Saurabh Bilgaiyan
Saurabh Bilgaiyan
Associate Professor
Dr. Saurabh Bilgaiyan holds a distinguished position as a faculty member in the School of Computer Engineering at KIIT, Deemed to be University, Bhubaneswar, India. With a strong passion for both teaching and research, he brings extensive expertise and academic experience to the university’s vibrant learning ecosystem. He earned his Ph.D. in Computer Science & Engineering from KIIT, Deemed to be University in 2018. He holds a Master of Technology (M.Tech) in Computer Science & Engineering from the same institution (2014) and a Bachelor of Engineering (B.E.) from BIRT, under Rajiv Gandhi Proudyogiki Vishwavidyalaya (RGPV), Bhopal (2012). Dr. Bilgaiyan is actively engaged in cutting-edge research and has published extensively in reputed peer-reviewed journals, edited volumes, and conference proceedings. His scholarly contributions have garnered significant recognition in the academic community. He is currently supervising M.Tech and Ph.D. scholars in emerging areas of computer science. He also serves as a reviewer for various prestigious international journals and conferences, further demonstrating his expertise and commitment to academic excellence.
Profile Links
Email :
[email protected]
Website :
sites.google.com
Scopus Id :
56126787500
Google Scholar :
https://scholar.google.co.in/citations?user=ymBNFJ8AAAAJ&hl=en
Social Links
Educational Qualification
Ph.D. (CS&E), M.Tech. (CS&E), B.E. (IT)
Research Interests
soft computing, software engineering, cloud computing, image processing, Blockchain and machine learning.
Administrative Responsibility
Awards & Honours
Outreach Activity
Ph.D. (CS&E), M.Tech. (CS&E), B.E. (IT)
Research Interests
soft computing, software engineering, cloud computing, image processing, Blockchain and machine learning.
Administrative Responsibility
- Expert Committee Member: National Innovation & Startup Policy (NISP), MHRD's Innovation Cell, AICTE — Representing KIIT, Deemed to be University, Bhubaneswar, Odisha, India actively contributing to national-level policy formulation and innovation ecosystem development.
- Member, Centre of Innovation & Research in Electric Vehicles (CIREV): Collaborating on interdisciplinary research and innovation in electric vehicle technologies under the CIREV initiative at KIIT, Deemed to be University, Bhubaneswar, Odisha, India .
- Faculty Coordinator – IT & Web Society: Mentoring students and coordinating co-curricular activities in IT and web development to promote technical and creative skills at KIIT, Deemed to be University, Bhubaneswar, Odisha, India
- Faculty In-Charge – Industry & Institute Collaboration: Facilitating partnerships with industry to enhance academic-industry synergy, internships, expert talks, and collaborative research at School of Computer Engineering, KIIT, Deemed to be University, Bhubaneswar, Odisha, India.
- Superintendent – Boys Hostel: Managing administrative and student welfare responsibilities in one of the university's residential facilities.
- Former Faculty In-Charge – Research E-Magazine, Website, & Booklet: Led the design, development, and publication of the School’s research e-magazine, official website, and institutional booklet to showcase academic and research achievements.
- Former Faculty In-Charge – R&D, Funded Projects, and Consultancy: Led efforts to promote research culture, manage funded projects, and facilitate industry consultancy engagements for the School of Computer Engineering, KIIT, Deemed to be University, Bhubneswar, India
- Member of International Student Academic Committee
- IRO, KIIT-DU
Awards & Honours
- Awarded for outstanding contribution in reviewing by Journal of King Saud University-Computer and Information Sciences, Elsevier.
- Best presentation award in 41st Annual Conference of the Odisha Mathematical Society & International Conference on Industrial Mathematics and Scientific Computing.
- Delivered Guest Lecture (Faculty Development Programme ) on LaTex at GITA, Bhubaneshwar, Odisha.
Outreach Activity
- Delivered Guest Lecture (Faculty Development Programme ) on LaTex at GITA, Bhubaneshwar, Odisha.
- Delivered a guest lecture (During BGI talks) on ”Cloud Computing and Software Engineering: Future Research Perspectives” at BIRT, Bhopal, Madhya Pradesh.
- Worked as Website chair for ACM’s 14th ISEC-2021 Organized jointly by NIT Rourkela and KIIT-DU, Bhubaneswar.
- Worked as PIC chair for Springer's 2oth ICDCIT-2024, Organized KIIT-DU, Bhubaneswar.
Journals/Conferences :
Journal Articles
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1.Beesetti, K., Sundari, M. R., & Bilgaiyan, S. (2025). Topical survey and empirical analysis on methods used to approximate effort in the software development process. International Journal of Productivity and Quality Management, 44. https://doi.org/10.1504/IJPQM.2025.10070339
2.Bilgaiyan, S., Aryan, A., Kumar Nayak, N., & Mishra, P. (2025). Enhancing reliability, security, and scalability of serverless computing for cloud backup in power grids during emergency situations. SN Computer Science, 6(4), 390. https://doi.org/10.1007/s42979-025-03941-2
3.Bilgaiyan, S., Swain, A., Das, S., & Medha. (2025). Advanced fuzzy inference integration with MobileNetV2 for ovarian cyst detection. SN Computer Science, 6(6), 727. https://doi.org/10.1007/s42979-025-04200-0
4.Maiga, S., Bilgaiyan, S., & Sagnika, S. (2025). Predicting software effort using BERT-based word embeddings. International Journal of System Assurance Engineering and Management, 6(390), 1728–1742. https://doi.org/10.1007/s13198-025-02746-z
5.Moharram, M. A., Bilgaiyan, S., & Sagnika, S. (2025). Software effort estimation using cascade neural network optimized based on modified particle swarm optimization (MPSO-CNN). International Journal of Productivity and Quality Management, 44(1), 40–70. https://doi.org/10.1504/IJPQM.2025.143963
6.Saleh, B. M., Bilgaiyan, S., & Sagnika, S. (2025). KanuriSenti: A novel dataset for sentiment analysis in the under-resourced Kanuri language. Data in Brief. https://doi.org/10.1016/j.dib.2025.111758
7.Kumar, B. K., Bilgaiyan, S., & Mishra, B. S. P. (2024). Software effort estimation based on ensemble extreme gradient boosting algorithm and modified Jaya optimization algorithm. International Journal of Computational Intelligence and Applications. https://doi.org/10.1142/S1469026823500323
8.Agrawal, S., Debnath, S., Sagnika, S., Bilgaiyan, S., & Gupta, S. (2023). Hyperspectral image compression using modified convolutional autoencoder. International Journal of Computer Information Systems and Industrial Management Applications, 15, 396–407.
