Saurabh Bilgaiyan

Artificial Intelligence, Machine Learning/Deep Learning, Medical Image Analysis, and Software Engineering

Ph.D. in Computer Science and Engineering from KIIT Deemed to be University in 2018, following his M.Tech. (2014) from KIIT and B.E. (2012) from BIRT, affiliated with Rajiv Gandhi Proudyogiki Vishwavidyalaya (RGPV), Bhopal

• 1. Expert Committee Member of National Innovation & Startup Policy, MHRD's Innovation Cell, AICTE from KIIT (For CS&E)
• 2.Member of International Student Academic Committee, IRO, KIIT-DU
• 3. Superintendent, KP-25-I,

Software Engineering, Software Project Management, Agile Software Development, Operating Systems

1. Awarded for outstanding contribution in reviewing by Journal of King Saud University-Computer and Information Sciences, Elsevier.
2. Best presentation award in 41st Annual Conference of the Odisha Mathematical Society & International Conference on Industrial Mathematics and Scientific Computing.
3. Delivered Guest Lecture (Faculty Development Programme ) on LaTex at GITA, Bhubaneshwar, Odisha.

IAENG

ICDCIT Springer, ISAC ACM, CINE, IEEE, ASSIC IEEE

• 1. Choudhury, S., Pandey, A., Mishra, R., Sahu, S., & BILGAIYAN, S. (n.d.). Water dispenser
• system with temperature recording. . Indian Patent Grant. 2026
• 2. MYTHILI, R. and MANOHAR, S. and SRIDEVI, R. and LAXMI, M. V. and DAWANDE, N. A. and GANAPATHY, B. S. and SUGANTHI, M. and PATEL, M. G. and BILGAIYAN, S. and SAGNIKA, S. and ASHOK, S. and ARUN, M. R.. Artificial intelligence based smart cyber attack
• detection in iot wireless networks. Indian Patent Grant. 2023

76

• Kumar, B. K., Bilgaiyan, S., & Sameera, V. K. (2025). The application of machine learning and deep learning algorithms for estimation of software development effort (sde). In H. Das & C. Pradhan (Eds.), Intelligent technologies (4th ed., p. 1). Springer Singapore.
• 10.1007/978-981-96-5585-4 4 Banerjee, P., Bilgaiyan, S., & Tikmani, A. (2022b). Covid-19 test report and vaccine certificate verification through blockchain and e-commerce. In S. Bilgaiyan, J. Singh, & H. Das (Eds.), Empirical research for futuristic e-commerce systems: foundations and applications (1st ed., Chap. 9, pp. 181–195). IGI Global.
• 10.4018/978-1-6684-4969-1.ch009 5 Bilgaiyan, S., Singh, J., & Das, H. (Eds.). (2022). Empirical research for futuristic e-commerce system: foundations and applications (1st ed.). IGI Global, (Accepted and Under Process). 6 Bilgaiyan, S., Mishra, B. S. P., Ansari, R., & Sagnika, S. (2022). A collaborative cloud model of auto scaling with load balancing for effective e-commerce. In S. Bilgaiyan, J. Singh, & H. Das (Eds.), Empirical research for futuristic e-commerce systems: foundations and applications (1st ed., Chap. 6, pp. 116–130). IGI Global.
• 10.4018/978-1-6684-4969-1.ch006 7 Das, H., Gourisaria, M. K., Sah, B. K., Bilgaiyan, S., Badajena, J. C., & Pattanayak, R. M. (2022). E-healthcare system for disease detection based on medical image classification using cnn. In S. Bilgaiyan, J. Singh, & H. Das (Eds.), Empirical research for futuristic e-commerce systems: foundations and applications (1st ed., Chap. 11, pp. 213–230). IGI Global.
• 10.4018/978-1-6684-4969-1.ch011 8 Sagnika, S., Das, N., Pandey, S., & Bilgaiyan, S. (2022). Analytical review on techniques and challenges in sentiment analysis. In S. Bilgaiyan, J. Singh, & H. Das (Eds.), Empirical research for futuristic e-commerce systems: foundations and applications (1st ed., Chap. 7, pp. 131–158). IGI Global.
• 10.4018/978-1-6684-4969-1.ch007 9 Sarmah, P., Das, R., Dhamija, S., Bilgaiyan, S., & Mishra, B. S. P. (2022). Facial identification expression-based attendance monitoring and emotion detection—a deep cnn approach. In P. Sarangi, M. Panda, S. Mishra, B. S. P. Mishra, & B. Majhi (Eds.), Machine learning for biometrics: concepts, algorithms, and applications (1st ed., pp. 155–176). Elsevier.
• https://www.elsevier.com/books/machine-learning-for-biometrics/sarangi/978-0- 323-85209-8 10 Tikmani, A., Bilgaiyan, S., Mishra, B., & Sagnika, S. (2022). A systematic review on blockchain technology: concepts, applications, and prospects in healthcare. In S. Mishra, H. Tripathy, P. Mallick, & K. Shaalan (Eds.), Augmented intelligence in healthcare: a pragmatic and integrated analysis (1st ed., Vol. 1024, pp. 315–354). Springer, Singapore.
• https://doi.org/10.1007/978-981-19-1076-0_17 11 Bilgaiyan, S., Panigrahi, P. K., & Mishra, S. (2020). Chaos-based modified morphological genetic algorithm for effort estimation in agile software development. In J. Singh, Bilgaiyan, S., B. S. P. Mishra, & S. Dehuri (Eds.), A journey towards bio-inspired techniques in software engineering (1st ed., Chap. 6, Vol. 185, pp. 89–102). Springer Nature Switzerland AG: Springer International Publishing. 12 Goswami, D. K., Chakrabarti, S., & Bilgaiyan, S. (2020). Effort estimation of web based applications using erd, use case point method and machine learning. In S. C. Satapathy, A. K. Jena, J. Singh, & Bilgaiyan, S. (Eds.), Automated software engineering: a deep learning-based approach (1st ed., Chap. 2, Vol. 8, pp. 19–37). Springer Nature Switzerland AG: Springer International Publishing. 13 Satapathy, S. C., Jena, A. K., Singh, J., & Bilgaiyan, S. (2020). Automated software engineering: a deep learning-based approach (1st ed.) (G. A. Tsihrintzis, M. Virvou, & L. C. Jain, Eds.). Springer Nature Switzerland AG: Springer International Publishing. 14 Singh, J., Bilgaiyan, S., Mishra, B. S. P., & Dehuri, S. (2020). A journey towards bio-inspired techniques in software engineering (1st ed.) (J. Kacprzyk & L. C. Jain, Eds.). Springer Nature Switzerland AG: Springer International Publishing.