Hello, this is Weixin Bu (Also, Bryson), an ordinary but curious person.
I work at REVERSIBLE INC as a [Search and Recommendation Engineer]. I am now working on the pipeline construction, performance optimization and multimodal implementation of the search and recommendation systems. Additionally, I am exploring innovative applications of LLMs for automated code bug fix, while also working on advanced image generation technologies.
I graduated from School of Computer and Software, Nanjing University of Information Science and Technology (南京信息工程大学计算机与软件学院) with a bachelor’s degree; and from School of Artificial Intelligence, Jilin University (吉林大学人工智能学院) with a master’s degree.
I am passionate about researching on Artificial Intelligence and Software Development. My research interests include Graph Neural Networks (GNNs), Self/Semi-supervised Learning, Multimodal Learning, and Large Foundation Models, etc.
🔥 News
- 2025.05: 🎉 One paper Nonparametric Teaching for Graph Property Learners accepted by ICML 2025!
- 2024.11: 🎉 I join REVERSIBLE INC as a [Search and Recommendation Engineer]!
📝 Publications
Graph Neural Networks

Improving Augmentation Consistency for Graph Contrastive Learning
Weixin Bu*
, Xiaofeng Cao*
, Yizhen Zheng, Shirui Pan
[Paper
] | [Code
]
- A novel augmentation consistency perspective in GCL
- Integrate semantic and structural properties to better capture node consistency
- An effective consistency improvement loss to maintain augmentation consistency among positive node pairs

Nonparametric Teaching for Graph Property Learners
Chen Zhang*
, Weixin Bu*
, Zeyi Ren, Zhengwu Liu, Yik-Chung Wu, Ngai Wong
[Project
] | [Code
]
- A novel paradigm that interprets graph property learning within the theoretical context of nonparametric teaching (NT)
- Reveal the consistency between the evolution of GCN driven by parameter updates and that under functional gradient descent in NT
- Demonstrate the effectiveness of GraNT through extensive experiments (graph/node-level regression / classification) in graph property learning
Self/Semi-supervised Learning
Multimodal Learning
Large Foundation Models
Others
📖 Educations
- 2021.09 - 2024.06, Computer Science, Msc, Jilin University, Changchun.
- 2014.09 - 2018.06, Network Engineering, Bsc, Nanjing University of Information Science and Technology, Nanjing.
💻 Work and Internships
- 2024.11 - now, Search and Recommendation Engineer in REVERSIBLE INC, Remote.
- 2024.06 - 2024.09, AI Researcher in NGAI of CAICT, Nanjing.
- 2022.07 - 2022.10, Algorithm Software Intern in Shanghai AI Lab, Remote.
- 2021.01 - 2021.06, Software Engineer(Part-time) in Beyond APP, Shanghai.
- 2018.07 - 2020.05, Software Engineer(Full-time) in Beyond APP, Shanghai.