Publications

Journal Articles

1. Banerjee, S., Bhuyan, D., Elmroth, E., and Bhuyan, M. (2024). “Cost-Efficient Feature Selection for Horizontal Federated Learning.” IEEE Transactions on Artificial Intelligence, vol. 5, no. 12, pp. 6551–6565.
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Conference Papers

1. Banerjee, S., Bergqvist, D., Toor, S., Rohner, C., and Johnsson, A. (2026). “Quantifying Catastrophic Forgetting in IoT Intrusion Detection Systems.” In Proc. IEEE International Conference on Communications (ICC).
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2. Banerjee, S., Subramaniam, V., Roy, D., Subbaraju, V., and Bhuyan, M. (2026). “Personalized Image Privacy Advisors via Federated Daisy-Chaining.” In Proc. IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), pp. 2808–2817.
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3. Banerjee, S., Roy, D., Subbaraju, V., and Bhuyan, M. (2025). “Predicting Event Memorability Using Personalized Federated Learning.” In Proc. IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), pp. 1556–1565.
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4. Dadras, A., Banerjee, S., Prakhya, K., and Yurtsever, A. (2024). “Federated Frank-Wolfe Algorithm.” In Proc. Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML-PKDD), pp. 58–75. Springer.
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5. Banerjee, S., Dadras, A., Yurtsever, A., and Bhuyan, M. (2024). “Personalized Multi-tier Federated Learning.” In Proc. International Conference on Neural Information Processing (ICONIP), pp. 192–207. Springer. (Early version presented at FL-NeurIPS Workshop, 2022.)
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6. Banerjee, S., Patel, Y. S., Kumar, P., and Bhuyan, M. (2023). “Towards Post-disaster Damage Assessment using Deep Transfer Learning and GAN-based Data Augmentation.” In Proc. 24th International Conference on Distributed Computing and Networking (ICDCN), pp. 372–377. ACM.
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7. Banerjee, S., Vu, X.-S., and Bhuyan, M. (2022). “Optimized and Adaptive Federated Learning for Straggler-Resilient Device Selection.” In Proc. International Joint Conference on Neural Networks (IJCNN), pp. 1–9. IEEE.
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8. Banerjee, S., Elmroth, E., and Bhuyan, M. (2021). “Fed-FiS: A Novel Information-Theoretic Federated Feature Selection for Learning Stability.” In Proc. International Conference on Neural Information Processing (ICONIP), pp. 480–487. Springer.
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9. Banerjee, S., Misra, R., Prasad, M., Elmroth, E., and Bhuyan, M. (2020). “Multi-diseases Classification from Chest X-ray: A Federated Deep Learning Approach.” In Proc. Australasian Joint Conference on Artificial Intelligence (AI 2020), pp. 3–15. Springer.
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10. Patel, Y. S., Banerjee, S., Misra, R., and Das, S. K. (2020). “Low-Latency Energy-Efficient Cyber-Physical Disaster System Using Edge Deep Learning.” In Proc. 21st International Conference on Distributed Computing and Networking (ICDCN), pp. 34:1–34:6. ACM.
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11. Chakraborty, M., Banerjee, S., and Chaki, N. (2020). “A Framework Towards Generalized Mid-term Energy Forecasting Model for Industrial Sector in Smart Grid.” In Proc. International Conference on Distributed Computing and Internet Technology (ICDCIT), pp. 296–310. Springer.
12. Banerjee, S., Mukherjee, P., Kanrar, S., and Chaki, N. (2018). “A novel symmetric algorithm for process synchronization in distributed systems.” In Algorithms and Applications: ALAP 2018, pp. 51–66. Springer Singapore.
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Workshop Papers

1. Lunderbye, E., Banerjee, S., Rohner, C., and Johnsson, A. (2026). “Towards Intrusion Detection Systems for RPL-based IoT Networks using Foundation Models.” Accepted and presented in the Swedish National Computer Networking Workshop (SNCNW). arXiv:2606.03530.
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2. Sun, Y., Johnsson, A., and Banerjee, S. (2026). “Rethinking IoT Intrusion Detection: Augmenting Routing Metrics with Radio Features.” Accepted and presented in the Swedish National Computer Networking Workshop (SNCNW). arXiv:2606.07282.
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3. Banerjee, S., Yurtsever, A., and Bhuyan, M. (2022). “Personalized Multi-tier Federated Learning.” Accepted and presented in Workshop on Federated Learning: Recent Advances and New Challenges (NeurIPS).
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Book Chapters

1. Banerjee, S., Ghosh, S., and Mishra, B. K. (2021). “Application of deep learning for energy management in smart grid.” In Deep Learning in Data Analytics: Recent Techniques, Practices and Applications, pp. 221–239. Springer.
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Patent

1. Shekhar, H., Banerjee, S., Misra, R., and Patel, Y. S. (2024). “System and Method for Detection of Banned Objects from Images in Real-time using Intelligence at the Edge.” Indian Patent No. 550543, Application No. 202031006618.