9.Kumar, B. K., Bilgaiyan, S., & Mishra, B. (2023). Software effort estimation through ensembling of base models in machine learning using a voting estimator. International Journal of Advanced Computer Science and Applications, 14, 172–181. https://doi.org/10.14569/IJACSA.2023.0140222
10.Bilgaiyan, S., Ahmad, R., & Sagnika, S. (2023). Adaptive image steganography using rotating color channels and inverted LSB substitution. SN Computer Science, 4(5), 565. https://doi.org/10.1007/s42979-023-01949-0
11.Dutta, H., Bilgaiyan, S., Mishra, B. S. P., Dehuri, S., & Ghosh, A. (2023). Genetically optimized UFLANN for uncovering clusters. IEEE Access. https://doi.org/10.1109/ACCESS.2023.3309557
12.Mahanayak, S. P., Nikhita, B., & Bilgaiyan, S. (2023). Enhancing e-voting security with quantum-resistant encryption: A blockchain-based approach utilizing elliptic curve Diffie–Hellman and decentralized storage. SN Computer Science, 4(5), 642. https://doi.org/10.1007/s42979-023-02041-3
13.Redie, D. K., Bilgaiyan, S., & Sagnika, S. (2023). Oral cancer detection using transfer learning-based framework from histopathology images. Journal of Electronic Imaging, 32(5), 053004. https://doi.org/10.1117/1.JEI.32.5.053004
14.Ruia, K. K., Daga, U., Tripathi, A., Rahman, M. N., & Bilgaiyan, S. (2022). Airline dynamic price prediction using machine learning. International Journal of Productivity and Quality Management, 36(2), 187–207. https://doi.org/10.1504/IJPQM.2020.10037903
15.Dutta, H., Pandey, A., & Bilgaiyan, S. (2021). EnsembleDet: Ensembling against adversarial attack on deepfake detection. Journal of Electronic Imaging, 30(6), 063030.
16.Goswami, D. K., Bilgaiyan, S., & Mishra, S. (2021). Effort estimation of web-based projects: A systematic review. International Journal of Productivity and Quality Management, 32(2), 2678–2682. https://doi.org/10.1504/IJPQM.2021.113619
17.Bilgaiyan, S., Goswami, D. K., Mishra, S., & Das, M. (2019). Effort estimation of back-end part of software using chaotically modified genetic algorithm. International Journal of Intelligent Systems and Applications, 11(1), 32–42. https://doi.org/10.5815/ijisa.2019.01.04
18.Bilgaiyan, S., Aditya, K., Mishra, S., & Das, M. (2018). A swarm intelligence-based chaotic morphological approach for software development cost estimation. International Journal of Intelligent Systems and Applications, 10(9), 13–22. https://doi.org/10.5815/ijisa.2018.09.02
19.Bilgaiyan, S., Mishra, S., & Das, M. (2018). Effort estimation in agile software development using experimental validation of neural network models. International Journal of Information Technology. https://doi.org/10.1007/s41870-018-0131-2
20.Bilgaiyan, S., Sagnika, S., Mishra, S., & Das, M. (2017). A systematic review on software cost estimation in agile software development. Journal of Engineering Science and Technology Review, 10(4), 51–64. https://doi.org/10.25103/jestr.104.08
21.Mishra, D. B., Bilgaiyan, S., Mishra, R., Acharya, A. B., & Mishra, S. (2017). A review of random test case generation using genetic algorithm. Indian Journal of Science and Technology, 10(30), 1–7. https://doi.org/10.17485/ijst/2017/v10i30/107654
22.Bilgaiyan, S., Sagnika, S., Mishra, S., & Das, M. (2015). Study of task scheduling in cloud computing environment using soft computing algorithms. International Journal of Modern Education and Computer Science, 7(3), 32–38. https://doi.org/10.5815/ijmecs.2015.03.05
23.Bilgaiyan, S., Sagnika, S., & Mishra, B. S. P. (2014). An analysis of task scheduling in cloud computing using evolutionary and swarm-based algorithms. International Journal of Computer Applications, 89(2), 11–18. https://doi.org/10.5120/15473-4158
24.Bilgaiyan, S., Sagnika, S., & Sahu, S. (2014). Cloud computing: concept, terminologies, issues, recent technologies. Research Journal of Applied Sciences, 9(9), 614–618. https://doi.org/10.3923/rjasci.2014.614.618
25.Sagnika, S., Bilgaiyan, S., Mishra, S., & Mishra, B. S. P. (2014). An exploration of change detection techniques for images. Journal of Theoretical and Applied Information Technology, 64(3), 820–836.
26.Kumar, N., Bilgaiyan, S., & Sagnika, S. (2013). An overview of transparency in homogeneous distributed database system. International Journal of Advanced Research in Computer Engineering and Technology, 2(10), 2678–2682.
