Edge Intelligence, Federated Learning, Integrated Communications and Sensing
From 2015-9 to 2019-12, The University of Hong Kong, Electronic and Electrical Engineering, PhD, Supervisor: Kaibin Huang
From 2012-9 to 2015-3, Zhejiang University, Information and Electronic Engineering, Master, Supervisor: Caijun Zhong
From 2008-9 to 2012-6, Zhejiang University, Information and Electronic Engineering, bachelor
HONORS AND AWARDS
- Best paper award at 2013 International Conference on WCSP.
- Hong Kong Ph.D. Fellowship. (09/2015 - 08/2019)
- Outstanding Ph.D. Thesis Award at The University of Hong Kong
- Exemplary Reviewer at IEEE Transactions on Communications
- Shenzhen Overseas High-Caliber Personnel (Level C)
Dr. Guangxu Zhu is a research scientist at the Shenzhen research institute of big data. He received the Ph.D. degree in electrical and electronic engineering from The University of Hong Kong in 2019, and the BS and MS degrees in information and communication engineering from Zhejiang University in 2012 and 2015, respectively. His research interests include intelligent edge, federated learning, and integrated sensing and communications. He have published over 30 top-tier journal papers and more than 20 conference papers in his research area. He is currently hosting several national and provincial project including NSFC Youth Program, Guangdong Natural Science Foundation General Program, and the 6G open project of China Academy of Information and Communications Technology and participating the National Key Research and Development Program of China. He is a recipient of the Hong Kong Postgraduate Fellowship (HKPF), Outstanding Ph.D. Thesis Award from HKU, and Best Paper Award from WCSP 2013, Shenzhen Overseas High-Caliber Personnel (Level C). He was invited to be a co-chair for the “MAC and cross-layer design” track in IEEE PIMRC 2021.
SELECTED JOURNAL PUBLICATIONS
1.G. Zhu, D. Liu, Y, Du, C. You, J. Zhang, and K. Huang, "Toward an Intelligent Edge: Wireless Communication Meets Machine Learning", IEEE Commun. Mag., vol. 58, no. 1, pp. 19 - 25, Jan. 2020. ( ESI highly cited paper, ESI hot paper)
2. G. Zhu, Y. Wang K. Huang, "Broadband analog aggregation for low-latency federated edge learning", IEEE Trans. Wireless Commun., vol. 19, no. 1, pp. 491-506, Jan. 2020. ( ESI highly cited paper)
3. G. Zhu, Y. Du, D. Gunduz, K. Huang, "One-Bit Over-the-Air Aggregation for Communication-Efficient Federated Edge Learning: Design and Convergence Analysis", IEEE Trans. Wireless Commun., vol. 20, no. 3, Mar. 2021.
4. G. Zhu, K. Huang, V. K. N. Lau, B. Xia, X. Li and S. Zhang, "Hybrid beamforming via the Kronecker decomposition for the millimeter-wave massive MIMO systems", IEEE J. Sel Area Commun., Vol. 35, no. 9, pp. 2097–2114, Sep. 2017.
5.G. Zhu and K. Huang, "MIMO Over-the-Air Computation for High-Mobility Multi-Modal Sensing", IEEE IoT Journal, vol. 6, no. 4, pp. 6089 - 6103, Aug. 2019.