B. Tech, M. Tech (NIT RKL)

Ph.D. (NIT RKL)

Computer Science

PMEC – Since 22.10.2014

Programming & Problem Solving using C, Data Structure, Artificial Intelligence & Machine Learning, Parallel Algorithm, Expert System

PhD scholars(Continuing)
1. Mrs. Sasmita Rani Behera, Research Title: Computation Offloading in Mobile Edge Computing
2. Mrs. Ranumayee Sing, Research Title: Task Scheduling in Fog Computing
3. Mrs. Priyadarshini Voosala, Research Title: Task Assignment Strategies in Cloudlets

1. OIC for Computer Center-I and Computer Center-II from 2014-2016
2. Institute AICTE Coordinator from 2017-2019
3. Central NBA Coordinator for NBA visit during 2019
4. OIC for Center of Excellence: High-Performance Computing from 2018

ISTE, IAENG, UACEE

[1] N. Panigrahi and S. Jha, “A comparative study of explainable artificial intelligence algorithms in local interpretable model-agnostic based pneumonia prediction,” Computing, Communication and Intelligence, pp. 9–13, 2026.

[2] S. K. Jha and N. Panigrahi, “Explainable AI integrated deep learning approach for glaucoma prediction,” in Proc. Int. Conf. Machine Learning, IoT and Big Data, pp. 140–150, 2025.

[3] N. Panigrahi, “An expert system-assisted AI approach for awareness and prevention of crimes against women in India,” in Advancements in Artificial Intelligence and Machine Learning, 2025. doi: https://doi.org/…

[4] N. Panigrahi et al., “ORS: A novel olive ridley survival inspired meta-heuristic optimization algorithm,” arXiv preprint arXiv:2409.09210, 2024.

[5] N. Panigrahi, S. Kumar, and P. Parida, Aspect-based sentiment analysis for Odisha’s Eco-retreat Center: A case study on Konark, LAP LAMBERT Academic Publishing, 2024, ISBN: 978-620-7-48423-2.

[6] P. Arya et al., “MSCMGTB: A novel approach for multimodal social media content moderation using hybrid graph theory and bio-inspired optimization,” IEEE Access, vol. 12, pp. 73700–73718, 2024.

[7] P. Misra et al., “PETLFC: Parallel ensemble transfer learning based framework for COVID-19 differentiation and prediction using deep convolutional neural network models,” Multimedia Tools and Applications, vol. 83, no. 5, pp. 14211–14233, 2024.

[8] V. Raut et al., “An NLP based differentiated case flow management system,” in Proc. 13th Project Innovation Contest (PIC), KIIT DU, pp. 136–142, 2024.

[9] R. Sing, S. K. Bhoi, and N. Panigrahi, “A fault-tolerant load balancing approach using whale optimization algorithm for cloud-fog based IoT applications,” in Proc. OITS Int. Conf. Information Technology (OCIT), pp. 231–236, 2023.

[10] S. R. Behera, N. Panigrahi, and S. K. Bhoi, “A novel dynamic D2D-assisted offloading decision making in multi-user edge computing environment,” in Proc. OITS Int. Conf. Information Technology (OCIT), pp. 144–149, 2023.

[11] R. Sing, S. K. Bhoi, and N. Panigrahi, “A load balancing algorithm for cloud-fog-based IoT networks using bald eagle search optimization,” in Proc. 1st Int. Conf. Circuits, Power and Intelligent Systems, 2023.

[12] N. Panigrahi et al., “Groundwater quality analysis and drinkability prediction using artificial intelligence,” Earth Science Informatics, vol. 16, no. 2, pp. 1701–1725, 2023.

[13] S. R. Behera et al., “A distributed fuzzy optimal decision-making strategy for task offloading in edge computing environment,” IEEE Access, vol. 11, pp. 33189–33204, 2023.

[14] S. R. Behera et al., “Time series-based edge resource prediction and parallel optimal task allocation in mobile edge computing environment,” Processes, vol. 11, no. 4, p. 1017, 2023.

[15] S. K. Jha, A. Gupta, and N. Panigrahi, “Resilient consensus-based time synchronization with distributed Sybil attack detection strategy for wireless sensor networks: A graph theoretic approach,” International Journal of Computer Networks and Applications, vol. 10, no. 1, pp. 39–50, 2023.

[16] N. Panigrahi, “Artificial intelligence based Indian sign language recognition with accelerated performance under HPC environment,” in Proc. OITS Int. Conf. Information Technology (OCIT), pp. 228–232, 2022.

[17] R. Sing, S. K. Bhoi, N. Panigrahi, K. S. Sahoo, M. Bilal, and S. C. Shah, “EMCS: An energy-efficient makespan cost-aware scheduling algorithm using evolutionary learning approach for cloud-fog-based IoT applications,” Sustainability, vol. 14, no. 22, p. 15096, 2022.

[18] R. Sing, S. K. Bhoi, N. Panigrahi, K. S. Sahoo, N. Jhanjhi, and M. A. AlZain, “A whale optimization algorithm based resource allocation scheme for cloud-fog based IoT applications,” Electronics, vol. 11, no. 19, p. 3207, 2022.

[19] S. Kumar Sahu and N. Panigrahi, “CosSinO: A trigonometric rule-based deterministic gaming algorithm in a multi-player environment,” 2022.