Conference Proceedings
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1.Aryan, A., Bilgaiyan, S., & Bhardwaj, M. (2024). Deep learning applications in plant disease detection: A comparative study. In Proceedings of the 2024 International Conference on Advancements in Smart, Secure and Intelligent Computing (ASSIC) (pp. 1–6). IEEE. https://doi.org/10.1109/ASSIC60049.2024.10507918
2.Bhardwaj, M., Roy, A., & Bilgaiyan, S. (2024). StockGAN: Enhancing stock price prediction with GAN and sentiment analysis. In Proceedings of the 2024 Second International Conference on Networks, Multimedia and Information Technology (NMITCON) (pp. 1–6). IEEE. https://doi.org/10.1109/NMITCON62075.2024.10699240
3.Bilgaiyan, S., Pandey, A., Roy, S., Shukla, S., & Gourisaria, M. K. (2024). PPO-based autoscaling for CPU efficiency in edge computing. In Proceedings of the 2024 Second International Conference on Networks, Multimedia and Information Technology (NMITCON) (pp. 1–6). IEEE. https://doi.org/10.1109/NMITCON62075.2024.10698877
4.Deka, K., Rabha, M., Hazarika, H., Gourisaria, M. K., Bilgaiyan, S., & Patra, S. S. (2024). Harnessing machine learning for improved solar radiation prediction. In Proceedings of the 2024 Second International Conference on Networks, Multimedia and Information Technology (NMITCON) (pp. 1–6). IEEE. https://doi.org/10.1109/NMITCON62075.2024.10699121
5.Kumari, S., Jha, R., Ray, A., Bilgaiyan, S., Gourisaria, M. K., & Sharma, A. (2024). Enhancing image quality with GAN super resolution evaluation. In Proceedings of the 2024 Fifth International Conference on Electronics and Sustainable Communication Systems (ICESC) (pp. 1070–1075). IEEE. https://doi.org/10.1109/ICESC60852.2024.10689831
6.Kumari, S., Pati, N., Gourisaria, M. K., & Bilgaiyan, S. (2024). Application of advanced deep learning models for plant disease detection. In Proceedings of the 2024 International Conference on Integrated Circuits and Communication Systems (ICICACS) (pp. 1–6). IEEE. https://doi.org/10.1109/ICICACS60521.2024.10498791
7.Pati, N., Sharma, A., Gourisaria, M. K., Bilgaiyan, S., Patra, S. S., & Pattnayak, P. (2024). Exploring generative adversarial networks for image synthesis: A comprehensive approach. In Proceedings of the 2024 International Conference on Electrical Electronics and Computing Technologies (ICEECT) (pp. 1–6). IEEE. https://doi.org/10.1109/ICEECT61758.2024.10739274
8.Saikia, D., Barua, R., Gourisaria, M. K., Bandyopadhyay, A., Mishra, S. R., & Bilgaiyan, S. (2024). Machine learning enhancements for car insurance claim prediction. In Proceedings of the 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT) (pp. 1–6). IEEE. https://doi.org/10.1109/ICCCNT61001.2024.10724028
9.Verma, T., Bilgaiyan, S., & Singh, J. P. (2024). Application of machine learning in climate change strategies. In Proceedings of the 2024 Second International Conference on Networks, Multimedia and Information Technology (NMITCON) (pp. 1–6). IEEE. https://doi.org/10.1109/NMITCON62075.2024.10699258
10.Bilgaiyan, S., Ayon, T. I., Khan, A. A., Johora, F. T., Parvin, M., & Alam, M. J. (2023). Heart disease prediction using machine learning. In Proceedings of the 2023 International Conference on Computer Communication and Informatics (ICCCI) (pp. 1–6). IEEE. https://doi.org/10.1109/ICCCI56745.2023.10128378
11.Ghosh, S., Bilgaiyan, S., Gourisaria, M. K., & Sharma, A. (2023). Comparative analysis of applications of machine learning in credit card fraud detection. In Proceedings of the 2023 6th International Conference on Information Systems and Computer Networks (ISCON) (pp. 1–7). IEEE. https://doi.org/10.1109/ISCON57294.2023.10112099
12.Gourisaria, M. K., Arora, A., & Bilgaiyan, S., & Sahni, M. (2023). Chicken disease multiclass classification using deep learning. In Proceedings of the International Conference on Information Technology and Applications: ICITA 2022 (pp. 225–238). Springer. https://doi.org/10.1007/978-981-19-9331-2_19
13.Kabir, M. S., Khanom, J., Bhuiyan, M. A., Tumpa, Z. N., Rabby, S. F., & Bilgaiyan, S. (2023). The early detection of dementia disease using machine learning approach. In Proceedings of the 2023 International Conference on Computer Communication and Informatics (ICCCI) (pp. 1–6). IEEE. https://doi.org/10.1109/ICCCI56745.2023.10128411
14.Mia, M. S., Mim, S. M., Alam, M. J., Razib, M., & Bilgaiyan, S. (2023). An approach to detect melanoma skin cancer using FastAI CNN models. In Proceedings of the 2023 International Conference on Computer Communication and Informatics (ICCCI) (pp. 1–6). IEEE. https://doi.org/10.1109/ICCCI56745.2023.10128274
15.Raipitam, S. K., Kumar, S., Dhanani, T., Bilgaiyan, S., & Gourisaria, M. K. (2023). Comparative study on stock market prediction using generic CNN-LSTM and ensemble learning. In Proceedings of the 2023 International Conference on Network, Multimedia and Information Technology (NMITCON) (pp. 1–6). IEEE. https://doi.org/10.1109/NMITCON58196.2023.10275849
16.Roy, K., Sagnika, S., & Bilgaiyan, S. (2023). Decision assist system for patients using machine learning. In 2023 2nd International Conference for Innovation in Technology (INOCON) (pp. 1–5). IEEE. https://doi.org/10.1109/INOCON57975.2023.10101188
17.Shashank, S., Gourisaria, M. K., & Bilgaiyan, S. (2023). Weather forecasting-based shared bike demand analysis using machine learning. In 2023 6th International Conference on Information Systems and Computer Networks (ISCON) (pp. 1–6). IEEE. https://doi.org/10.1109/ISCON57294.2023.10112160
18.Surjo, G. S., Ghosh, B. K., Alam, M. J., Razib, M., & Bilgaiyan, S. (2023). A comparative analysis between single and dual-handed Bangladeshi sign language detection using CNN-based approach. In 2023 International Conference on Computer Communication and Informatics (ICCCI) (pp. 1–8). IEEE. https://doi.org/10.1109/ICCCI56745.2023.10128583
19.Banerjee, P., Bilgaiyan, S., & Tikmani, A. (2022). Application of blockchain technology in healthcare: An analysis. In 2022 International Conference on Computing, Communication and Power Technology (IC3P) (pp. 254–259). IEEE. https://doi.org/10.1109/IC3P52835.2022.00061
