Ferdous Pervej
Electrical and Computer Engineering
Assistant Professor
Educational Background
Biography
Ferdous Pervej received the B.Sc. degree in Electronics and Telecommunication Engineering from the Rajshahi University of Engineering and Technology, Rajshahi, Bangladesh, in 2014; the M.S. degree in Electrical Engineering from Utah State University (USU), Logan, UT, USA, in 2019; and the Ph.D. degree in Electrical Engineering from North Carolina State University, Raleigh, NC, USA, in 2023. From August 2023 to July 2025, he was a Postdoctoral Scholar in the Ming Hsieh Department of Electrical and Computer Engineering at the University of Southern California, Los Angeles, CA, USA. He is currently an Assistant Professor of Computer Engineering in the Electrical and Computer Engineering Department at USU. His primary research interests are distributed machine learning, wireless communication networks, edge caching/computing, and machine learning for wireless communications.
Teaching Interests
Wireless Communication and Networking, Machine Learning, Optimization, and Distributed Machine Learning
Research Interests
Wireless Communication and Networking, Distributed Machine Learning, Edge Computing, and Optimization
Publications | Journal Articles
Academic Journal
- Rizwan, A., Han, D., Pervej, F., Brinton, C.G, Molisch, A.F, Minseok Choi, M., (2026). Efficient Split Learning With Overlapping Areas: Handling Distribution Shift in Multi-Cell Networks. IEEE Transactions on Networking, 34, 2834-2849. doi: 10.1109/TON.2026.3654381
- Pervej, F., Molisch, A.F, (2024). Resource-aware hierarchical federated learning in wireless video caching networks. IEEE Transactions on Wireless Communications, 24:1, 165-180. doi: 10.1109/TWC.2024.3489578
- Pervej, F., Jin, R., Dai, H., (2024). Hierarchical Federated Learning in Wireless Networks: Pruning Tackles Bandwidth Scarcity and System Heterogeneity. IEEE Transactions on Wireless Communications, 23:9, 11417 - 11432. doi: 10.1109/TWC.2024.3382093
- Pervej, F., Jin, R., Lin, S., Dai, H., (2023). Efficient Content Delivery in User-Centric and Cache-Enabled Vehicular Edge Networks with Deadline-Constrained Heterogeneous Demands. IEEE Transactions on Vehicular Technology , 73:1, 1129 - 1145. doi: 10.1109/TVT.2023.3300954
- Pervej, F., Jin, R., Dai, H., (2023). Resource Constrained Vehicular Edge Federated Learning With Highly Mobile Connected Vehicles. IEEE Journal on Selected Areas in Communications, 41:6, 1825 - 1844. doi: 10.1109/JSAC.2023.3273700
An asterisk (*) at the end of a publication indicates that it has not been peer-reviewed.
Publications | Other
An asterisk (*) at the end of a publication indicates that it has not been peer-reviewed.