About
Dr. Hong-Ning Dai (Henry) obtained a Ph.D. in Computer Science and Engineering from the Department of Computer Science and Engineering at the Chinese University of Hong Kong and a D.Eng. in Computer Technology Application from the Department of Computer Science and Engineering at Shanghai Jiao Tong University. Before joining HKBU, he worked in the Department of Information Engineering at the Chinese University of Hong Kong, the School of Computer Science and Engineering at Macau University of Science and Technology, and the Department of Computing and Decision Sciences at Lingnan University, Hong Kong. He has published more than 200 papers in referred journals and conferences, including Proceedings of the IEEE, IEEE JSAC, IEEE TMC, IEEE TPDS, IEEE Trans. on Computer, IEEE TDSC, IEEE TKDE, IEEE TNNLS, ACM/IEEE ASE, IEEE INFOCOM, AAAI, ACM CSUR, IEEE Communications Surveys & Tutorials, etc. He is a senior member of ACM, IEEE, and EAI. He has served as an associate editor for IEEE Transactions on Intelligent Transportation Systems, IEEE Transactions on Industrial Informatics, Ad Hoc Networks, and Connection Science. He has also served as general chair/PC chair of many international conferences.
Dr. Henry Dai is recruiting
self-motivated Ph.D./RA/Post-doc with a strong background in computer science, electronic engineering, or applied mathematics, working in the fields including (but not limited to) blockchain, the Internet of Things, and big data analytics. More details about Ph.D. applications and Ph.D. scholarships are as follows.
Research Interests
- Internet of Things
- Blockchain
- Big Data Analytics
Selected Publications
- Zhaolin Yuan, Xiaojuan Ban, Zixuan Zhang, Xiaorui Li, and Hong-Ning Dai, “ODE-RSSM: Learning Stochastic Recurrent State Space Model from Irregular Sampled Data”, accepted to appear in the Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI), Washington, DC, USA, 2023.
- Jianzhong Su, Hong-Ning Dai, Lingjun Zhao, Zibin Zheng, Xiapu Luo, “Effectively Generating Vulnerable Transaction Sequences in Smart Contracts with Reinforcement Learning-guided Fuzzing”, accepted to appear in the 37th IEEE/ACM International Conference on Automated Software Engineering (ASE), Michigan, USA, 2022.
- Xuran Li, Shuaishuai Guo, Hong-Ning Dai, and Dengwang Li, “Infectious Probability Analysis on COVID-19 Spreading with Wireless Edge Networks”, in IEEE Journal on Selected Areas in Communications (JSAC), https://doi.org/10.1109/JSAC.2022.3211534 (early access), 2022.
- Junqin Huang, Linghe Kong, Long Cheng, Hong-Ning Dai, Meikang Qiu, Guihai Chen, Xue Liu, and Gang Huang, “Block-Sense: Towards Trustworthy Mobile Crowdsensing via Proof-of-Data Blockchain”, accepted to appear in IEEE Transactions on Mobile Computing (TMC), 2022
- Xiaoyu Qiu, Wuhui Chen, Bingxin Tang, Junyuan Liang, Hong-Ning Dai, and Zibin Zheng, “A Distributed and Privacy-Aware High-Throughput Transaction Scheduling Approach for Scaling Blockchain”, accepted to appear in IEEE Transactions on Dependable and Secure Computing (TDSC), 2022.
- Jinghua Yang, Chuan Chen, Hong-Ning Dai, Meng Ding, Zhebin Wu, and Zibin Zheng, “Robust Corrupted Data Recovery and Clustering via Generalized Transformed Tensor Low-rank Representation”, accepted to appear in IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022.
- Wei Wang, Xiaoyang Suo, Xiangyu Wei, Bin Wang, Hao Wang, Hong-Ning Dai, and Xiangliang Zhang, “HGATE: Heterogeneous Graph Attention Auto-Encoders”, accepted to appear in IEEE Transactions on Knowledge and Data Engineering (TKDE) (early access), 2021, doi: 10.1109/TKDE.2021.3138788.
- Huawei Huang, Zhengyu Yue, Xiaowen Peng, Liuding He, Wuhui Chen, Hong-Ning Dai, Zibin Zheng, and Song Guo, “Elastic Resource Allocation against Imbalanced Transaction Assignments in Sharding-based Permissioned Blockchains”, in IEEE Transactions on Parallel and Distributed Systems (TPDS), vol. 33, no. 10, pp. 2372-2385, 1 Oct. 2022.
- Yulei Wu, Hong-Ning Dai, Haozhe Wang, Zehui Xiong, and Song Guo, “A Survey of Intelligent Network Slicing Management for Industrial IoT: Integrated Approaches for Smart Transportation, Smart Energy, and Smart Factory”, in IEEE Communications Surveys and Tutorials (CST), vol. 24, no. 2, pp. 1175-1211, Second Quarter 2022.
- Jiafu Wan, Xiaomin Li, Hong-Ning Dai, Andrew Kusiak, Miguel Martínez-García, and Di Li, “Artificial Intelligence Driven Customized Manufacturing Factory: Key Technologies, Applications, and Challenges”, in Proceedings of the IEEE (PIEEE), Vol. 109, No. 4, pp. 377 - 398, April 2021.
- Hong-Ning Dai, Raymond Chi-Wing Wong, Hao Wang, Zibin Zheng, and Athanasios V. Vasilakos, “Big Data Analytics for Large Scale Wireless Networks: Challenges and Opportunities”, in ACM Computing Surveys (CSUR), vol. 52, no. 5, pp. 99:1-36, 2019.
