & Diwakar, M. (2024). Leveraging Machine Learning and Patient Reviews for Developing a Drug Recommendation System to Reduce Medical Errors. The Open Bioinformatics Journal, 17(1).
5. Chauhan, S., Cheruku, R., Edla, D. R., Kampa, L., Nayak, S. R., Giri, J., ... & Qin, H. (2024). BT-CNN: a balanced binary tree architecture for classification of brain tumour using MRI imaging. Front Physiol 15.
6. Gupta, I., Singh, S., Gupta, S., & Nayak, S. R. (2024). Classification of brain tumours in MRI images using a convolutional neural network. Current Medical Imaging, 20(1), E270323214998.
7. Sharma, K., Sarangi, P. K., Sharma, P., Nayak, S. R., Aluvala, S., & Swain, S. K. (2024). Reconfigurable Neuromorphic Neural Network Architecture. Applied Computational Intelligence and Soft Computing, 2024(1), 6632801.
8. Kumar, S., Singh, M. P., Nayak, S. R., Khan, A. U., Jain, A. K., Singh, P., ... & Soujanya, T. (2023). A new efficient referential genome compression technique for FastQ files. Functional & Integrative Genomics, 23(4), 333.
9. Nayak, T. K., Annavarappu, C. S. R., Nayak, S. R., & Gedefaw, B. M. (2023). DMF-Net: a deep multi-level semantic fusion network for high-resolution chest CT and X-ray image de-noising. BMC Medical Imaging, 23(1), 150.
10. Nayak, S. R., Nayak, J., Sinha, U., Arora, V., Ghosh, U., & Satapathy, S. C. (2023). An automated lightweight deep neural network for diagnosis of COVID-19 from chest X-ray images. Arabian journal for science and engineering, 48(8), 11085-11102.
11. Sahu, A. K., Sahu, M., Patro, P., Sahu, G., & Nayak, S. R. (2023). Dual image-based reversible fragile watermarking scheme for tamper detection and localization. Pattern Analysis and Applications, 26(2), 571-590.
12. Jena, K. K., Bhoi, S. K., Nayak, S. R., Panigrahi, R., & Bhoi, A. K. (2022). Deep convolutional network based machine intelligence model for satellite cloud image classification. Big Data Mining and Analytics, 6(1), 32-43.
13. Ajij, M., Pratihar, S., Nayak, S. R., Hanne, T., & Roy, D. S. (2023). Off-line signature verification using elementary combinations of directional codes from boundary pixels. Neural Computing and Applications, 1-18.
14. Kaur, P., SINGH, M. P., MISHRA, A. M., SHANKAR, A., SINGH, P., DIWAKAR, M., & NAYAK, S. R. (2023). DELM: deep ensemble learning model for multiclass classification of super-resolution leaf disease images. Turkish Journal of Agriculture and Forestry, 47(5), 727-745.
15. Nayak, S. R., Nayak, D. R., Sinha, U., Arora, V., & Pachori, R. B. (2022). An efficient deep learning method for detection of COVID-19 infection using chest X-ray images. Diagnostics, 13(1), 131.
16. Motwani, A., Shukla, P. K., Pawar, M., Kumar, M., Ghosh, U., Alnumay, W., & Nayak, S. R. (2023). Enhanced framework for COVID-19 prediction with computed tomography scan images using dense convolutional neural network and novel loss function. Computers and Electrical Engineering, 105, 108479.
17. Jena, K. K., Nayak, S. R., Bhoi, S. K., Verma, K. D., Prakash, D., & Gupta, A. (2022). A novel service robot assignment approach for COVID-19 infected patients: a case of medical data driven decision making. Multimedia Tools and Applications, 81(29), 41995-42021.
18. Diwakar, M., Singh, P., Shankar, A., Nayak, S. R., Nayak, J., Vimal, S., ... & Sisodia, D. (2022). Directive clustering contrast-based multi-modality medical image fusion for smart healthcare system. Network Modeling Analysis in Health Informatics and Bioinformatics, 11(1), 15.
19. Anand, V., Gupta, S., Nayak, S. R., Koundal, D., Prakash, D., & Verma, K. D. (2022). An automated deep learning models for classification of skin disease using Dermoscopy images: A comprehensive study. Multimedia Tools and Applications, 81(26), 37379-37401.
20. Gupta, I., Nayak, S. R., Gupta, S., Singh, S., Verma, K. D., Gupta, A., & Prakash, D. (2022). A deep learning based approach to detect IDC in histopathology images. Multimedia Tools and Applications, 81(25), 36309-36330.
21. Nayak, S. R., Nayak, J., Vimal, S., Arora, V., & Sinha, U. (2022). An ensemble artificial intelligence‐enabled MIoT for automated diagnosis of malaria parasite. Expert Systems, 39(4), e12906.
22. Anand, V., Gupta, S., Koundal, D., Nayak, S. R., Barsocchi, P., & Bhoi, A. K. (2022). Modified U-net architecture for segmentation of skin lesion. Sensors, 22(3), 867.