[20] R. Sing, S. K. Bhoi, N. Panigrahi, K. S. Sahoo, N. Jhanjhi, and M. A. AlZain, “A whale optimization algorithm based resource allocation scheme for cloud-fog based IoT applications,” Electronics, vol. 11, no. 19, p. 3207, 2022.

[21] S. K. Jha, A. Gupta, and N. Panigrahi, “Performance analysis of consensus-based time synchronization algorithms for wireless sensor network,” in Lecture Notes in Electrical Engineering (LNEE), vol. 825, pp. 359–368, 2022.

[22] I. Ayus and N. Panigrahi, “A decision support system using rule-based expert system for COVID-19 prediction and diagnosis,” in Applications of Artificial Intelligence in COVID-19, pp. 119–140, 2021.

[23] S. K. Jha, A. Gupta, and N. Panigrahi, “Security threat analysis and countermeasures on consensus-based time synchronization algorithms for wireless sensor network,” SN Computer Science, vol. 2, no. 5, p. 409, 2021.

[24] P. Misra and N. Panigrahi, “Prediction and detection of COVID-19 from chest X-rays using transfer learning based deep convolutional neural networks,” 2021.

[25] A. Sahani et al., “A novel rule-based expert system for penalty prediction for two-wheeler’s traffic rules violation in India,” in Intelligent Computing and Communication Systems, pp. 67–75, 2021.

[26] N. Panigrahi, I. Ayus, and O. P. Jena, “An expert system-based clinical decision support system for Hepatitis-B prediction & diagnosis,” in Machine Learning for Healthcare Applications, pp. 57–75, 2021.

[27] S. K. Sahoo et al., “Temporal modeling of on-street parking data for detection of parking violation in smart cities,” in Evolution in Computational Intelligence: Frontiers in Intelligent Computing, 2020.

[28] S. R. Behera et al., “A novel decision making strategy for computation offloading in mobile edge computing,” in Proc. Int. Conf. Computer Science, Engineering and Applications, 2020.

[29] S. K. Jha, N. Panigrahi, and A. Gupta, “Security threats for time synchronization protocols in the internet of things,” in Principles of Internet of Things (IoT) Ecosystem: Insight Paradigm, pp. 495–517, 2019.

[30] M. Behera, P. K. Bhardwaj, and N. Panigrahi, “Performance analysis of machine learning algorithms for missing value imputation on medical dataset,” International Journal of Management, Technology and Engineering, vol. 8, no. X, pp. 2640–2649, 2018.

[31] N. Panigrahi and P. M. Khilar, “Multi-hop consensus time synchronization algorithm for sparse wireless sensor network: A distributed constraint-based dynamic programming approach,” Ad Hoc Networks, vol. 61, pp. 124–138, 2017.

[32] N. Panigrahi and P. M. Khilar, “Energy consumption analysis of consensus time synchronization algorithms for wireless sensor networks,” Journal of Wireless Communications, vol. 2, no. 2, 2017.

[33] N. Panigrahi, “Consensus-based time synchronization algorithms for wireless sensor networks with topological optimization strategies for performance improvement,” 2016.

[34] N. Panigrahi and P. M. Khilar, “Optimal consensus-based clock synchronization algorithm in wireless sensor network by selective averaging,” IET Wireless Sensor Systems, vol. 5, no. 3, pp. 166–174, 2015.

[35] N. Panigrahi and P. M. Khilar, “An evolutionary based topological optimization strategy for consensus based clock synchronization protocols in wireless sensor network,” Swarm and Evolutionary Computation, 2015. doi:10.1016/j.swevo.2015.02.001.

[36] N. Panigrahi and P. M. Khilar, “Optimal topological balancing strategy for performance optimisation of consensus-based clock synchronisation protocols in wireless sensor networks: A genetic algorithm-based approach,” IET Wireless Sensor Systems, vol. 4, no. 4, pp. 213–222, 2014. https://doi.org/10.1049/iet-wss.2014.0063.

[37] N. Panigrahi and B. Sahoo, “QoS based retrieval strategy for video on demand,” in Proc. ISM, 2009.

[38] N. Panigrahi and S. Jha, “A comparative study of explainable artificial intelligence algorithms in local interpretable model-agnostic based pneumonia prediction,” in Computing, Communication and Intelligence, 2026.

[1] Odisha Skill Development Authority (OSDA), “SAP Training of Trainers (ToT),” Odisha, India, 1–22 Jul. 2020.

[2] IEEE Bhubaneswar Subsection, “Ground-water quality analysis using ML approach: A case study on Odisha,” State-level paper presentation, IEEE Day Celebration, Odisha, India, Oct. 5, 2021.

[1] C-DAC, Pune, “Online Short-Term Training Programme (STTP): Machine Learning and Deep Learning using PARAM SHAVAK DL-GPU System,” Coordinator, India, Jan. 11–15, 2021.

[2] Department of CSE, Parala Maharaja Engineering College (PMEC), “One-day Seminar: Graph Theoretic Approach to Topology Control of Wireless Sensor Network,” Coordinator, Odisha, India, May 2, 2022.

[3] Department of CSE, PMEC, “Online Industrial Training: RPA using UiPath,” Coordinator, Odisha, India, Aug. 1–7, 2022.

Dept. of Computer Science Engineering

PMEC Berhampur 761003, Odisha, India