人员简介

SHI, Qingjiang

Biography

POSITION/TITLE

Lab Director

EMAIL

shiqj@sribd.cn

EDUCATION BACKGROUND

2006.9~2011.1 Shanghai Jiao Tong University,Electronic Engineering  

1999.9~2006.7 China University of Petroleum,Electronic and Information Engineering

RESEARCH INTERESTS

Network system optimization,  Big data analytics for signal/network Systems, Distributed machine learning

PERSONAL INTRODUCTION

Dr. Qingjiang Shi received his Ph.D. degree in electronic engineering from Shanghai Jiao Tong University, Shanghai, China, in 2011. From September 2009 to September 2010, he visited Prof. Z.-Q. (Tom) Luo's research group at the University of Minnesota, Twin Cities. In 2011, he worked as a Research Scientist at Bell Labs China. From 2012, He was with the School of Information and Science Technology at Zhejiang Sci-Tech University. From Feb. 2016 to Mar. 2017, he worked as a research fellow at Iowa State University, USA. From Mar. 2018, he is currently a full professor with the School of Software Engineering at Tongji University. He is also with the Shenzhen Research Institute of Big Data. His interests lie in algorithm design and analysis with applications in machine learning, signal processing and wireless networks. So far he has published more than 80 IEEE journals and filed about 40 national patents.Dr. Shi was an Associate Editor for the IEEE TRANSACTIONS ON SIGNAL PROCESSING. He was the recipient of IEEE Signal Processing Society Best Paper Award in 2022, the Huawei Technical Cooperation Achievement Transformation Award (2nd Prize) in 2022, the Huawei Outstanding Technical Achievement Award in 2021, the Golden Medal at the 46th International Exhibition of Inventions of Geneva in 2018, the First Prize of Science and Technology Award from China Institute of Communications in 2017, the National Excellent Doctoral Dissertation Nomination Award in 2013, the Shanghai Excellent Doctorial Dissertation Award in 2012, and the Best Paper Award from the IEEE PIMRC'09 conference.

ACADEMIC PUBLICATIONS

[1] Qingjiang Shi, Mesiam Razaviyayn, Zhi.-Quan Luo, and Chen He. “An iteratively weighted MMSE approach to distributed sum-utility maximization for a MIMO interfering broadcast Channel,” IEEE Transactions on Signal Processing, vol.59, no. 9, pp. 4331-4340, Sept. 2011. google citation 1466, ESI高被引论文,获提名2016 IEEE SPS Best Paper Award

[2] H. Sun, X. Chen, Qingjiang Shi, M. Hong, X. Fu and N. D. Sidiropoulos, "Learning to optimize: training deep neural networks for interference management,"  IEEE Transactions on Signal Processing, vol. 66, no. 20, pp. 5438-5453, 15 Oct.15, 2018. 加上会议版Google citation 792, ESI高被引论文,获2022 IEEE SPS Best Paper Award

[3] Qingjiang Shi, Liang Liu, Weiqiang Xu, Rui Zhang, “Joint transmit beamforming and receive power splitting for MISO SWIPT systems,” IEEE Transactions on Wireless Communications, vol. 13, no. 6, pp. 3269-3280, Jun. 2014. Google citation 520, ESI高被引论文

[4] X. Zhao, S. Lu, Qingjiang Shi, Z.-Q. Luo, “Rethinking WMMSE: Can Its Complexity Scale Linearly With the Number of BS Antennas?” IEEE Transactions on Signal Processing, early access, 2023.

[5] L. Xie, J. Liu, S. Lu, T.-H. Chang, and Qingjiang Shi, "An Efficient Learning Framework For Federated XGBoost Using Secret Sharing And Distributed Optimization",accepted by ACM Transactions on Intelligent Systems and Technology, vol. 13, no. 5, pp.1-28, 2022.

[6]  Li D, Li J, Zeng X, Stankovic V, Stankovic L, Xiao C, Qingjiang Shi. Transfer learning for multi-objective non-intrusive load monitoring in smart building[J]. Applied Energy, 2023, 329: 120223.

[7] Qingjiang Shi and M. Hong. Penalty dual decomposition method for nonsmooth nonconvex optimization—Part I: Algorithms and convergence analysis. IEEE Transactions on Signal Processing, 68, pp. 4108-4122,  June 2020.

[8] Y. Dong, X. Jiang, H. Zhou, Y. Lin, and Qingjiang Shi*. SR2CNN: Zero-shot learning for signal recognition. IEEE Transactions on Signal Processing, 69:2316 – 2329, Mar. 2021. ESI高被引论文

[9] M. Zhao, Qingjiang Shi, Y. Cai, M. Zhao, and Y. Li. Distributed penalty dual decomposition algorithm for optimal power flow in radial networks. IEEE Transactions on Power Systems, 35(3): 2176-2189, May 2020.

[10] Qingjiang Shi, M. Hong, X. Fu, and T. -H. Chang. Penalty dual decomposition method for nonsmooth nonconvex optimization—Part II: Applications. IEEE Transactions on Signal Processing, 68: 4242-4257, June 2020.