20.Beesetti, K. K., Bilgaiyan, S., & Mishra, B. S. P. (2022). A hybrid feature selection method using multi-objective Jaya algorithm. In 2022 International Conference on Computing, Communication and Power Technology (IC3P) (pp. 232–237). IEEE. https://doi.org/10.1109/IC3P52835.2022.00056
21.Kundu, A., & Bilgaiyan, S. (2022). Automatic enhancement of deep neural networks for diagnosis of COVID-19 cases with X-ray images using MLOps. In 2nd International Conference on Emerging Trends and Technologies on Intelligent Systems (ETTIS) (pp. 155–165). Springer. https://doi.org/10.1007/978-981-19-4182-5_13
22.Mohapatra, S., Bilgaiyan, S., & Mishra, B. (2022). Multi-criteria decision-making methods for large scale database. In 2022 Second International Conference on Computer Science, Engineering and Applications (ICCSEA) (pp. 1–7). IEEE. https://doi.org/10.1109/ICCSEA54677.2022.9936205
23.Pal, S., Mishra, S., Mishra, B. S. P., Sagnika, S., & Bilgaiyan, S. (2022). Quick & lightweight tuberculosis detection: A CNN-based approach. In 2022 International Conference on Advancements in Smart, Secure and Intelligent Computing (ASSIC) (pp. 1–7). IEEE. https://doi.org/10.1109/ASSIC55218.2022.10088388
24.Jha, A., Venkatesh, M., Agarwal, T., & Bilgaiyan, S. (2021). Predicting the risk of patients from coronavirus in India using machine learning. In Advances in Intelligent Systems and Computing (pp. 351–364). Springer. https://doi.org/10.1007/978-981-33-4859-2
25.Kundu, A., Mishra, C., & Bilgaiyan, S. (2021). COVID-SegNet: Diagnosis of COVID-19 cases on radiological images using Mask R-CNN. In IEEE Seventh International Conference on Bio Signals, Images, and Instrumentation (ICBSII) (pp. 1–5). IEEE. https://doi.org/10.1109/ICBSII51839.2021.9445190
26.Mohanty, A., & Bilgaiyan, S. (2021). Drowsiness detection system using KNN and OpenCV. In Advances in Intelligent Systems and Computing (pp. 383–390). Springer. https://doi.org/10.1007/978-981-33-4859-2
27.Singh, A., Kaur, R., Sahu, D., & Bilgaiyan, S. (2021). Real-time emotion detection and song recommendation using CNN architecture. In Advances in Intelligent Systems and Computing (pp. 373–382). Springer. https://doi.org/10.1007/978-981-33-4859-2
28.Aditya, S., Shrivastava, A., & Bilgaiyan, S. (2020). Abstractive text summarization and unsupervised text classifier. In Machine Learning and Information Processing (ICMLIP) (pp. 355–365). Springer. https://doi.org/10.1007/978-981-15-1884-3_33
29.Bilgaiyan, S. (2020). Heart disease prediction using machine learning. In Machine Learning and Information Processing (ICMLIP) (pp. 355–365). Springer. https://doi.org/10.1007/978-981-15-1884-3_33
30.Sinha, S., Mishra, S. K., & Bilgaiyan, S. (2020). Emotion analysis to provide counseling to students fighting depression and anxiety by using CCTV surveillance. In Machine Learning and Information Processing (ICMLIP) (pp. 81–94). Springer. https://doi.org/10.1007/978-981-15-1884-3_8
31.Mishra, S. K., Sinha, S., & Bilgaiyan, S. (2019). Recognition of hand gestures and conversion of voice for the betterment of deaf and mute people. In Third International Conference on Advances in Computing and Data Sciences (ICACDS) (pp. 46–57). Springer. https://doi.org/10.1007/978-981-13-9942-8_5
32.Aditya, K., Chacko, P., Kumari, D., D., K., & Bilgaiyan, S. (2018). Recent trends in HCI: A survey on data glove, Leap Motion, and Microsoft Kinect. In IEEE International Conference on Systems, Computation, Automation and Networking (ICSCAN) (pp. 1–5). IEEE. https://doi.org/10.1109/ICSCAN.2018.8541163
33.Bilgaiyan, S., Aditya, K., Mishra, S., & Das, M. (2018). Chaos-based modified morphological genetic algorithm for software development cost estimation. In Progress in Computing, Analytics and Networking (pp. 31–40). Springer. https://doi.org/10.1007/978-981-10-7871-2_4
34.Sagnika, S., Bilgaiyan, S., & Mishra, B. S. P. (2018). Workflow scheduling in cloud computing environment using bat algorithm. In First International Conference on Smart System, Innovations and Computing (pp. 149–163). Springer. https://doi.org/10.1007/978-981-10-5828-8_15
35.Sarkar, S., Gayen, S., & Bilgaiyan, S. (2018). Android-based home security systems using IoT and Firebase. In IEEE International Conference on Inventive Research in Computing Applications (ICIRCA) (pp. 102–105). IEEE. https://doi.org/10.1109/ICIRCA.2018.8597197
36.Bilgaiyan, S., Mishra, S., & Das, M. (2016). A review of software cost estimation in agile software development using soft computing techniques. In IEEE 2nd International Conference on Computational Intelligence and Networks (CINE) (pp. 112–117). IEEE. https://doi.org/10.1109/CINE.2016.27
37.Rana, M., Bilgaiyan, S., & Kar, U. (2016). A study on load balancing in cloud computing environment using evolutionary and swarm-based algorithms. In IEEE International Conference on Control, Instrumentation, Communication and Computational Technologies (ICCICCT) (pp. 245–250). IEEE. https://doi.org/10.1109/ICCICCT.2014.6992964
38.Bilgaiyan, S., Sagnika, S., & Das, M. (2014). A multi-objective cat swarm optimization algorithm for workflow scheduling in cloud computing environment. In Intelligent Computing, Communication and Devices (pp. 73–84). Springer. https://doi.org/10.1007/978-81-322-2012-1_9
39.Bilgaiyan, S., Sagnika, S., & Das, M. (2014). Workflow scheduling in cloud computing environment using cat swarm optimization. In IEEE International Advance Computing Conference (IACC) (pp. 680–685). IEEE. https://doi.org/10.1109/IAdCC.2014.6779406
40.Sagnika, S., Bilgaiyan, S., & Mishra, B. S. P. (2014). Image change detection using particle swarm optimization. In Intelligent Computing, Communication and Devices (pp. 795–803). Springer. https://doi.org/10.1007/978-81-322-2012-1_86
41.Sahu, S., & Priyadarshini, P. A., Bilgaiyan, S. (2014). Curbing distributed denial of service attack by traffic filtering in wireless sensor network. In IEEE Fifth International Conference on Computing, Communications and Networking Technologies (ICCCNT) (pp. 1–6). IEEE. https://doi.org/10.1109/ICCCNT.2014.6963043
Kumar, N., Sahoo, L., & Bilgaiyan, S. (2013). Enhanced two-phase commit protocol in transaction management. In 7th International Conference on Advance Computing and Communication Technologies (ICACCT 2013). Panipat, India.