23. Gopalakrishnan, S., Sridharan, S., Nayak, S. R., Nayak, J., & Venkataraman, S. (2022). Central hubs prediction for bio networks by directed hypergraph-ga with validation to covid-19 ppi. Pattern Recognition Letters, 153, 246-253.
24. Nayak, S. R., & Mishra, J. (2021). Fractal dimension-based generalized box-counting technique with application to grayscale images. Fractals, 29(03), 2150055.
25. Nayak, S. R., Nayak, D. R., Sinha, U., Arora, V., & Pachori, R. B. (2021). Application of deep learning techniques for detection of COVID-19 cases using chest X-ray images: A comprehensive study. Biomedical Signal Processing and Control, 64, 102365.
Books :
1. Soumya Ranjan Nayak, Janmenjoy Nayak, Khan Muhammad, Yeliz Karaca, Intelligent Fractal Based Image Analysis: Applications in Pattern Recognition and Machine Vision, Elsevier, 2024, ISBN: 9780443184697.
2. R. C. Poonia, V. Singh, and Soumya Ranjan Nayak, Deep Learning for Sustainable Agriculture, Elsevier, 2022, ISBN: 9780323852142.
3. Soumya Ranjan Nayak, B. R. Sahoo, M. Muthukumaran, and J. Mishra, Smart Sensor Networks Using AI for Industry 4.0: Applications and New Opportunities, CRC Press (Taylor & Franchise), 2021, ISBN: 9781003145028.
4. M. Muthukumaran, Soumya Ranjan Nayak, S. N. Panda, and P. K. Pattnaik, Machine Vision Inspection Systems: Machine Learning-Based Approaches, Wiley-Scrivener Publishing, 2021, ISBN: 9781119786092.
5. M. Muthukumaran, Soumya Ranjan Nayak, S. N. Panda, P. K. Pattnaik, and N. Muangnak, Machine Vision Inspection Systems: An Image Processing Approach, Wiley-Scrivener Publishing, 2020, ISBN: 9781119681809.
6. Soumya Ranjan Nayak, and J. Mishra, Examining Fractal Image Processing and Analysis, IGI Global, Advances in Computational Intelligence and Robotics (ACIR), 2019, ISBN: 9781799800668.
Book Chapter Published
1. Gupta, S., Mohanty, S., Behera, D. K., & Nayak, S. R. (2025). AI enhanced healthcare: Opportunities, challenges, ethical considerations, and future risk. Responsible and Explainable Artificial Intelligence in Healthcare, 127-153.
2. Nayak, S. R., & Sinha, U. (2024). Fractal feature based image classification. In Intelligent Fractal-Based Image Analysis (pp. 73-88). Academic Press.
3. Jena, K. K., Bhoi, S. K., & Nayak, S. R. (2024). Analysis of Mandelbrot set fractal images using a machine learning based approach. In Intelligent Fractal-Based Image Analysis (pp. 33-45). Academic Press.
4. Nayak, S. R., & Mishra, J. (2023). Analysis of medical images using fractal geometry. In Research anthology on improving medical imaging techniques for analysis and intervention (pp. 1547-1562). IGI Global.
5. Acharya, S., Ghosh, D., Swapnarekha, H., Mishra, M., & Nayak, S. (2023). Integrative data analysis and automated deep learning technique for ovary cancer detection. In Computational Intelligence in Cancer Diagnosis (pp. 43-65). Academic Press.
6. Sharma, S., Ashu, Gupta, A., & Nayak, S. R. (2022). Quantitative Assessment of Fetal Wellbeing Through CTG Recordings. In Connected e-Health: Integrated IoT and Cloud Computing (pp. 291-310). Cham: Springer International Publishing.
7. Meedeniya, D. A., Mahakalanda, I., Lenadora, D. S., Perera, I., Hewawalpita, S. G. S., Abeysinghe, C., & Nayak, S. R. (2022). Prediction of paddy cultivation using deep learning on land cover variation for sustainable agriculture. In Deep learning for sustainable agriculture (pp. 325-355). Academic Press.
8. Jena, K. K., Bhoi, S. K., Nayak, S. R., & Mallick, C. (2021). Machine learning‐based virus type classification using transmission electron microscopy virus images. Machine Vision Inspection Systems, Volume 2: Machine Learning‐Based Approaches, 1-22.
9. Patel, A. K., Mandhala, V. N., Anguraj, D. K., & Nayak, S. R. (2021). Surface defect detection using SVM‐based machine vision system with optimized feature. Machine Vision Inspection Systems, Volume 2: Machine Learning‐Based Approaches, 109-127.
10. Rajesh Kumar, E., Rama Rao, A. K. V. S. N., & Nayak, S. R. (2020). Emotional level classification and prediction of Tweets in Twitter. Emotion and Information Processing: A Practical approach, 161-169.
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