🤵🏻 About Me

I am a researcher with research interests in artificial intelligence and machine learning. I obtained my Ph.D. degree from Department of Computer Science and Technology in Nanjing University in June 2022, where I was very fortunate to be advised by professor Yu-Feng Li (李宇峰). Currently, I am an Assistant Professor in School of Intelligence Science and Technology, Nanjing University (Suzhou Campus). I am also a member of LAMDA Group (机器学习与数据挖掘研究所), which is led by professor Zhi-Hua Zhou (周志华).

The long-term research goal of our team is to make AI models more general (i.e., able to solve more tasks better). Most recently, the research mainly focuses on the pre-trained foundation model (LLM, VLM, etc.) and its adaptation to downstream tasks, following are some related research problems:

How to make AI models applicable to more tasks?

How to select appropriate pre-trained models to reuse for a specific task?
(Releated fields: Model Selection, Model Adaptation, Learnware, etc.)
How to adapt foundation models to specific tasks with limited data and labels?
(Related fields: Semi-Supervised Learning, Reinforcement Learning, Prompt Learning, etc.)
How to exploit general large models in conjunction with task-specific small models to solve more tasks?
(Related fields: Model Adaptation, Knowledge Distillation, Learnware, etc.)

How to make AI models adapt to more open environments?

How to make AI models adapt to the continuous changes in data distributions/classes/features in open environments?
(Related fields: Out-of Distribution Detection, Test-Time Adaptation, Class Incremental Learning, etc.)

📢: 招收对机器学习、人工智能感兴趣，有较好编程基础的学生，可通过邮箱guolz@nju.edu.cn联系我，请附上带普通生活照的个人简历、成绩单。
更多内容请见:招生说明.

🎉 News

2024.05: One Paper is accepted by KDD 2024!
2024.04: One Paper is accepted by ICML 2024!
2024.01: One Paper is accepted by ICLR 2024!
2023.12: CFP: We are organizing a "Robust Machine Learning in Open Environments" workshop in PAKDD 2024, Taipei, May 7, 2024
2023.12: One Paper is accepted by IEEE TVCG!
2023.11: One paper is accepted by Science China Information Science!
2023.05: We open-sourced a LLM for Chinese Legal domain LawGPT.⛏️ 🛠️
2022.07: We open-sourced the semi-supervised learning toolkit LAMDA-SSL.⛏️ 🛠️