Patents
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--->Choudhury, S., Pandey, A., Mishra, R., Sahu, S., & BILGAIYAN, S. (2025). Water dispenser system with temperature recording. Application Number:455224-001. Indian Patent Grant.
--->Mythli, R., Manohar, S., Sridevi, R., Laxmi, M. V., Dawande, N. A., Ganapathy, B. S., Suganthi, M., Patel, M. G., Bilgaiyan, S., Sagnika, S., Ashok, S. and Arun, M. R. (2023). Artificial Intelligence Based Smart Cyber Attack Detection in IoT Wireless Networks. Patent No. 202341003722. Indian Patent Grant.
Books :
Books, Book Chapters, and Patents
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1.Choudhury, S., Pandey, A., Mishra, R., Sahu, S., & Bilgaiyan, S. (n.d.). Water dispenser system with temperature recording [Indian Patent No. 455224-001]. Indian Patent Office.
2.Mythili, R., Manohar, S., Sridevi, R., Laxmi, M. V., Dawande, N. A., Ganapathy, B. S., … Bilgaiyan, S. (n.d.). Artificial intelligence-based smart cyber attack detection in IoT wireless networks [Indian Patent No. 202341003722]. Indian Patent Office.
3.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. https://doi.org/10.1007/978-981-96-5585-4
4.Banerjee, P., Bilgaiyan, S., & Tikmani, A. (2022). 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. https://doi.org/10.4018/978-1-6684-4969-1.ch009
5.Bilgaiyan, S., Singh, J., & Das, H. (Eds.). (2022). Empirical Research for Futuristic E-Commerce Systems: Foundations and Applications (1st ed.). IGI Global.
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. https://doi.org/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. https://doi.org/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. https://doi.org/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 (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 (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, S. Bilgaiyan, 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.
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, & S. Bilgaiyan (Eds.), Automated Software Engineering: A Deep Learning-Based Approach (1st ed., Chap. 2, Vol. 8, pp. 19–37). Springer Nature Switzerland AG.
13.Satapathy, S. C., Jena, A. K., Singh, J., & Bilgaiyan, S. (Eds.). (2020). Automated Software Engineering: A Deep Learning-Based Approach. Springer Nature Switzerland AG.
14.Singh, J., Bilgaiyan, S., Mishra, B. S. P., & Dehuri, S. (Eds.). (2020). A Journey Towards Bio-Inspired Techniques in Software Engineering. Springer Nature Switzerland AG.
Journal Articles
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1.Beesetti, K., Sundari, M. R., & Bilgaiyan, S. (2025). Topical survey and empirical analysis on methods used to approximate effort in the software development process. International Journal of Productivity and Quality Management, 44. https://doi.org/10.1504/IJPQM.2025.10070339
2.Bilgaiyan, S., Aryan, A., Kumar Nayak, N., & Mishra, P. (2025). Enhancing reliability, security, and scalability of serverless computing for cloud backup in power grids during emergency situations. SN Computer Science, 6(4), 390. https://doi.org/10.1007/s42979-025-03941-2
3.Bilgaiyan, S., Swain, A., Das, S., & Medha. (2025). Advanced fuzzy inference integration with MobileNetV2 for ovarian cyst detection. SN Computer Science, 6(6), 727. https://doi.org/10.1007/s42979-025-04200-0
4.Maiga, S., Bilgaiyan, S., & Sagnika, S. (2025). Predicting software effort using BERT-based word embeddings. International Journal of System Assurance Engineering and Management, 6(390), 1728–1742. https://doi.org/10.1007/s13198-025-02746-z
5.Moharram, M. A., Bilgaiyan, S., & Sagnika, S. (2025). Software effort estimation using cascade neural network optimized based on modified particle swarm optimization (MPSO-CNN). International Journal of Productivity and Quality Management, 44(1), 40–70. https://doi.org/10.1504/IJPQM.2025.143963
6.Saleh, B. M., Bilgaiyan, S., & Sagnika, S. (2025). KanuriSenti: A novel dataset for sentiment analysis in the under-resourced Kanuri language. Data in Brief. https://doi.org/10.1016/j.dib.2025.111758
7.Kumar, B. K., Bilgaiyan, S., & Mishra, B. S. P. (2024). Software effort estimation based on ensemble extreme gradient boosting algorithm and modified Jaya optimization algorithm. International Journal of Computational Intelligence and Applications. https://doi.org/10.1142/S1469026823500323
8.Agrawal, S., Debnath, S., Sagnika, S., Bilgaiyan, S., & Gupta, S. (2023). Hyperspectral image compression using modified convolutional autoencoder. International Journal of Computer Information Systems and Industrial Management Applications, 15, 396–407.
9.Kumar, B. K., Bilgaiyan, S., & Mishra, B. (2023). Software effort estimation through ensembling of base models in machine learning using a voting estimator. International Journal of Advanced Computer Science and Applications, 14, 172–181. https://doi.org/10.14569/IJACSA.2023.0140222
10.Bilgaiyan, S., Ahmad, R., & Sagnika, S. (2023). Adaptive image steganography using rotating color channels and inverted LSB substitution. SN Computer Science, 4(5), 565. https://doi.org/10.1007/s42979-023-01949-0
11.Dutta, H., Bilgaiyan, S., Mishra, B. S. P., Dehuri, S., & Ghosh, A. (2023). Genetically optimized UFLANN for uncovering clusters. IEEE Access. https://doi.org/10.1109/ACCESS.2023.3309557
12.Mahanayak, S. P., Nikhita, B., & Bilgaiyan, S. (2023). Enhancing e-voting security with quantum-resistant encryption: A blockchain-based approach utilizing elliptic curve Diffie–Hellman and decentralized storage. SN Computer Science, 4(5), 642. https://doi.org/10.1007/s42979-023-02041-3
13.Redie, D. K., Bilgaiyan, S., & Sagnika, S. (2023). Oral cancer detection using transfer learning-based framework from histopathology images. Journal of Electronic Imaging, 32(5), 053004. https://doi.org/10.1117/1.JEI.32.5.053004
14.Ruia, K. K., Daga, U., Tripathi, A., Rahman, M. N., & Bilgaiyan, S. (2022). Airline dynamic price prediction using machine learning. International Journal of Productivity and Quality Management, 36(2), 187–207. https://doi.org/10.1504/IJPQM.2020.10037903
15.Dutta, H., Pandey, A., & Bilgaiyan, S. (2021). EnsembleDet: Ensembling against adversarial attack on deepfake detection. Journal of Electronic Imaging, 30(6), 063030.
