Publications

In Preparation:

1. I. P. Shahrbabaki and F. Pervej , “**Multimodal Sensing and Continual Federated Learning under Continual Data Distribution Shift for Autonomous Connected Vehicles**,” to be submitted to suitable IEEE Transactions, 2026.
2. R. Bomah and F. Pervej , “**Channel Graphs and Statistics-aided Training Solutions for Double-Directional Channel Modeling**,” to be submitted to suitable IEEE Transactions, 2026.
3. F. Pervej et al., “**Efficient Personalized Hierarchical Split Federated Learning in Wireless Networks**,” to be submitted to suitable IEEE Transactions, 2026.
4. F. Pervej et al., “**Computation- and Communication-Efficient Federated Learning in UAV Networks**,” (in progress) expected to be submitted to suitable IEEE Transactions, 2026.

Under Review:

1. Y. Zhang, F. Pervej , and A. F. Molisch, “Revenue Optimization in Wireless Video Caching Networks: A Privacy-Preserving Two-Stage Solution,” under review, 2026.
2. F. Pervej , M. Choi, and A. F. Molisch, “Online-Score-Aided Federated Learning for Resource-Constrained Wireless Clients with Continual Data Arrival,” under review for possible publication in IEEE Transactions on Mobile Computing, 2026.
3. M. F. Reza, F. Pervej , R. Jin, T. Wu, and H. Dai, “BAT: Core Target–Guided Generative Attacks for Transferable Targeted Adversarial Examples,” under review for possible publication in IEEE Transactions on Information Forensics and Security, 2026.

Published/Accepted:

1. F. Pervej , P Pratik, K. Manjunatha, P. Shamain, and A. F. Molisch, “Double-Directional Wireless Channel Generation using Statistics-Informed Machine Learning,” in IEEE Journal of Selected Topics in Electromagnetics, Antennas and Propagation (JSTEAP), 2026, doi: 10.1109/JSTEAP.2026.3701014.
2. A. Rizwan, D-J. Han, F. Pervej , C. G. Brinton, A. F. Molisch, and M. Choi, “Efficient Split Learning with Overlapping Areas: Handling Distribution Shift in Multi-Cell Networks,” to appear in IEEE/ACM Transactions on Networking, 2026, doi 10.1109/TON.2026.3654381.
3. M. F. Pervej and A. F. Molisch, 'Resource-Aware Hierarchical Federated Learning for Video Caching in Wireless Networks,' accepted for publication in IEEE Transactions on Wireless Communications (TWC), vol. 24, no. 1, pp. 165-180, Jan. 2025, doi:10.1109/TWC.2024.3489578.
4. M. F. Pervej , R. Jin, and H. Dai, “Hierarchical Federated Learning in Wireless Networks: Pruning Tackles Bandwidth Scarcity and System Heterogeneity,” in IEEE Transactions on Wireless Communications (TWC), April 2024, doi: 10.1109/TWC.2024.3382093
5. M. F. Pervej , R. Jin, and H. Dai, “Resource Constrained Federated Learning with Highly Mobile Vehicular Clients,” in IEEE Journal on Selected Areas in Communications (JSAC), vol. 41, no. 6, pp. 1825-1844, June 2023, doi: 10.1109/JSAC.2023.3273700.
6. M. F. Pervej , R. Jin, S.-C. Lin, and H. Dai, “Efficient Content Delivery in User-Centric and Cache-Enabled Vehicular Edge Networks with Deadline-Constrained Heterogeneous Demands,” in IEEE Transactions on Vehicular Technology (TVT), vol. 73, no 1, pp. 1129 - 1145, 2023, doi: 10.1109/TVT.2023.3300954.

Under Review:

1. R. Boamah and F. Pervej , “Double-Directional Wireless Channel Modeling Using Statistics-Aided Machine Learning,” under review for possible publication in the IEEE Military Communications Conference, 2026.

Published/Accepted:

1. M. F. Pervej , R. Jin, M. M. U. Chowdhury, S. Singh, I. Guvenç, and H Dai, “Computation- and Communication-Efficient Online FL for Resource-Constrained Aerial Vehicles”, accepted for publication in IEEE Military Communications Conference, 2025.
2. Y. Zhang, M. F. Pervej and A. F. Molisch, “Revenue Optimization in Video Caching Networks with Privacy-Preserving Demand Predictions,” accepted for publication in IEEE Military Communications Conference, 2025.
3. M. F. Pervej , P Pratik, K. Manjunatha, P. Shamain, and A. F. Molisch, “Double Directional Wireless Channel Generation: A Statistics-Informed Generative Approach,” (accepted) in Proc. IEEE ICC, Montreal, Canada, 2025.
4. M. F. Pervej and A. F. Molisch, “Personalized Hierarchical Split Federated Learning in Wireless Networks,” (accepted) in Proc. IEEE ICC, Montreal, Canada, 2025.
5. M. F. Pervej and A. F. Molisch, 'Resource-Aware Hierarchical Federated Learning for Video Caching in Wireless Networks,' in Proc. of IEEE ICC, Denver, CO, 2024.
6. M. F. Pervej , J. Guo, K. J. Kim, K. Parsons, P. Orlik, S. D. Cairano, M. Menner, K. Berntorp, Y. Nagai, and H. Dai, “Mobility, Communication and Computation Aware Federated Learning for Internet of Vehicles,” in Proc. of 33rd IEEE Intelligent Vehicles Symposium (IV), Aachen, Germany, June 2022.
7. M. F. Pervej , S. -C. Lin, “Eco-Vehicular Edge Networks for Connected Transportation: A Distributed Multi-Agent Reinforcement Learning Approach,” in Proc. of IEEE VTC2020-Fall, Victoria, B.C., Canada, October 2020.
8. M. F. Pervej , S. -C. Lin, “Dynamic Power Allocation and Virtual Cell Formation for Throughput-Optimal Vehicular Edge Networks in Highway Transportation,” in Proc. of IEEE ICC 2020 Workshops, June 2020.
9. M. F. Pervej , L. T. Tan, Rose Qingyang Hu, “User Preference Learning Aided Collaborative Edge Caching for Small Cell Networks,” in Proc. of IEEE Globecom, Taipei, Taiwan, December 2020.
10. M. F. Pervej , L. T. Tan, Rose Qingyang Hu, “Artificial Intelligence Assisted Collaborative Edge Caching in Small Cell Networks,” in Proc. of IEEE Globecom, Taipei, Taiwan, December 2020.