Weisen JIANG 江伟森
Professor 教授
School of Future Technology 未来技术学院
South China University of Technology 华南理工大学
🎯 Join Us 招生信息
- 每年招收博士生 2 名、硕士生 2–4 名，长期招收博士后与科研助理。
- 欢迎对大模型、深度学习及 AI4Science 感兴趣的同学联系。
- 华南理工大学大三、大四同学如对科研感兴趣，也欢迎联系。
- 联系邮箱：waysonkong@gmail.com
- 来信请按
[Research Position] 姓名-学校-研究兴趣的格式拟定邮件主题，例如：[Research Position] 李明-华南理工大学-大模型后训练。
🧑💻 About Me 关于我
Weisen Jiang is a Professor and Ph.D. supervisor in the School of Future Technology at South China
University of Technology, and a recipient of China's National High-Level Young Talent Program.
His research focuses on Large Models, Deep Learning, and AI4Science, with over twenty publications
at top-tier venues including NeurIPS, ICML, ICLR, and TPAMI. He serves as Area Chair for leading AI
conferences such as ICLR and NeurIPS. His work on knowledge augmentation for large models (ICLR
2024 & ACL 2024, 1400+ citations) has been applied and validated by leading organizations such
as DeepSeek and Qwen.
He received his Ph.D. from the Hong Kong University of Science and Technology and was a Researcher
at the Chinese University of Hong Kong; earlier, he worked as a Researcher on recommendation and
ranking systems at Tencent and Meituan. He maintains ongoing research collaborations with Tencent,
Meituan, and other technology companies, and can recommend students for internships there.
江伟森，华南理工大学未来技术学院教授，博士生导师，国家级高层次青年人才。研究聚焦于大模型、深度学习与 AI4Science，在
NeurIPS、ICML、ICLR、TPAMI 等顶会顶刊发表论文二十余篇，并担任 ICLR、NeurIPS 等顶级 AI 会议的领域主席（Area Chair）。提出的大模型知识增强技术（ICLR
2024 & ACL 2024，引用 1400+）被 DeepSeek、Qwen
等知名机构应用验证。他于香港科技大学获得博士学位，曾任香港中文大学研究员，此前曾在腾讯和美团担任推荐和排序系统的研究员；长期与腾讯、美团等互联网企业保持科研合作，可推荐学生前往上述企业实习。
🔬 Research Directions 研究方向
Large Models 大模型
LLMs 大语言模型
Multimodal LLMs 多模态大语言模型
Generative Models 生成模型
Mamba
Deep Learning 深度学习
Meta-Learning 元学习
Multi-Task Learning 多任务学习
Multi-Objective Learning 多目标学习
Transfer Learning 迁移学习
AI4Science 科学智能
Biology 生物
Healthcare 医疗健康
🔥 News 最新消息
- 2026 Aug Career Joined the School of Future Technology at South China University of Technology as a Professor.
- 2026 Aug Service Serving as Area Chair for ICLR 2027.
- 2026 May ICML'26 Two papers (MetaMoE and SPARD) on LLMs are accepted by ICML 2026.
- 2025 Nov NeurIPS'25 Our paper MetaDefense on LLMs is accepted by NeurIPS 2025.
- 2025 Aug Service Serving as Area Chair for ICLR 2026.
- 2025 Jul TPAMI'25 MTMamba++ about applying Mamaba to deep learning is accepted by IEEE TPAMI 2025.
- 2025 May ICML'25 PARM on LLMs is accepted by ICML 2025.
- 2025 Apr NN'25 DCDM on generative models is accepted by Neural Networks.
- 2024 Sep NeurIPS'24 Two papers (RouterDC and GITA) on LLMs and MLLMs are accepted by NeurIPS 2024.
- 2024 Jul PhD Defended my Ph.D. thesis at HKUST.
- 2024 Jul ECCV'24 Two papers (MTMamba and MEHL-Soup) about Mamba and MLLMs are accepted by ECCV 2024.
- 2024 May ECML'24 LETS-SAM on deep learning is accepted by ECML 2024.
- 2024 May ACL'24 FOBAR on LLMs is accepted by ACL 2024 Findings.
- 2024 Jan ICLR'24 MetaMath on LLMs is accepted by ICLR 2024 (Spotlight).
- 2023 Apr ICML'23 MetaPrompter on LLMs is accepted by ICML 2023.
- 2023 Jan ICLR'23 AE-SAM on deep learning is accepted by ICLR 2023.
- 2022 May ICML'22 MUSML on deep learning is accepted by ICML 2022.
- 2021 Sep NeurIPS'21 MetaProx on deep learning is accepted by NeurIPS 2021.
📚 Working & Education 工作与教育
💼 Working 工作经历
-
2026 –Professor 教授South China University of Technology 华南理工大学
-
2024 – 2026Researcher 研究员Chinese University of Hong Kong 香港中文大学
-
2017 – 2019Research Scientist 研究科学家Tencent 腾讯
-
2015 – 2017Engineer 工程师Meituan 美团
🎓 Education 教育经历
-
2020 – 2024Ph.D. in Computer Science 计算机科学博士Hong Kong University of Science and Technology 香港科技大学
-
2012 – 2015M.Sc. in Operations Research 运筹学与控制论硕士University of Chinese Academy of Sciences
中国科学院大学 -
2008 – 2012B.Eng. in Automation 自动化学士South China University of Technology 华南理工大学
📄 Publications & Patents 论文与专利
Publications 论文
(♠ equal contribution 共同一作 · corresponding author 通讯作者)
MetaMoE: Diversity-Aware Proxy Selection for
Privacy-Preserving Mixture-of-Experts Unification
Weisen Jiang, Shuhao Chen, Sinno Jialin Pan
ICML 2026 Code CCF-A
SPARD: Defending Harmful Fine-Tuning Attack via Safety
Projection with Relevance–Diversity Data Selection
Shuhao Chen, Weisen Jiang, Y. Gong, S. Luo, C. Zhuo, Z. Li, James Kwok, Yu
Zhang
ICML 2026 CCF-A
Dual-Balancing
for Multi-Task Learning
Baijiong Lin, Weisen Jiang, P. Chen, F. Ye, Yu Zhang, Y. Chen, S. Liu, Ivor W.