📝 Publications

Conference Papers

DeCoOp: Robust Prompt Tuning with Out-of-Distribution Detection.
Zhi Zhou, Ming Yang, Jiang-Xin Shi, Lan-Zhe Guo^✉, Yu-Feng Li^✉.
In: Proceedings of the 41st International Conference on Machine Learning, Vienna, 2024.
ICML 2024. [Paper] [Webpage] [Code] [Poster]
Offline Imitation Learning with Model-based Reverse Augmentation.
Jie-Jing Shao, Hao-Sen Shi, Lan-Zhe Guo^✉, Yu-Feng Li^✉.
In: Proceedings of the 30th SIGKDD Conference on Knowledge Discovery and Data Mining, Barcelona, 2024.
KDD 2024. [Paper] [Webpage] [Code]
Realistic Evaluation of Semi-Supervised Learning Algorithms in Open Environments.
Lin-Han Jia, Lan-Zhe Guo^✉, Yu-Feng Li^✉.
In: Proceedings of the 12th International Conference on Learning Representations, Vienna, Austria, 2024.
ICLR 2024. [Paper] [Webpage] [Code]
You Only Submit One Image to Find the Most Suitable Generative Model.
Zhi Zhou, Lan-Zhe Guo, Peng-Xiao Song, Yu-Feng Li.
In: NeurIPS 2023 Diffusion Workshop.
NeurIPS 2023 Workshop. [Paper]
Identifying Useful Learnwares for Heterogeneous Label Spaces.
Lan-Zhe Guo, Zhi Zhou, Yu-Feng Li, Zhi-Hua Zhou.
In: Proceedings of the 40th International Conference on Machine Learning, Hawaii, 2023. Page: 12122-12131.
ICML 2023. [Paper]
Bidirectional Adaptation for Robust Semi-Supervised Learning with Inconsistent Data Distributions.
Lin-Han Jia, Lan-Zhe Guo, Zhi Zhou, Jie-Jing Shao, Yu-Ke Xiang, Yu-Feng Li.
In: Proceedings of the 40th International Conference on Machine Learning Hawaii, 2023. Page: 14886-14901.
ICML 2023. [Paper] [Code]
ODS: Test-Time Adaptation in the Presence of Open-World Data Shift.
Zhi Zhou, Lan-Zhe Guo, Lin-Han Jia, Ding-Chu Zhang, Yu-Feng Li.
In: Proceedings of the 40th International Conference on Machine Learning, Hawaii, 2023. Page: 42574-42588.
ICML 2023. [Paper] [Code] [Poster] [Video]
DualMatch: Robust Semi-Supervised Learning with Dual-Level Interaction.
Cong Wang, Xiao-Feng Cao, Lan-Zhe Guo, Zeng-Lin Shi.
In: Machine Learning and Knowledge Discovery in Databases: Research Track - European Conference, Turin, Italy, 2023. Page: 102--119. ECML/PKDD 2023. [Paper] [Code]
Robust Semi-Supervised Learning when Not All Classes have Labels.
Lan-Zhe Guo, Yi-Ge Zhang, Zhi-Fan Wu, Jie-Jing Shao, Yu-Feng Li.
In: Advances in Neural Information Processing Systems, New Orleans, LA, 2022. Page: 3305-3317.
NeurIPS 2022. [Paper] [Code]
LOG: Active Model Adaptation for Label-Efficient OOD Generalization.
Jie-Jing Shao, Lan-Zhe Guo, Xiao-Wen Yang, Yu-Feng Li.
In: Advances in Neural Information Processing Systems, New Orleans, LA, 2022. Page: 11023-11034.
NeurIPS 2022. [Paper] [Code]
USB: A Unified Semi-Supervised Learning Benchmark for Classification.
Yi-Dong Wang, Hao Chen, Yue Fan, Wang Sun, Ran Tao, Wen-Xin Hou, Ren-Jie Wang, Lin-Yi Yang, Zhi Zhou, Lan-Zhe Guo, He-Li Qi, Zhen Wu, Yu-Feng Li, Satoshi Nakamura, Wei Ye, Marios Savvides, Bhiksha Raj, Takahiro Shinozaki, Bernt Schiele, Jin-Dong Wang, Xing Xie, Yue Zhang.
In: Advances in Neural Information Processing Systems Datasets and Benchmarks, New Orleans, LA, 2022. Page: 3938-3961.
NeurIPS 2022 Datasets and Benchmarks. [Paper] [Code]
Class-Imbalanced Semi-Supervised Learning with Adaptive Thresholding.
Lan-Zhe Guo, Yu-Feng Li.
In: Proceedings of the 39th International Conference on Machine Learning, Baltimore, Maryland, 2022. Page: 8082-8094.
ICML 2022. [Paper] [Code]
STEP: Out-of-Distribution Detection in the Presence of Limited In-Distribution Labeled Data.
Zhi Zhou, Lan-Zhe Guo (co-first author), Zhan-Zhan Cheng, Yu-Feng Li, Shi-Liang Pu.
In: Advances in Neural Information Processing Systems, Virtual Conference, 2021. Page: 29168-29180.
NeurIPS 2021. [Paper] [Code] [Poster]
Learning from Imbalanced and Incomplete Supervision with Its Application to Ride-Sharing Liability Judgment.
Lan-Zhe Guo, Zhi Zhou, Jie-Jing Shao, Yu-Feng Li, and DiDi Collaborators.
In: Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Singapore, 2021. Page: 487-495.
KDD 2021. [Paper]
Safe Deep Semi-Supervised Learning for Unseen-Class Unlabeled Data.
Lan-Zhe Guo, Zhen-Yu Zhang, Yuan Jiang, Yu-Feng Li, Zhi-Hua Zhou.
In: Proceedings of the 37th International Conference on Machine Learning, Vienna, Austria, 2020. Page: 3897-3906.
ICML 2022. [Paper] [Code]
RECORD: Resource Constrained Semi-Supervised Learning under Distribution Shift.
Lan-Zhe Guo, Zhi Zhou, Yu-Feng Li.
In: Proceedings of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, San Diego, CA, 2020. Page: 1636-1644.
KDD 2020. [Paper] [Code]
Weakly Supervised Learning Meets Ride-Sharing User Experience Enhancement.
Lan-Zhe Guo, Feng Kuang, Zhang-Xun Liu, Yu-Feng Li, Nan Ma, Xiao-Hu Qie.
In: Proceedings of the 34rd AAAI conference on Artificial Intelligence, New York, NY, 2020. Page: 4052-4059.
AAAI 2020. [Paper]
Robust Semi-Supervised Representation Learning for Graph-Structublue Data.
Lan-Zhe Guo, Tao Han, Yu-Feng Li.
In: Proceedings of the 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining, Macau, China. 2019. Page: 131--143.
PAKDD 2019. [Paper]
A General Formulation for Safely Exploiting Weakly Supervised Data.
Lan-Zhe Guo, Yu-Feng Li.
In: Proceedings of the 32nd AAAI conference on Artificial Intelligence, New Orleans, LA, 2018. Page: 3126-3133.
AAAI 2018. [Paper]
Large Margin Graph Construction for Semi-Supervised Learning.
Lan-Zhe Guo, Shao-Bo Wang, Yu-Feng Li.
In: 2018 IEEE International Conference on Data Mining Workshops, Singapore, 2018. Page: 1030-1033.
ICDM 2018. [Paper]

