个人简介
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 2018, He is currently a professor with the School of Software Engineering at Tongji University. 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 more than 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, National Excellent Doctoral Dissertation Nomination Award in 2013, Shanghai Excellent Doctorial Dissertation Award in 2012, and the Best Paper Award from the IEEE PIMRC’09 conference.
荣誉与获奖
2022 IEEE信号处理协会最佳论文奖
2020-2023爱思唯尔中国高被引学者
2022年华为技术合作成果转化二等奖
2020年华为优秀技术成果奖
2017年任国际信号处理顶级期刊IEEE Trans. Signal Process.编委
2018年获日内瓦国际发明展发明金奖
2018年获中国通信学会自然科学一等奖
2014年获得全国百篇优秀博士学位论文提名奖
2013年获得上海市研究生优秀成果(博士学位论文)奖
2009年获得国际个人移动通信领域IEEE PIMRC会议最佳论文奖,
2019年获得全国Intel杯人工智能软件创新大赛一等奖(优秀指导教师)
2019年获第五届中国“互联网+”大学生创新创业大赛上海赛区一等奖(优秀指导教师)
研究领域
Intelligent communications and networking
Machine learning for big data analytics
Optimization methods and distributed computing
近期论文
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X. Zhao, S. Lu, Q. Shi* and Z. -Q. Luo, "Rethinking WMMSE: Can Its Complexity Scale Linearly With the Number of BS Antennas?," IEEE Transactions on Signal Processing, vol. 71, pp. 433-446, 2023, doi: 10.1109/TSP.2023.3244104.
Y. Dong, X. Jiang, H. Zhou, Y. Lin, Q. Shi*, "SR2CNN: Zero-Shot Learning for Signal Recognition", IEEE Transactions on Signal Processing, 2021, vol. 69, pp. 2316-2329, 2021.
Q. Shi and M. Hong, "Penalty Dual Decomposition Method For Nonsmooth Nonconvex Optimization—Part I&II: Algorithms and Applications," IEEE Transactions on Signal Processing, 2020. doi: 10.1109/TSP.2020.3001906.
L. Xie, J. Liu, S. Lu, T.-H. Chang, and Q. Shi*, "An Efficient Learning Framework For Federated XGBoost Using Secret Sharing And Distributed Optimization",ACM Transactions on Intelligent Systems and Technology, vol. 13, no. 5, pp.1-28, 2022.
H. Sun, X. Chen, Q. Shi, M. Hong, X. Fu, N. Sidiropoulos, "Learning To Optimize: Training Deep Neural Networks For Interference Management," IEEE Transactions on Signal Processing, vol. 66, no. 20, pp. 5438-5453, 2018