Specialization

Fog/Edge Computing, Blockchain

Email

vibha.jain@thapar.edu

Education
1.    PhD in Computer Science and Engineering from Netaji Subhas University of Technology, New Delhi
2.    M.Tech in Computer Science and Engineering from National Institute of Technology Hamirpur, Himachal Pradesh (Gold Medalist)
3.    B. Tech. in Computer Science and Engineering from Dr. A. P. J. Abdul Kalam Technical University, Uttar Pradesh.

Experience
1.    Assistant Professor, Computer Science and Engineering Department, Thapar University Patiala, India (July 2024 - present)

Journal publications
•    V. Jain and B. Kumar, ‘Combinatorial auction based multi-task resource allocation in fog environment using blockchain and smart contracts’, Peer-to-Peer Networking and Applications, vol. 14, no. 5, pp. 3124–3142, 2021. (SCIE indexed, IF: 4.4)
•    A. Gupta, V. Jain, and A. Singh, ‘Stacking ensemble-based intelligent machine learning model for predicting post-COVID-19 complications’, New Generation Computing, vol. 40, no. 4, pp. 987–1007, 2022. (SCIE indexed, IF: 2.6)
•    V. Jain and B. Kumar, ‘Auction based cost-efficient resource allocation by utilizing blockchain in fog computing’, Transactions on Emerging Telecommunications Technologies, p. e4469, 2022. (SCIE indexed, IF: 3.6)
•    V. Jain, B. Kumar, and A. Gupta, ‘Cybertwin-driven resource allocation using deep reinforcement learning in 6G-enabled edge environment’, Journal of King Saud University-Computer and Information Sciences, vol. 34, no. 8, pp. 5708–5720, 2022. (SCIE indexed, IF: 6.9)
•    P. Rani, P. Kaur, V. Jain, J. Shokeen, and S. Nain, ‘Blockchain-based IoT enabled health monitoring system’, The Journal of Supercomputing, vol. 78, no. 15, pp. 17284–17308, 2022. (SCIE indexed, IF: 3.6)
•    V. Jain and B. Kumar, ‘Blockchain enabled trusted task offloading scheme for fog computing: A deep reinforcement learning approach’, Transactions on Emerging Telecommunications Technologies, p. e4587, 2022. (SCIE indexed, IF: 4.4)
•    A. Gupta, I. S. Rajput, V. Jain, and S. Chaurasia, ‘NSGA-II-XGB: Meta-heuristic feature selection with XGBoost framework for diabetes prediction’, Concurrency and Computation: Practice and Experience, p. e7123, 2022. (SCIE indexed, IF: 2)
•    V. Jain and B. Kumar, ‘Qos-aware task offloading in fog environment using multi-agent deep reinforcement learning’, Journal of Network and Systems Management, vol. 31, no. 1, p. 7, 2023. (SCIE indexed, IF: 3.6) 
•    V. Jain and B. Kumar, ‘A trusted resource allocation scheme in fog environment to satisfy high network demand’, Arabian Journal for Science and Engineering, vol. 48, no. 8, pp. 9769–9786, 2023. (SCIE indexed, IF: 2.9)
•    A. Gupta, M. Bhagat, and V. Jain, ‘Blockchain-enabled healthcare monitoring system for early Monkeypox detection’, The Journal of Supercomputing, vol. 79, no. 14, pp. 15675–15699, 2023. (SCIE indexed, IF: 3.6)
•    I. S. Rajput, A. Gupta, V. Jain, and S. Tyagi, ‘A transfer learning-based brain tumor classification using magnetic resonance images’, Multimedia Tools and Applications, vol. 83, no. 7, pp. 20487–20506, 2024. (SCIE indexed, IF: 3.6)
•    I. S. Rajput, S. Tyagi, A. Gupta, and V. Jain, ‘Sine cosine algorithm-based feature selection for improved machine learning models in polycystic ovary syndrome diagnosis’, Multimedia Tools and Applications, pp. 1–25, 2024. (SCIE indexed, IF: 3.6)
•    R. Kumar, V. Jain, N. Chauhan, and N. Chand, ‘An adaptive prediction strategy with clustering in wireless sensor network’, International Journal of Wireless Information Networks, vol. 27, pp. 575–587, 2020. (Scopus indexed)
•    P. Rani, V. Jain, J. Shokeen, and A. Balyan, ‘Blockchain-based rumor detection approach for COVID-19’, Journal of Ambient Intelligence and Humanized Computing, vol. 15, no. 1, pp. 435–449, 2024. (Scopus indexed)
•    V. Jain and B. Kumar, ‘Quality of Service-Based Resource Management in Fog Computing: A Systematic Review’, International Journal of Cloud Applications and Computing (IJCAC), vol. 12, no. 1, pp. 1–27, 2022. (Scopus indexed)
•    I. S. Rajput, S. Tyagi, A. Gupta, and V. Jain, ‘Advances in Medical Imaging: Using Convolutional Neural Networks for White Blood Cell Identification’, 2024. (Scopus indexed)

Conference publications
•    P. Rani, P. P. Singh, A. Balyan, J. Shokeen, V. Jain, and D. Sangwan, ‘A secure epidemic routing using blockchain in opportunistic internet of things’, in Data Analytics and Management: Proceedings of ICDAM, 2021, pp. 101–110.
•    P. Rani, V. Jain, M. Joshi, M. Khandelwal, and S. Rao, ‘A secured supply chain network for route optimization and product traceability using blockchain in internet of things’, in Data Analytics and Management: Proceedings of ICDAM, 2021, pp. 637–647.
•    P. Rani, A. Balyan, V. Jain, D. Sangwan, P. P. Singh, and J. Shokeen, ‘A probabilistic routing-based secure approach for opportunistic IoT network using blockchain’, in 2020 IEEE 17th India Council International Conference (INDICON), 2020, pp. 1–7.
•    V. Jain and B. Kumar, ‘Optimal task offloading and resource allotment towards fog-cloud architecture’, in 2021 11th International Conference on Cloud Computing, Data Science & Engineering (Confluence), 2021, pp. 233–238.
•    B. Kumar and V. Jain, ‘A Comparative Study on Simulation Environment on Fog Computing’, in 2021 IEEE International Conference on Emerging Trends in Industry 4.0 (ETI 4.0), 2021.
•    P. Rani, P. Sharma, and V. Jain, ‘Smart Home Automation: Literature Review’, Available at SSRN 3884647, 2021.
•    A. Gupta, V. Jain, and W. Hussain, ‘A Fog--Cloud Computing-Inspired Image Processing-Based Framework for Lung Cancer Diagnosis Using Deep Learning’, Intelligent Systems: Proceedings of SCIS 2021, p. 19, 2021.
•    P. Rani, V. Jain, M. Saif, S. H. Mugloo, M. Hirna, and S. Jain, ‘Improving accuracy of deep learning-based compression techniques by introducing perceptual loss in industrial IoT’, in International Conference on Innovative Computing and Communications: Proceedings of ICICC 2021, Volume 3, 2022, pp. 61–69.

Honours and Achievements
●    Qualified GATE 2016, 2018
●    Qualified UGC NET 2017