Journal Papers

Interactive Reweighting for Mitigating Label Quality Issues.
Wei-Kai Yang, Yu-Kai Guo, Jing Wu, Zheng Wang, Lan-Zhe Guo, Yu-Feng Li, Shixia Liu.
IEEE Transactions on Visualization and Computer Graphics, 30(3):1837-1852, 2024.
TVCG 2024. [Paper]
LAMDA-SSL: A Comprehensive Semi-Supervised Learning Toolkit.
Lin-Han Jia, Lan-Zhe Guo^✉, Zhi Zhou, Yu-Feng Li^✉.
SCIENCE CHINA Information Sciences, 67:117101, 2024.
SCIS 2024. [Paper] [Code]
稳健选择伪标注的混合式半监督学习.
Lan-Zhe Guo, Yu-Feng Li.
中国科学：信息科学, 54(3):623–637, 2024.
中国科学：信息科学, 2024. [Paper]
Open-Set Learning under Covariate Shift.
Jie-Jing Shao, Xiao-Wen Wang, Lan-Zhe Guo^✉.
Machine Learning, 113(4):1643-1659, 2024.
MLJ 2024. [Paper]
Transfer and Share: Semi-Supervised Learning from Long-Tailed Data.
Tong-Wei, Qian-Yu Liu, Jiang-Xin Shi, Wei-Wei Tu, Lan-Zhe Guo^✉.
Machine Learning, 113(4):1725-1742, 2024.
MLJ 2024. [Paper] [Code]
Towards Safe Weakly Supervised Learning.
Yu-Feng Li, Lan-Zhe Guo (co-first author), Zhi-Hua Zhou.
IEEE Transactions on Pattern Analysis and Machine Intelligence, 43(1): 334-346, 2021.
TPAMI 2021. [Paper]
Interactive Graph Construction for Graph-Based Semi-Supervised Learning.
Chang-Jian Chen, Zhao-Wei Wang, Jing Wu, Xi-Ting Wang, Lan-Zhe Guo, Yu-Feng Li, Shi-Xia Liu.
IEEE Transactions on Visualization and Computer Graphics (TVCG), 27(9): 3701-3716, 2021.
TVCG 2021. [Paper]
Learning From Group Supervision: The Impact of Supervision Deficiency on Multi-Label Learning.
Miao Xu, Lan-Zhe Guo^✉.
Science China Information Science, 64(3): 1-13, 2021.
SCIS 2021. [Paper]
Learning Safe Multi-Label Pblueiction for Weakly Labeled Data.
Tong Wei, Lan-Zhe Guo, Yu-Feng Li, Wei Gao.
Machine Learning, 107(4): 703-725, 2018.
MLJ 2021. [Paper]

Manuscript

LawGPT: A Chinese Legal Knowledge-Enhanced Large Language Model.
Zhi Zhou, Jiang-Xin Shi, Peng-Xiao Song, Xiao-Wen Yang, Yi-Xuan Jin, Lan-Zhe Guo, Yu-Feng Li.
[Paper] [Webpage]

Thesis

Semi-Supervised Learning for Open Environment.