Tsang, James T. Kwok
Neural Networks 2026 JCR Q1
MetaDefense: Defending Fine-tuning based Jailbreak Attack
Before and During Generation
Weisen Jiang, Sinno Jialin Pan
NeurIPS 2025 Code CCF-A
MTMamba++: Enhancing Multi-Task Dense Scene Understanding
via Mamba-Based Decoders
Baijiong Lin, Weisen Jiang, Pengguang Chen, Shu Liu, Ying-Cong Chen
IEEE TPAMI 2025 CCF-A JCR Q1
PARM: Multi-Objective Test-Time Alignment via
Preference-Aware Autoregressive Reward Model
Baijiong Lin, Weisen Jiang, Yuancheng Xu, Hao Chen, Ying-Cong Chen
ICML 2025 CCF-A
Domain-Guided Conditional Diffusion Model for Unsupervised
Domain Adaptation
Yulong Zhang, Shuhao Chen, Weisen Jiang, Yu Zhang, Jiangang Lu, James Kwok
Neural Networks 2025 JCR Q1
RouterDC: Query-Based Router by Dual Contrastive Learning
for Assembling Large Language Models
Shuhao Chen♠, Weisen Jiang♠, Baijiong Lin, James T.
Kwok, Yu Zhang
NeurIPS 2024 CCF-A
GITA: Graph to Visual and Textual Integration for
Vision-Language Graph Reasoning
Yanbin Wei, Shuai Fu, Weisen Jiang, Zejian Zhang, Zhixiong Zeng, Qi Wu, James
T. Kwok, Yu Zhang
NeurIPS 2024 CCF-A
MTMamba: Enhancing Multi-Task Dense Scene Understanding by
Mamba-Based Decoders
Baijiong Lin, Weisen Jiang, Pengguang Chen, Yu Zhang, Shu Liu, Ying-Cong
Chen
ECCV 2024
Learning Scalable Model Soup on a Single GPU: An Efficient
Subspace Training Strategy
Tao Li♠, Weisen Jiang♠, Fanghui Liu, Xiaolin Huang,
James Kwok
ECCV 2024
Forward-Backward Reasoning in Large Language Models for
Mathematical Verification
Weisen Jiang, Han Shi, Longhui Yu, Zhengying Liu, Yu Zhang, Zhenguo Li, James
Kwok
ACL 2024 Findings
MetaMath: Bootstrap Your Own Mathematical Questions for
Large Language Models
Longhui Yu♠, Weisen Jiang♠, Han Shi, J. Yu, Z. Liu, Yu
Zhang, James Kwok, Zhenguo Li, A. Weller, Weiyang Liu
ICLR 2024 Spotlight (5%)
CCF-A
Enhancing Sharpness-Aware Minimization by Learning
Perturbation Radius
Xuehao Wang♠, Weisen Jiang♠, Shuai Fu, Yu Zhang
ECML 2024
Effective Structured Prompting by Meta-Learning and
Representative Verbalizer
Weisen Jiang, Yu Zhang, James Kwok
ICML 2023 Code
CCF-A
An Adaptive Policy to Employ Sharpness-Aware
Minimization
Weisen Jiang, Hansi Yang, Yu Zhang, James Kwok
ICLR 2023 Code
CCF-A
Subspace Learning for Effective Meta-Learning
Weisen Jiang, Yu Zhang, James Kwok
ICML 2022 COde CCF-A
Effective Meta-Regularization by Kernelized Proximal
Regularization
Weisen Jiang, James Kwok, Yu Zhang
NeurIPS 2021 Code
CCF-A
SEEN: Few-Shot Classification with
SElf-ENsemble
Weisen Jiang, James Kwok, Yu Zhang
IJCNN 2021
Identification for Wiener System with Discontinuous
Piece-wise Linear Function via Sparse Optimization
Weisen Jiang, Hai-Tao Fang
CCC 2014
Patents 专利
信息推荐方法、装置、系统及存储介质
江伟森, 吴德龙, 邱泰生
腾讯, 授权号: CN110413868B (2023)
一种页面生成方法及装置
江伟森, 骆顺昌, 吴德龙, 邱泰生
腾讯, 公开号: CN112307319A (2021)
🏆 Awards & Services 奖项与服务
Awards 奖项
- 中华人民共和国教育部 国家奖学金（前 2%，两次）
- 腾讯 五星优秀员工（前 10%，两次）
- 深圳市第三届优秀科技学术论文（2023）
Academic Services 学术服务
- Area Chair / Senior PC: ICLR, NeurIPS, IJCAI
- Reviewer / PC Member: ICML, NeurIPS, ICLR, CVPR, ICCV, AAAI, KDD, AISTATS
- Journal Reviewer: TPAMI, TNNLS, TBD, AIJ, JMLR, TMLR, Neural Networks, International Journal of Data Science and Analytics
🧑🏫 Teaching 教学
- COMP 2012 — Object-Oriented Programming and Data Structures, Teaching Assistant, HKUST
- COMP 4331 — Data Mining, Teaching Assistant, HKUST