Xiangxiang DAI

Email: xiangxdai0@gmail.com

About me

I am a new Ph.D. student in Advanced Networking and System Research Laboratory (ANSRLab) supervised by Chair Professor John C.S. Lui (ACM/IEEE Fellow) at the Department of Computer Science & Engineering, The Chinese University of Hong Kong (CUHK). Before that, I obtained my bachelor’s degree (Advanced Class, GPA: 3.95/4.0) from the Department of Electronics and Information Engineering at Huazhong University of Science and Technology (HUST). I am interested in reinforcement learning and bandit theory and their algorithm design for various applications, such as web recommendation systems, video analytics, computer networks, and large language models. I am always open to possible collaborations. Please feel free to contact me.

(^* Equal Contribution)

Xiangxiang Dai^*, Zhiyong Wang^*, Jiancheng Ye, and John C.S. Lui. Quantifying the Merits of Network-Assist Online Learning in Optimizing Network Protocols. Accepted by the IEEE/ACM International Symposium on Quality of Service (IWQoS), 2024. (81/326 = 24.8%, CCF B)
Xiangxiang Dai, Peng Yang, Xinyu Zhang, Zhewei Dai, and Li Yu. RESPIRE: Reducing Spatial–Temporal Redundancy for Efficient Edge-Based Industrial Video Analytics. IEEE Transactions on Industrial Informatics (TII), vol. 18, no. 12, pp. 9324–9334, 2022. (SCI Q1)

2023-2027, CUHK Vice-Chancellor’s PhD Scholarship
(Only 30 PhD students in the whole university of CUHK)
2022, Pacemaker to Merit Student
(Highest honor in HUST, awarded to 20 students from all undergraduate grades, from National Scholarship recipients across the university, ≈0.07%)
2023, Honour Bachelor
(Highest honor for graduates in HUST on academic performance, 199/6500≈3%)
2022, National Scholarship
2023, Xiaomi Special First-Class Scholarship
(With an invitation to visit Xiaomi Headquarters)

Journal Reviewer: IEEE Transactions on Knowledge and Data Engineering (TKDE, CCF A), IEEE Internet of Things Journal (IoT, SCI Q1).