💻 Software

LAMDA-SSL: A comprehensive and easy-to-use toolkit for semi-supervised learning. LAMDA-SSL contains 30+ semi-supervised learning algorithms, including both statiscal and deep semi-supervised learning. We hope this toolkit can promote the research of semi-supervised learning.
[Tutorial][Github]
LawGPT: A Large Language Model in the Legal Domain.
[Github]

🏆 Awards

吴文俊人工智能科学技术奖优秀博士学位论文，人工智能学会，2023
Excellent Doctoral Dissertation Award, Computer Science and Technology, Nanjing University, 2022
Baidu Scholarship (全球华人博士生共10人), Baidu Inc, 2021
Tecent Scholarship, Nanjing University, 2021
MSRA Fellowship Nomination Award, 2021
Outstanding Contribution Award of Huawei-LAMDA Artificial Intelligence Joint Laboratory, 2021
National Scholarship for Ph.D. Students, Nanjing University, 2020
GuoRui Scholarship, 2019
National Scholarship for Master Students, Nanjing University, 2018
ACM-ICPC Asia Regional Contest, Gold Medal: Shenyang Site, 2015
ACM-ICPC Asia Regional Contest, Sliver Medal: Mudanjiang Site, 2014
ACM-ICPC Asia Regional Contest, Sliver Medal: AnShan Site, 2014
ACM-ICPC Asia Regional Contest, Sliver Medal: BeiJing Site, 2015
The 2015 China Collegiate Programming Contest, Sliver Medal
Northeast Collegiate Programming Contest, Second Place, 2015
CodeCup 2015: Gold Medal
ACM-ICPC China Provincial Programming Contest, Gold Medal, Jilin, 2014

📖 Educations

2019.09 - 2022.06, Ph.D., Computer Science and Technology, Nanjing University, Nanjing.
2017.09 - 2019.07, Master, Computer Science and Technology, Nanjing University, Nanjing.
2013.09 - 2017.07, Undergraduate, School of Software, Jilin University, Jilin.

📚 Teaching

人工智能导论（Introduction to Artificial Intelligence） For undergraduate students, Fall 2023.
高级机器学习（Advanced Machine Learning） For graduate students, Fall 2023.

🎈 Students

Graduate Students

Hao-Zhe Tan, 2023--
Zi-Kang Wang, 2023--
Song-Lin Lv, 2024--
Tian-Chi Ma, 2024--
Zi-Jian Cheng, 2024--

🤝 Activities

Conference Committee

Senior Program Committee Member, IJCAI 2021.
Senior Program Committee Member, ACML 2021/2022.
Program Committee Member, NeurIPS 2020--
Program Committee Member, ICML 2020--
Program Committee Member, ICLR 2021--
Program Committee Member, KDD 2020--
Program Committee Member, IJCAI 2020--
Program Committee Member, AAAI 2019--
Program Committee Member, ECML 2023--
Program Committee Member, UAI 2023--
Program Committee Member, ECAI 2024--

Journal Reviewer

Reviewer for IEEE TPAMI, IEEE TKDE, IEEE TSMCS, Artificial Intelligence, Machine Learning, Neural Networks, Pattern Recognition,etc.

Organization Committee

Vice Program Chair of LAMDA-RIKEN Joint Workshop on Machine Learning, 2024.
Organizer of PAKDD Workshop on Robust Machine in Open Environments, May, 2024, Taipei, China.
Organization committee member of MLA 2022.
Workflow chair of CCML 2021.
Workflow chair of ACML 2021/2022.
Assist in the organization of PAKDD Workshop on Weakly Supervised Learning, Apr. 2019, Macau, China.

Lan-Zhe Guo

郭兰哲