Prof. Qingjiang Shi (史清江)

 Associate editor, IEEE Trans. Signal Processing


Office:442L@Jishi Building 

Emailshiqj AT tongji DOT edu DOT cn,

Tel: 021-69580215

Wechat: SJTUMN

Google Scholar:



Recent research directions:

1. Spatio-temporal big data processing 

2. Distributed AI over IoT

3. Machine learning for multimedia processing

4. Resource management for wireless networks

5. Optimization methods and large-scale computing


Brief intro: 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 40 IEEE journals (five papers were ESI highly cited papers and one was nominated as the best paper award of IEEE Signal Processing Society in 2016) and filed more than 15 national patents.

Dr. Shi is an Associate Editor for the IEEE TRANSACTIONS ON SIGNAL PROCESSING. He was awarded Golden Medal at the 46th International Exhibition of Inventions of Geneva in 2018, and also was the recipient of 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.


Recent works:

[1] City traffic flow prediction with incomplete data using constrained PPCA and LSTM, joint work with S. Zhao and Q. Jiang, submitted to IEEE J-IOT, 2018.

[2] Learning to optimize: training deep neural networks for interference management, joint work with H. Sun, X. Chen, M. Hong, X. Fu, N. Sidiropoulos, IEEE T-SP, vol. 66, no. 20, pp. 5438-5453, 2018
[3] Penalty dual decomposition method for nonsmooth optimization, Part I & II, joint work with M. Hong, X. Fu, T.-S. Chang, submitted to IEEE T-SP, 2018. 

[4] Anchor-free correlated topic modeling, joint work with X. Fu, K. Huang, N. Sidiropoulos, M. Hong, IEEE T-PAMI, early access, 2018.
[5] Inexact block coordinate descent methods for symmetric nonnegative matrix factorization, joint work with H. Sun, S. Lu, M. Hong, M. Razaviyayan, IEEE T-SP, vol. 65, no. 22, pp. 5995-6008, 2017.



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