Dr. Dongmei Zhao

Dr. Zhao received a B. Eng. degree in Wireless Communication from Northern Jiaotong University (now Beijing Jiaotong University), Beijing, China in 1992 and a Ph.D degree in the Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Ontario, Canada in June 2002. In July 2002 she joined the Department of Electrical and Computer Engineering at McMaster University, where she is a full professor. From April 2004 to March 2009 she was an adjunct assistant professor in the Department of Electrical and Computer Engineering at University of Waterloo. Dr. Zhao is an associate editor of the IEEE Internet of Things Journal. She served as an associate editor of the IEEE Transactions on Vehicular Technology between 2007 and 2017. She is a co-chair of the Project & Awards committee in the IEEE ComSoc Frontier Networking Symposium 2023, a co-chair of the Mobile and Wireless Networks Symposium of IEEE Global Communications Conference (GLOBECOM) 2020, a co-chair of the Wireless Networking Symposium in IEEE GLOBECOM 2007, and a co-chair of the technical program committee for IEEE International Workshop on Computer Aided Modelling and Design of Communication Links and Networks (CAMAD) 2016. Dr. Zhao is a senior member of IEEE and a Professional Engineer of Ontario. Her current research areas are mainly in digital twins, mobile computation offloading, energy efficient wireless networking, and vehicular communication networks.

B.S. (Northern Jiaotong University, Beijing, China) ; Ph.D (University of Waterloo, Canada)

NSERC University Faculty Award, 2003-2006, 2006-2007, 2008-2009
NSERC Discovery Accelerator Supplement Award, 2009-2012
Top associate editor, IEEE Transactions on Vehicular Technology, 2009, 2010, 2011, 2012
Best paper award, IEEE Green Computing and Communications, 2018

[1] H. Zhang, H. Liang, Y. Yao, L. Wang, B. Lin, and D. Zhao, “Joint Resource Allocation and Security Redundancy for Autonomous driving based on Deep Reinforcement Learning Algorithm,” IET Intelligent Transport Systems, accepted.
[2] H. Zhang, H. Liang, L. Wang, Y. Yao, B. Lin, and D. Zhao, “DRL-Based Resource Allocation Game with Influence of Review Information for Vehicular Edge Computing Systems”, IEEE Transactions on Vehicular Technology, accepted.
[3] X. Fu. Q. Yuan, Z. Zhuang, Y. Li, J. Liao, and D. Zhao, “TacNet: A Tactic-Interactive Resource Allocation Method for Vehicular Networks,” IEEE Internet of Things Journal, accepted.
[4] L. Wang, H. Liang, and D. Zhao, “Deep Reinforcement Learning-based Computation Offloading and Power Allocation within a Dynamic Platoon Network,” IEEE Internet of Things Journal, accepted.
[5] H. Chen, T. Todd, D. Zhao, and G. Karakostas, “Digital Twin Model Selection for Feature Accuracy”, IEEE Internet of Things Journal, accepted.
[6] L. Jiao, J. Zhao, Y. Xu, T. Zhang, H. Zhou, and D. Zhao, “Performance Analysis for Downlink Transmission in Multi-Connectivity Cellular V2X Networks”, IEEE Internet of Things Journal, accepted.
[7] J. Chen, B. Qian, H. Zhou, and D. Zhao, “A Decentralized Web 3.0 Platform for Manufacturing Customized Products”, IEEE Network Magazine, accepted.
[8] H. Chen, T. Todd, D. Zhao, and G. Karakostas, “Task Class Partitioning for Mobile Computation Offloading”, IEEE Internet of Things Journal, vol. 11, no. 2, Jan. 2024, pp. 2534-2549.
[9] H. Chen, T. Todd, D. Zhao, and G. Karakostas, “Wireless and Service Allocation for Mobile Computation Offloading with Task Deadlines”, IEEE Transactions on Mobile Computing, accepted.
[10] M. Vaezi, K. Noroozi, T. Todd, D. Zhao, and G. Karakostas, “Digital Twin Placement for Minimum Application Request Delay with Data Age Targets”, IEEE Internet of Things Journal, vol. 10, no. 13, July 2023, pp. 11547-11557.
[11] M. Vaezi, K. Noroozi, T. D. Todd, D. Zhao, G. Karakostas, H. Wu, and X. Shen, “Digital Twins from a Networking Perspective,” IEEE Internet of Things Journal, vol. 9, no. 23, Dec. 2022, pp. 23525-23544.
[12] P. Teymoori, A. Hekmati, T. D. Todd, D. Zhao, and G. Karakostas, “Preemptive Mobile Computation Offloading with Hard Deadlines and Concurrent Local Execution”, IEEE Transactions on Green Communications and Networking, vol. 5, no. 2, June 2021, pp.950-963.
[13] S. Zhu, L. Gui, D. Zhao, N. Cheng, Q. Zhang, and X. Lang, “Learning-Based Computation Offloading Approaches in UAVs-Assisted Edge Computing,” IEEE Transactions on Vehicular Technology, vol. 70, no. 1, 2021, pp. 928-944.
[14] Z. Wang, D. Zhao, M. Ni, L. Li, and C. Li, “Collaborative Mobile Computation Offloading to Vehicle-based Cloudlets,” IEEE Transactions on Vehicular Technology, vol. 70, no. 1, Jan. 2021, pp. 768-781.
[15] S. Mu, Z. Zhong, and D. Zhao, “Energy-efficient and delay-fair mobile computation offloading,” IEEE Transactions on Vehicular Technology, vol. 69, no. 12, Dec. 2020, pp. 15746-15759.
[16] A. Hekmati, P. Teymoori, T. D. Todd, D. Zhao, and G. Karakostas, “Optimal multi-part mobile computation offloading with hard deadline constraints,” Elsevier Computer Communications, vol. 160, July 2020, pp. 614-622.
[17] H. Chen, D. Zhao, R. Chai, and Q. Chen, “Joint computation offloading and radio resource allocations for small-cell wireless cellular networks,” IEEE Transactions on Green Communications and Networking, vol. 4, no. 3, Sept. 2020, pp. 745-758.
[18] A. Hekmati, P. Teymoori, T. D. Todd, D. Zhao, and G. Karakostas, “Optimal mobile computation offloading with hard deadline constraints,” IEEE Transactions on Mobile Computing, vol. 19, no. 9, Sept. 2020, pp. 2160-2173.