Qiang QU is a full professor at Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences. He is the director of Guangdong Provincial Blockchain and Distributed IoT Security Engineering Research Center, the deputy director of Shenzhen Key Laboratory on High-performance Data Mining, and the deputy director of the AI Large Model Research Center at SIAT. He serves on the technical committees of the China Computer Federation (CCF) on Databases, Blockchain, and Information Systems. He held visiting and research positions at Carnegie Mellon University, ETH Zurich, Innopolis University, and Singapore Management University.
His research focuses on trustworthy distributed intelligent systems, bridging data, algorithms, and systems to build reliable, scalable, and efficient infrastructures. His specific interests include distributed systems and consensus protocols, data-intensive computing and intelligent analytics, system security and cryptographic applications, and blockchain-enabled trusted data governance, with the goal of building next-generation distributed intelligent platforms. He has published over 100 papers in top-tier journals and conferences, and authored several books in both Chinese and English, including Blockchain and Artificial Intelligence: The Next Economic Model That Will Change the World and Information Infrastructure and Technology Applications in Emergency Logistics Systems.
He joined the Chinese Academy of Sciences in late 2016 and was promoted to an associate professor, and to a full professor in 2020. He has served as Principal Investigator for multiple national and provincial projects, and was the Chief Scientist of a project supported by the National Key Research and Development Program of China.
Contact
Email: qiang@siat.ac.cn
Address: Shenzhen Institutes of Advanced Technology, 1068 Xueyuan Avenue, Xili, Nanshan District, Shenzhen 518055, China
Multiple postdoc/assistant professor and Ph.D vacancies are available. If you are interested, please check THIS LINK carefully and feel free to contact us if qualified.
Selected Publications
Papers
1. Md M Karim, S. Khan, Qiang Qu. LL-CEIoT: Lightweight LLM-based Collaborative Cloud-Edge Computing for Internet of Things. IEEE Transactions on Mobile Computing (2026) (Corresponding, JCR Q1, CCF A, IF 8.8)
2. Md M Karim, S. Khan, Qiang Qu, M Muzammal, K Sharif. From Trust to Augmentation: A Comprehensive Survey on Synergistic Integration of Decentralized and Generative Intelligence. Computer Science Review (2026) (Corresponding, JCR Q1, IF 17.5)
3. Md Monjurul Karim, Dong Hoang Van, Qiang Qu. Securing Decentralized Finance: A Comprehensive Survey of Maximal Extractable Value and Its Countermeasures. Blockchain: Research and Applications (2026) (Corresponding, JCR Q1, IF 6.5)
4. Md M Karim, Qiang Qu, Y Cai, T Liu, X Meng. Bitcoin reimagined: A comprehensive study of ordinals and inscriptions protocols for Web3 asset innovation. Blockchain: Research and Applications (2025) (Corresponding, JCR Q1, IF 6.5)
5. Karim, M. M., Van, D. H., Khan, S., Qu, Q., & Kholodov, Y. (2025). AI Agents Meet Blockchain: A Survey on Secure and Scalable Collaboration for Multi-Agents. Future Internet, 17(2), 57 (Full Paper，Download PPT, Paper Summary)
6. F. Abbasi, M. Muzzamal, Qiang Qu, F. Riaz, and J. Ashraf. SNCA: Semi-supervised Node Classification for Evolving Large Attributed Graphs. IEEE Big Data Mining and Analytics, 7(3), 794-808 (2024) (Corresponding, JCR Q1, IF 6.1)
7. Xuewen Dong, Jiachen Li, Shujun Li, Zhichao You, Qiang Qu, Yaroslav Kholodov, Yulong Shen. Adaptive Backdoor Attacks with Reasonable Constraints on Graph Neural Networks. IEEE Transactions on Dependable and Secure Computing (2025)(CCF A, JCR Q1，IF 6.8)
8. S. Zhang, S. M. H. Bamakan, Qiang Qu and S. Li, "Learning for Personalized Medicine: A Comprehensive Review From a Deep Learning Perspective," in IEEE Reviews in Biomedical Engineering, vol. 12, pp. 194-208 (2019) (Corresponding, JCR Q1, IF 16)
9. Su Yao, Mu Wang, Qiang Qu, Ziyi Zhang, Yi-Feng Zhang, Ke Xu, Mingwei Xu: Blockchain-Empowered Collaborative Task Offloading for Cloud-Edge-Device Computing. IEEE J. Sel. Areas Commun. 40(12): 3485-3500 (2022) (CCF A, JCR Q1, IF 16.8)
10. Seyed Mojtaba Hosseini Bamakan, Ildar Nurgaliev, Qiang Qu: Opinion leader detection: A methodological review. Expert Systems with Applications 115: 200-222 (2019) (Corresponding, JCR Q1, IF 9.4)
11. Qiang Qu, Ildar Nurgaliev, Muhammad Muzamma：On Spatio-temporal Blockchain Query Processing. Future Generation Computer Systems, 98, 208-218 (2019) (JCR Q1, IF 5.9)
12. Min Yang, Wenpeng Yin, Qiang Qu, Wenting Tu, Ying Shen, Xiaojun Chen: Neural Attentive Network for Cross-Domain Aspect-Level Sentiment Classification. IEEE Trans. Affect. Comput. 12(3): 761-775 (2021) (JCR Q1, IF 11.3)
13. Jiehuan Luo, Xin Cao, Xike Xie, Qiang Qu, Zhiqiang Liu, Christian S. Jensen. Efficient Attribute-Constrained Co-Located Community Search, ICDE 2020: 1201-1212 (Corresponding, CCF A)
14. Ali Hadian, Sadegh Nobari, Behrouz Minaei-Bidgoli, Qiang Qu: ROLL: Fast In-Memory Generation of Gigantic Scale-free Networks. SIGMOD Conference 2016: 1829-1842 (CCF A)
15. Feida Zhu, Qiang Qu, David Lo, Xifeng Yan, Jiawei Han, Philip S. Yu: Mining Top-K Large Structural Patterns in a Massive Network. Proc. VLDB Endow. 4(11): 807-818 (2011) (CCF A)
16. Qiang Qu, Siyuan Liu, Feida Zhu, Christian S. Jensen: Efficient Online Summarization of Large-Scale Dynamic Networks. IEEE Trans. Knowl. Data Eng. 28(12): 3231-3245 (2016) (CCF A, JCR Q1, IF 11.6)
17. Qiang Qu, Susheng Zhang, S.M. Hosseini Bamakan, Christos Doulkeridris, George Vouros (2022). Understanding Health Data by Mobility Analytics. In: Faruque, F.S. (eds) Geospatial Technology for Human Well-Being and Health. Springer, Cham. https://doi.org/10.1007/978-3-030-71377-5_5
18. Qu Qiang, Lin Yimin. Blockchain + Artificial Intelligence: The Next New Economic Model to Change the World. Published by Posts & Telecom Press on April 1, 2019. ISBN: 9787115507990 (Chinese Monograph)
19. Qu Qiang et al. Information Infrastructure Construction and Technology Application in Emergency Logistics Systems. Published by China Fortune Publishing House in November 2024. ISBN: 978-7-5047-8312-7 (Supported by the National Key Publication Publishing Special Planning Project during the 14th Five-Year Plan Period) (Chinese Monograph)