Jingwang Li

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PhD Student, Department of Electronic & Computer Engineering
The Hong Kong University of Science & Technology
Hong Kong, China

Email: jingwang.li [at] connect.ust.hk
Links: Google Scholar | Github

About

I am currently a PhD student at the Hong Kong University of Science & Technology, advised by Prof. Vincent Lau.

Previously, I received a BMgmt in Engineering Management from Huazhong Agricultural University and an MEng in Control Science & Engineering under the supervision of Prof. Housheng Su from Huazhong University of Science & Technology. After that, I worked as an algorithm engineer at FABU.AI, engaging in modeling and solving optimization problems related to autonomous driving. Upon deciding to pursue a PhD, I resigned and went to the Chinese University of Hong Kong, Shenzhen as a research assistant, where I worked on accelerated decentralized optimization under the mentorship of Prof. Xiao Li. See my CV for more detailed information.

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Research Interests

My research interests primarily focus on algorithm design and convergence analysis in decentralized optimization. Currently, I am particularly interested in a specific class of decentralized optimization problems involving globally coupled constraints:

minxi∈Rdi,y∈Rp n∑i=1(fi(xi)+gi(xi))+h(y)s.t. n∑i=1Aixi=y,

where fi:Rdi→R is a convex and smooth function, gi:Rdi→R∪{+∞} and h:Rp→R∪{+∞} are convex but possibly nonsmooth functions, and Ai∈Rp×di is a matrix, i=1,⋯,n. Under the decentralized setting, we need to solve (1) over a networked system consisting of n agents, where the underlying network topology can be represented by an undirected or directed graph. Particularly, fi, gi, and Ai are private information of agent i, while h is public for all agents. The problem (1) captures a wide range of real-world scientific and engineering problems, including decentralized control, decentralized vertical federated learning, decentralized resource allocation, and more, which is why it appeals to me so much.

Publications

* indicates the corresponding author.

Preprints

  1. Jingwang Li and Housheng Su*. “Decentralized constraint-coupled optimization with inexact oracle”, arXiv:2309.06330, 2023. [arXiv]

  2. Jingwang Li and Housheng Su*. “Gradient tracking: A unified approach to smooth distributed optimization”, arXiv:2202.09804, 2022. [arXiv]

Journal Articles

  1. Jingwang Li and Housheng Su*. “NPGA: A unified algorithmic framework for decentralized constraint-coupled optimization”, IEEE Transactions on Control of Network Systems, 2024. [DOI] [arXiv]

  2. Jingwang Li, Qing An and Housheng Su*. “Proximal nested primal-dual gradient algorithms for distributed constraint-coupled composite optimization”, Applied Mathematics and Computation, 2023. [DOI]

  3. Jingwang Li and Housheng Su*. “Implicit tracking-based distributed constraint-coupled optimization”, IEEE Transactions on Control of Network Systems, 2022. [DOI] [arXiv]

Conference Proceedings

  1. Bingxi Jia*, Haidong Ren, Zheng Yang, Jingwang Li and Xiaofei He. “Cascaded motion estimation for intelligent vehicles in GNSS-denied scenes”, Chinese Control Conference, 2023. [DOI]

  2. Jingwang Li, Suoxia Miao and Housheng Su*. “Distributed primal-dual mirror dynamics for constraint-coupled optimization”, International Conference on Guidance, Navigation and Control, 2022. [DOI]

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