16.Goswami, D. K., Bilgaiyan, S., & Mishra, S. (2021). Effort estimation of web-based projects: A systematic review. International Journal of Productivity and Quality Management, 32(2), 2678–2682. https://doi.org/10.1504/IJPQM.2021.113619
17.Bilgaiyan, S., Goswami, D. K., Mishra, S., & Das, M. (2019). Effort estimation of back-end part of software using chaotically modified genetic algorithm. International Journal of Intelligent Systems and Applications, 11(1), 32–42. https://doi.org/10.5815/ijisa.2019.01.04
18.Bilgaiyan, S., Aditya, K., Mishra, S., & Das, M. (2018). A swarm intelligence-based chaotic morphological approach for software development cost estimation. International Journal of Intelligent Systems and Applications, 10(9), 13–22. https://doi.org/10.5815/ijisa.2018.09.02
19.Bilgaiyan, S., Mishra, S., & Das, M. (2018). Effort estimation in agile software development using experimental validation of neural network models. International Journal of Information Technology. https://doi.org/10.1007/s41870-018-0131-2
20.Bilgaiyan, S., Sagnika, S., Mishra, S., & Das, M. (2017). A systematic review on software cost estimation in agile software development. Journal of Engineering Science and Technology Review, 10(4), 51–64. https://doi.org/10.25103/jestr.104.08
21.Mishra, D. B., Bilgaiyan, S., Mishra, R., Acharya, A. B., & Mishra, S. (2017). A review of random test case generation using genetic algorithm. Indian Journal of Science and Technology, 10(30), 1–7. https://doi.org/10.17485/ijst/2017/v10i30/107654
22.Bilgaiyan, S., Sagnika, S., Mishra, S., & Das, M. (2015). Study of task scheduling in cloud computing environment using soft computing algorithms. International Journal of Modern Education and Computer Science, 7(3), 32–38. https://doi.org/10.5815/ijmecs.2015.03.05
23.Bilgaiyan, S., Sagnika, S., & Mishra, B. S. P. (2014). An analysis of task scheduling in cloud computing using evolutionary and swarm-based algorithms. International Journal of Computer Applications, 89(2), 11–18. https://doi.org/10.5120/15473-4158
24.Bilgaiyan, S., Sagnika, S., & Sahu, S. (2014). Cloud computing: concept, terminologies, issues, recent technologies. Research Journal of Applied Sciences, 9(9), 614–618. https://doi.org/10.3923/rjasci.2014.614.618
25.Sagnika, S., Bilgaiyan, S., Mishra, S., & Mishra, B. S. P. (2014). An exploration of change detection techniques for images. Journal of Theoretical and Applied Information Technology, 64(3), 820–836.
26.Kumar, N., Bilgaiyan, S., & Sagnika, S. (2013). An overview of transparency in homogeneous distributed database system. International Journal of Advanced Research in Computer Engineering and Technology, 2(10), 2678–2682.
Conference Proceedings
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1.Aryan, A., Bilgaiyan, S., & Bhardwaj, M. (2024). Deep learning applications in plant disease detection: A comparative study. In Proceedings of the 2024 International Conference on Advancements in Smart, Secure and Intelligent Computing (ASSIC) (pp. 1–6). IEEE. https://doi.org/10.1109/ASSIC60049.2024.10507918
2.Bhardwaj, M., Roy, A., & Bilgaiyan, S. (2024). StockGAN: Enhancing stock price prediction with GAN and sentiment analysis. In Proceedings of the 2024 Second International Conference on Networks, Multimedia and Information Technology (NMITCON) (pp. 1–6). IEEE. https://doi.org/10.1109/NMITCON62075.2024.10699240
3.Bilgaiyan, S., Pandey, A., Roy, S., Shukla, S., & Gourisaria, M. K. (2024). PPO-based autoscaling for CPU efficiency in edge computing. In Proceedings of the 2024 Second International Conference on Networks, Multimedia and Information Technology (NMITCON) (pp. 1–6). IEEE. https://doi.org/10.1109/NMITCON62075.2024.10698877
4.Deka, K., Rabha, M., Hazarika, H., Gourisaria, M. K., Bilgaiyan, S., & Patra, S. S. (2024). Harnessing machine learning for improved solar radiation prediction. In Proceedings of the 2024 Second International Conference on Networks, Multimedia and Information Technology (NMITCON) (pp. 1–6). IEEE. https://doi.org/10.1109/NMITCON62075.2024.10699121
5.Kumari, S., Jha, R., Ray, A., Bilgaiyan, S., Gourisaria, M. K., & Sharma, A. (2024). Enhancing image quality with GAN super resolution evaluation. In Proceedings of the 2024 Fifth International Conference on Electronics and Sustainable Communication Systems (ICESC) (pp. 1070–1075). IEEE. https://doi.org/10.1109/ICESC60852.2024.10689831
6.Kumari, S., Pati, N., Gourisaria, M. K., & Bilgaiyan, S. (2024). Application of advanced deep learning models for plant disease detection. In Proceedings of the 2024 International Conference on Integrated Circuits and Communication Systems (ICICACS) (pp. 1–6). IEEE. https://doi.org/10.1109/ICICACS60521.2024.10498791
7.Pati, N., Sharma, A., Gourisaria, M. K., Bilgaiyan, S., Patra, S. S., & Pattnayak, P. (2024). Exploring generative adversarial networks for image synthesis: A comprehensive approach. In Proceedings of the 2024 International Conference on Electrical Electronics and Computing Technologies (ICEECT) (pp. 1–6). IEEE. https://doi.org/10.1109/ICEECT61758.2024.10739274
8.Saikia, D., Barua, R., Gourisaria, M. K., Bandyopadhyay, A., Mishra, S. R., & Bilgaiyan, S. (2024). Machine learning enhancements for car insurance claim prediction. In Proceedings of the 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT) (pp. 1–6). IEEE. https://doi.org/10.1109/ICCCNT61001.2024.10724028
9.Verma, T., Bilgaiyan, S., & Singh, J. P. (2024). Application of machine learning in climate change strategies. In Proceedings of the 2024 Second International Conference on Networks, Multimedia and Information Technology (NMITCON) (pp. 1–6). IEEE. https://doi.org/10.1109/NMITCON62075.2024.10699258
