About Me
"The powerful play goes on...
And you may contribute a verse."
And you may contribute a verse."
Hi, this is Yue Lin (/ˈjuːeɪ lɪn/, or 林越 in Chinese), and welcome to my personal website. Currently I am a Ph.D. student (data science program) in School of Data Science at The Chinese University of Hong Kong, Shenzhen, fortunately advised by Prof. Baoxiang Wang [Homepage] and Prof. Hongyuan Zha [Google Scholar]. Here, I will irregularly update my experiences, notes, and computational magic spells that interest me.
My current research interest lies in using computational methods to study mechanisms, to address some social dilemma issues in game theory, in which scenarios everyone being self-interested may lead to the detriment of social welfare. [Click here to see details of my research interests]
- The method I use is Multi-Agent Reinforcement Learning (MARL), essentially with the rationality assumption. And I have recently started working with some tools that seem more "human-like", like large language models.
- Specifically I am focusing on the problem of Bayesian persuasion (BP, [my blog]) in economics: a sender with an informational advantage tries to persuade a receiver, who has different motives, to take actions that are beneficial to the sender. My research is on sequential decision-making situations.
- A representative work on this is this [my blog] (NeurIPS), where we proposed a general model-free RL algorithm for multi-agent communication (for the cognoscenti: policy gradient for communication), and expanded the constraints in BP so that mixed-motive communication (even between two agents) in MARL is conceivable.
- During my undergraduate years (specifically, from 2019 to 2021), I dabbled in robotics, understood kinematics, and played a bit with dynamics [my repo].
- I presented a purely simulation-based robotic mechanism design work [my blog] at ICRA. It is about a hybrid leg can transform into various forms (wheel, legs, RHex) to adapt to different terrains, and can even climb ladders.
- Also I have implemented [my blog] a "gimbal" using a hyper-redundant manipulator (purely based on kinematics), allowing it to efficiently reach into barrels.
And how could one endure being a man, if not also for the possibility to create, guess riddles, and redeem accidents? To redeem those who lived in the past and to recreate all "it was" into "thus I willed it" — that alone should I call redemption. — Friedrich Nietzsche, Thus Spoke Zarathustra.
Research Interests
Currently
- Multi-Agent RL: Mixed-Motive Tasks
- Game Theory: Information Design
- Large Language Models
- Psychology: Personality
Formerly
- Redundant Manipulator Control
- Robotic Mechanism Design
Education & Experience
Education
- The Chinese University of Hong Kong, Shenzhen
Ph.D. Student in Data Science (2024.8 - Present) - Tiangong University
Bachelor of Engineering in Computer Science and Technology (2018.9 - 2022.6)- School of Computer Science and Technology (2019.9 - 2022.6)
GPA: 3.89 / 4 (92.22 / 100); Rank: 1 / 127
[Certification] - School of Mechanical Engineering (2018.9 - 2019.6)
GPA: 3.90 / 4 (92.00 / 100); Rank: 1 / 60
- School of Computer Science and Technology (2019.9 - 2022.6)
Experience
- The Chinese University of Hong Kong, Shenzhen
Research Assistant in School of Data Science (2022.2 - Present)
Selected Publications
Data Science
- Information Design in Multi-Agent Reinforcement Learning.
Yue Lin, Wenhao Li, Hongyuan Zha, Baoxiang Wang.
Neural Information Processing Systems (NeurIPS) 2023.Poster. This is currently my most representative work.
[Paper] [Code] [Experiments] [Blog en] [Blog cn] [Zhihu cn] [Slides] [Talk en] [Talk RLChina]
Robotics
- Innovative Design and Simulation of a Transformable Robot with Flexibility and Versatility, RHex-T3.
Yue Lin, Yujia Tian, Yongjiang Xue, Shujun Han, Huaiyu Zhang, Wenxin Lai, Xuan Xiao.
International Conference on Robotics and Automation (ICRA) 2021.Oral. Delivered a presentation at the Xi’an conference venue.
[Paper] [Blog] [Demo Videos] - A snake-inspired path planning algorithm based on reinforcement learning and self-motion for hyper-redundant manipulators.
Yue Lin, Jianming Wang, Xuan Xiao, Ji Qu, Fatao Qin.
International Journal of Advanced Robotic Systems (IJARS) 2022.
Professional Services
Served as an independent reviewer for
- NeurIPS 2024
- ICLR 2025
Contact
| Types | ID |
|---|---|
| linyue3h1@gmail.com | |
| R01SVP | |
| GitHub | github.com/YueLin301 |
| Google Scholar | Yue Lin |
| Zhihu | R01SVP |
| Bilibili | 不梦眠 |
This post is licensed under CC BY 4.0 by the author.