Ning Lu PhD

Dr. Ning Lu is an Assistant Professor in the Department of Electrical & Computer Engineering at Queen’s University. He is also a Tier 2 Canada Research Chair in Future Communication Networks. Dr. Lu received the BEng (2007) and MEng (2010) degrees from Tongji University, Shanghai, China, and a PhD degree (2015) from the University of Waterloo, Waterloo, ON, Canada, all in electrical engineering. Prior to joining Queen’s University, he was an assistant professor in the Department of Computing Science at Thompson Rivers University, Kamloops, BC, Canada. From 2015 to 2016, he was a postdoctoral fellow with the Coordinated Science Laboratory, University of Illinois at Urbana-Champaign. He also spent the summer of 2009 as an intern at the National Institute of Informatics, Tokyo, Japan. 

His current research interests include scheduling, distributed algorithms, and reinforcement learning for wireless communication networks. He has published more than 60 papers in top IEEE journals and conferences, including IEEE/ACM Transactions on Networking, IEEE Journal on Selected Areas in Communications, ACM MobiHoc, and IEEE INFOCOM, etc. 

Dr. Lu has been the recipient of several awards and fellowships. He and his team won second place in the 2014 Valeo Innovation Challenge for excellence in vehicular networking protocol design. He was presented with the best paper award at the 2014 IEEE GLOBECOM conference. He received an NSERC Postdoctoral Fellowship in 2015. Dr. Lu is currently chairing the Special Interest Group (SIG) on AI Empowered Internet of Vehicles (IoV), IEEE Cognitive Networks Technical Committee. He also served as Vice Chair of the Technical Program Committee (TPC) for ICCSPA'22 and 24. 

Connected Intelligence Research Lab

Research Interests: Scheduling, computing, learning in communication networks, with applications to Internet of Things, autonomous vehicles, data centers, etc. 

For more information about Dr. Lu's research, visit the Connected Intelligence Research Lab page.

Also, visit his Google Scholar Profile

• ELEC 373 Computer Networks, Winter 2020, 2022, 2023, 2024
• ELEC 829 Optimization for Machine Learning, Winter 2024
• ELEC 860 Communication Network Analysis, Winter 2021, 2022
• ELEC 326 Probability and Random Processes, Fall 2021

Recent Publications 

• J. Steiger, Bin Li, and N. Lu, "Backlogged Bandits: Cost-Effective Learning for Utility Maximization in Queueing Networks," In Proc. IEEE International Conference on Computer Communications (INFOCOM), Vancouver, Canada, May 2024. [Acceptance rate: 19.6%]
• K.M. Mahfujul, K. Qu, Q. Ye, and N. Lu. "Augmenting Backpressure Scheduling and Routing for Wireless Computing Networks," In Proc. IEEE International Conference on Communications (ICC), Rome, Italy, May 2023.
• J. Steiger, B. Li, B. Ji, and N. Lu, "Constrained Bandit Learning with Switching Costs for Wireless Networks," In Proc. IEEE International Conference on Computer Communications (INFOCOM), New Jersey, USA, May 2023. [Acceptance rate: 19.2%]
• M. Beitollahi and N. Lu, "Federated Learning over Wireless Networks: Challenges and Solutions," IEEE Internet of Things Journal (IoTJ), Vol. 10, No. 16, pp. 14749-14763, 2023.
• M. Beitollahi and N. Lu, "FLAC: Federated Learning with Autoencoder Compression and Convergence Guarantee,” In Proc. IEEE Global Communications Conference (GLOBECOM), Rio de Janeiro, Brazil, Dec. 2022.
• J. Steiger, B. Li, and N. Lu, "Learning from Delayed Semi-Bandit Feedback under Strong Fairness Guarantees," In Proc. IEEE International Conference on Computer Communications (INFOCOM), May 2022. [Acceptance rate: 19.9%] 
• X. Kong, N. Lu, and B. Li, "Optimal Scheduling for Unmanned Aerial Vehicle Networks with Flow-Level Dynamics," IEEE Transactions on Mobile Computing (TMC), Vol. 20, No. 3, pp. 1186-1197, 2021. 

For a complete list of publications, visit Dr. Lu’s  Google Scholar Citations