10.Bilgaiyan, S., Ayon, T. I., Khan, A. A., Johora, F. T., Parvin, M., & Alam, M. J. (2023). Heart disease prediction using machine learning. In Proceedings of the 2023 International Conference on Computer Communication and Informatics (ICCCI) (pp. 1–6). IEEE. https://doi.org/10.1109/ICCCI56745.2023.10128378
11.Ghosh, S., Bilgaiyan, S., Gourisaria, M. K., & Sharma, A. (2023). Comparative analysis of applications of machine learning in credit card fraud detection. In Proceedings of the 2023 6th International Conference on Information Systems and Computer Networks (ISCON) (pp. 1–7). IEEE. https://doi.org/10.1109/ISCON57294.2023.10112099
12.Gourisaria, M. K., Arora, A., & Bilgaiyan, S., & Sahni, M. (2023). Chicken disease multiclass classification using deep learning. In Proceedings of the International Conference on Information Technology and Applications: ICITA 2022 (pp. 225–238). Springer. https://doi.org/10.1007/978-981-19-9331-2_19
13.Kabir, M. S., Khanom, J., Bhuiyan, M. A., Tumpa, Z. N., Rabby, S. F., & Bilgaiyan, S. (2023). The early detection of dementia disease using machine learning approach. In Proceedings of the 2023 International Conference on Computer Communication and Informatics (ICCCI) (pp. 1–6). IEEE. https://doi.org/10.1109/ICCCI56745.2023.10128411
14.Mia, M. S., Mim, S. M., Alam, M. J., Razib, M., & Bilgaiyan, S. (2023). An approach to detect melanoma skin cancer using FastAI CNN models. In Proceedings of the 2023 International Conference on Computer Communication and Informatics (ICCCI) (pp. 1–6). IEEE. https://doi.org/10.1109/ICCCI56745.2023.10128274
15.Raipitam, S. K., Kumar, S., Dhanani, T., Bilgaiyan, S., & Gourisaria, M. K. (2023). Comparative study on stock market prediction using generic CNN-LSTM and ensemble learning. In Proceedings of the 2023 International Conference on Network, Multimedia and Information Technology (NMITCON) (pp. 1–6). IEEE. https://doi.org/10.1109/NMITCON58196.2023.10275849
16.Roy, K., Sagnika, S., & Bilgaiyan, S. (2023). Decision assist system for patients using machine learning. In 2023 2nd International Conference for Innovation in Technology (INOCON) (pp. 1–5). IEEE. https://doi.org/10.1109/INOCON57975.2023.10101188
17.Shashank, S., Gourisaria, M. K., & Bilgaiyan, S. (2023). Weather forecasting-based shared bike demand analysis using machine learning. In 2023 6th International Conference on Information Systems and Computer Networks (ISCON) (pp. 1–6). IEEE. https://doi.org/10.1109/ISCON57294.2023.10112160
18.Surjo, G. S., Ghosh, B. K., Alam, M. J., Razib, M., & Bilgaiyan, S. (2023). A comparative analysis between single and dual-handed Bangladeshi sign language detection using CNN-based approach. In 2023 International Conference on Computer Communication and Informatics (ICCCI) (pp. 1–8). IEEE. https://doi.org/10.1109/ICCCI56745.2023.10128583
19.Banerjee, P., Bilgaiyan, S., & Tikmani, A. (2022). Application of blockchain technology in healthcare: An analysis. In 2022 International Conference on Computing, Communication and Power Technology (IC3P) (pp. 254–259). IEEE. https://doi.org/10.1109/IC3P52835.2022.00061
20.Beesetti, K. K., Bilgaiyan, S., & Mishra, B. S. P. (2022). A hybrid feature selection method using multi-objective Jaya algorithm. In 2022 International Conference on Computing, Communication and Power Technology (IC3P) (pp. 232–237). IEEE. https://doi.org/10.1109/IC3P52835.2022.00056
21.Kundu, A., & Bilgaiyan, S. (2022). Automatic enhancement of deep neural networks for diagnosis of COVID-19 cases with X-ray images using MLOps. In 2nd International Conference on Emerging Trends and Technologies on Intelligent Systems (ETTIS) (pp. 155–165). Springer. https://doi.org/10.1007/978-981-19-4182-5_13
22.Mohapatra, S., Bilgaiyan, S., & Mishra, B. (2022). Multi-criteria decision-making methods for large scale database. In 2022 Second International Conference on Computer Science, Engineering and Applications (ICCSEA) (pp. 1–7). IEEE. https://doi.org/10.1109/ICCSEA54677.2022.9936205
23.Pal, S., Mishra, S., Mishra, B. S. P., Sagnika, S., & Bilgaiyan, S. (2022). Quick & lightweight tuberculosis detection: A CNN-based approach. In 2022 International Conference on Advancements in Smart, Secure and Intelligent Computing (ASSIC) (pp. 1–7). IEEE. https://doi.org/10.1109/ASSIC55218.2022.10088388
24.Jha, A., Venkatesh, M., Agarwal, T., & Bilgaiyan, S. (2021). Predicting the risk of patients from coronavirus in India using machine learning. In Advances in Intelligent Systems and Computing (pp. 351–364). Springer. https://doi.org/10.1007/978-981-33-4859-2
25.Kundu, A., Mishra, C., & Bilgaiyan, S. (2021). COVID-SegNet: Diagnosis of COVID-19 cases on radiological images using Mask R-CNN. In IEEE Seventh International Conference on Bio Signals, Images, and Instrumentation (ICBSII) (pp. 1–5). IEEE. https://doi.org/10.1109/ICBSII51839.2021.9445190
26.Mohanty, A., & Bilgaiyan, S. (2021). Drowsiness detection system using KNN and OpenCV. In Advances in Intelligent Systems and Computing (pp. 383–390). Springer. https://doi.org/10.1007/978-981-33-4859-2
27.Singh, A., Kaur, R., Sahu, D., & Bilgaiyan, S. (2021). Real-time emotion detection and song recommendation using CNN architecture. In Advances in Intelligent Systems and Computing (pp. 373–382). Springer. https://doi.org/10.1007/978-981-33-4859-2
28.Aditya, S., Shrivastava, A., & Bilgaiyan, S. (2020). Abstractive text summarization and unsupervised text classifier. In Machine Learning and Information Processing (ICMLIP) (pp. 355–365). Springer. https://doi.org/10.1007/978-981-15-1884-3_33
29.Bilgaiyan, S. (2020). Heart disease prediction using machine learning. In Machine Learning and Information Processing (ICMLIP) (pp. 355–365). Springer. https://doi.org/10.1007/978-981-15-1884-3_33
30.Sinha, S., Mishra, S. K., & Bilgaiyan, S. (2020). Emotion analysis to provide counseling to students fighting depression and anxiety by using CCTV surveillance. In Machine Learning and Information Processing (ICMLIP) (pp. 81–94). Springer. https://doi.org/10.1007/978-981-15-1884-3_8
31.Mishra, S. K., Sinha, S., & Bilgaiyan, S. (2019). Recognition of hand gestures and conversion of voice for the betterment of deaf and mute people. In Third International Conference on Advances in Computing and Data Sciences (ICACDS) (pp. 46–57). Springer. https://doi.org/10.1007/978-981-13-9942-8_5
32.Aditya, K., Chacko, P., Kumari, D., D., K., & Bilgaiyan, S. (2018). Recent trends in HCI: A survey on data glove, Leap Motion, and Microsoft Kinect. In IEEE International Conference on Systems, Computation, Automation and Networking (ICSCAN) (pp. 1–5). IEEE. https://doi.org/10.1109/ICSCAN.2018.8541163
33.Bilgaiyan, S., Aditya, K., Mishra, S., & Das, M. (2018). Chaos-based modified morphological genetic algorithm for software development cost estimation. In Progress in Computing, Analytics and Networking (pp. 31–40). Springer. https://doi.org/10.1007/978-981-10-7871-2_4
34.Sagnika, S., Bilgaiyan, S., & Mishra, B. S. P. (2018). Workflow scheduling in cloud computing environment using bat algorithm. In First International Conference on Smart System, Innovations and Computing (pp. 149–163). Springer. https://doi.org/10.1007/978-981-10-5828-8_15
35.Sarkar, S., Gayen, S., & Bilgaiyan, S. (2018). Android-based home security systems using IoT and Firebase. In IEEE International Conference on Inventive Research in Computing Applications (ICIRCA) (pp. 102–105). IEEE. https://doi.org/10.1109/ICIRCA.2018.8597197
36.Bilgaiyan, S., Mishra, S., & Das, M. (2016). A review of software cost estimation in agile software development using soft computing techniques. In IEEE 2nd International Conference on Computational Intelligence and Networks (CINE) (pp. 112–117). IEEE. https://doi.org/10.1109/CINE.2016.27
37.Rana, M., Bilgaiyan, S., & Kar, U. (2016). A study on load balancing in cloud computing environment using evolutionary and swarm-based algorithms. In IEEE International Conference on Control, Instrumentation, Communication and Computational Technologies (ICCICCT) (pp. 245–250). IEEE. https://doi.org/10.1109/ICCICCT.2014.6992964
38.Bilgaiyan, S., Sagnika, S., & Das, M. (2014). A multi-objective cat swarm optimization algorithm for workflow scheduling in cloud computing environment. In Intelligent Computing, Communication and Devices (pp. 73–84). Springer. https://doi.org/10.1007/978-81-322-2012-1_9
39.Bilgaiyan, S., Sagnika, S., & Das, M. (2014). Workflow scheduling in cloud computing environment using cat swarm optimization. In IEEE International Advance Computing Conference (IACC) (pp. 680–685). IEEE. https://doi.org/10.1109/IAdCC.2014.6779406
40.Sagnika, S., Bilgaiyan, S., & Mishra, B. S. P. (2014). Image change detection using particle swarm optimization. In Intelligent Computing, Communication and Devices (pp. 795–803). Springer. https://doi.org/10.1007/978-81-322-2012-1_86
41.Sahu, S., & Priyadarshini, P. A., Bilgaiyan, S. (2014). Curbing distributed denial of service attack by traffic filtering in wireless sensor network. In IEEE Fifth International Conference on Computing, Communications and Networking Technologies (ICCCNT) (pp. 1–6). IEEE. https://doi.org/10.1109/ICCCNT.2014.6963043
Kumar, N., Sahoo, L., & Bilgaiyan, S. (2013). Enhanced two-phase commit protocol in transaction management. In 7th International Conference on Advance Computing and Communication Technologies (ICACCT 2013). Panipat, India.
Patents
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--->Choudhury, S., Pandey, A., Mishra, R., Sahu, S., & BILGAIYAN, S. (2025). Water dispenser system with temperature recording. Application Number:455224-001. Indian Patent Grant.
--->Mythli, R., Manohar, S., Sridevi, R., Laxmi, M. V., Dawande, N. A., Ganapathy, B. S., Suganthi, M., Patel, M. G., Bilgaiyan, S., Sagnika, S., Ashok, S. and Arun, M. R. (2023). Artificial Intelligence Based Smart Cyber Attack Detection in IoT Wireless Networks. Patent No. 202341003722. Indian Patent Grant.
Books :
Books, Book Chapters, and Patents
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1.Choudhury, S., Pandey, A., Mishra, R., Sahu, S., & Bilgaiyan, S. (n.d.). Water dispenser system with temperature recording [Indian Patent No. 455224-001]. Indian Patent Office.
2.Mythili, R., Manohar, S., Sridevi, R., Laxmi, M. V., Dawande, N. A., Ganapathy, B. S., … Bilgaiyan, S. (n.d.). Artificial intelligence-based smart cyber attack detection in IoT wireless networks [Indian Patent No. 202341003722]. Indian Patent Office.
3.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. https://doi.org/10.1007/978-981-96-5585-4
4.Banerjee, P., Bilgaiyan, S., & Tikmani, A. (2022). 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. https://doi.org/10.4018/978-1-6684-4969-1.ch009
5.Bilgaiyan, S., Singh, J., & Das, H. (Eds.). (2022). Empirical Research for Futuristic E-Commerce Systems: Foundations and Applications (1st ed.). IGI Global.
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. https://doi.org/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. https://doi.org/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. https://doi.org/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 (pp. 155–176). Elsevier. https://www.elsevier.com/books/machine-learning-for-biometrics/sarangi/978-0-323-85209-8
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