News
20 Jun. 2025
Two full papers are accepted by WWW'25 on LLM-based recommendation and graph generalization.
17 Nov. 2024
One full paper is accepted by KDD'25 on graph OOD generalization.
23 Jun. 2024
Four full papers are accepted by WWW'24 on invariant graph learning, KG-recommendation, graph condensation and graph anomaly detection.
30 Nov. 2023
One full paper is accepted by ICDE'24 on graph contrastive learning.
20 Oct. 2023
One full paper is accepted by WSDM'24 on efficient recommendation.
22 Sep. 2023
One full paper is accepted by NeurIPS'23 on graph OOD generalization.
25 Jan. 2023
One full paper is accepted by WWW'23 on graph unlearning.
19 May 2022
One full paper is accepted by KDD'22 on graph OOD generalization.
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Yongduo Sui
PhD student
Lab of Data Science 443 Huangshan Road, Hefei, China 230027
Advisor: Xiangnan He and Xiang Wang
Email: syd2019 AT mail.ustc.edu.cn
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I am currently a Senior Researcher at Tencent, having recently completed my PhD at the Lab for Data Science, University of Science and Technology of China (USTC), under the supervision of Prof. Xiangnan He and Prof. Xiang Wang. My research interests lie in Large Language Models (LLM), Agent-based systems, Graph Learning, and Recommendation Systems. During my PhD, I focused on Out-of-distribution Generalization, Self-supervised Learning, Causal Inference, and Efficient Machine Learning, with a particular emphasis on Graph Learning and Recommendation Systems.
Education
| University of Science and Techonology of China (USTC) PhD student in Computer Science Sep 2021 - June 2024, Hefei Advisor: Prof. Xiangnan He and Prof. Xiang Wang |
| University of Science and Techonology of China (USTC) Master in Computer Science Sep 2019 - June 2021, Hefei Advisor: Prof. Bin Li |
| Harbin Engineering University (HEU) Bachelor in Electrical Engineering Sep 2015 - June 2019, Harbin |
Experiences
| Research Intern, Ant Group, Hangzhou, March 2023 - June 2024 Mentor: Jun Zhou, Longfei Li, and Qing Cui |
Publications
In the Year of 2025: |
Unleashing the Power of Large Language Model for Denoising Recommendation Shuyao Wang, Zhi Zheng, Yongduo Sui, Hui Xiong WWW 2025 (Full, Oral, Accept rate: 19.8%) |
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Grasp the Key Takeaways from Source Domain for Few Shot Graph Domain Adaptation Xiangwei Lv, Jingyuan Chen, Mengze Li, Yongduo Sui, Zemin Liu, Beishui Liao WWW 2025 (Full, Accept rate: 19.8%) |
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A Unified Invariant Learning Framework for Graph Classification Yongduo Sui, Jie Sun, Shuyao Wang, Zemin Liu, Qing Cui, Longfei Li, Xiang Wang KDD 2025 (Full, Accept rate: 19%) |
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A Simple Data Augmentation for Graph Classification: A Perspective of Equivariance and Invariance
Yongduo Sui, Shuyao Wang, Jie Sun,Zhiyuan Liu,Qing Cui,Longfei Li, Jun Zhou, Xiang Wang, Xiangnan He TKDD 2024 (ACM Transactions on Knowledge Discovery from Data) |
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Two Heads Are Better Than One: Boosting Graph Sparse Training via Semantic and Topological Awareness Guibin Zhang, Yanwei Yue, Kun Wang, Junfeng Fang, Yongduo Sui, Kai Wang, Yuxuan Liang, Dawei Cheng, Shirui Pan, Tianlong Chen ICML 2024 (Full, Accept rate: 22%) |
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Invariant Graph Learning for Causal Effect Estimation Yongduo Sui, Caizhi Tang,Zhixuan Chu,Junfeng Fang,Yuan Gao,Qing Cui,Longfei Li,Jun Zhou, Xiang Wang WWW 2024 (Full, Accept rate: 20.2%) |
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Unleashing the Power of Knowledge Graph for Recommendation via Invariant Learning Shuyao Wang, Yongduo Sui, Chao Wang, Hui Xiong WWW 2024 (Full, Accept rate: 20.2%) |
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EXGC: Bridging Efficiency and Explainability in Graph Condensation Junfeng Fang, Xinglin Li, Yongduo Sui, Yuan Gao, Guibin Zhang, Kun Wang, Xiang Wang, Xiangnan He WWW 2024 (Full, Accept rate: 20.2%) |
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Graph Anomaly Detection with Bi-level Optimization Yuan Gao, Junfeng Fang, Yongduo Sui, Yangyang Li, Xiang Wang, HuaMin Feng, Yongdong Zhang WWW 2024 (Full, Accept rate: 20.2%) |
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Masked Graph Modeling with Multi-View Contrast Yanchen Luo, Sihang Li, Yongduo Sui, Junkang Wu, Jiancan Wu, Xiang Wang, Xiangnan He ICDE 2024 (Full) |
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Dynamic Sparse Learning: A Novel Paradigm for Efficient Recommendation Shuyao Wang, Yongduo Sui, Jiancan Wu, Zhi Zheng, Hui Xiong WSDM 2024 (Full, Accept rate: 18%) |
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Enhancing Out-of-distribution Generalization on Graphs via Causal Attention Learning
Yongduo Sui, Wenyu Mao, Shuyao Wang, Xiang Wang, Jiancan Wu, Xiangnan He, Tat-Seng Chua TKDD 2024 (ACM Transactions on Knowledge Discovery from Data) [PDF] [Codes] |
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Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift Yongduo Sui, Qitian Wu, Jiancan Wu, Qing Cui, Longfei Li, Jun Zhou, Xiang Wang, Xiangnan He NeurIPS 2023 (Full, Accept rate: 26.1%) [PDF] [Codes] |
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Inductive Lottery Ticket Learning for Graph Neural Networks
Yongduo Sui, Xiang Wang, Tianlong Chen, Meng Wang, Xiangnan He, Tat-Seng Chua JCST 2023 (Journal of Computer Science and Technology) [PDF] [Codes] |
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GIF: A General Graph Unlearning Strategy via Influence Function Jiancan Wu, Yi Yang, Yuchun Qian, Yongduo Sui, Xiang Wang, Xiangnan He WWW 2023 (Full, Accept rate: 19.2%) |
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Causal Attention for Interpretable and Generalizable Graph Classification
Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, Xiangnan He, Tat-Seng Chua KDD 2022 (Full Research, Accept Rate: 15.0%) [PDF] [Codes] |
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Towards Robust Detection and Segmentation Using Vertical and Horizontal Adversarial Training
Yongduo Sui, Tianlong Chen, Pengfei Xia, Shuyao Wang, Bin Li IJCNN 2022 (Oral Presentation) [PDF] |
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Exploring Lottery Ticket Hypothesis in Media Recommender Systems
Yanfang Wang, Yongduo Sui, Xiang Wang, Zhenguang Liu, Xiangnan He IJIS 2022 (International Journal of Intelligent Systems) |
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A Unified Lottery Ticket Hypothesis for Graph Neural Networks
Tianlong Chen*, Yongduo Sui*, Xuxi Chen, Aston Zhang, Zhangyang Wang ICML 2021 (Accept rate: 21.5%, *Co-first author) [PDF] [Codes] |
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Gans Can Play Lottery Tickets Too
Xuxi Chen, Zhenyu Zhang, Yongduo Sui, Tianlong Chen ICLR 2021 (Accept rate: 28.7%) |
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Graph Contrastive Learning with Augmentations
Yuning You, Tianlong Chen, Yongduo Sui, Ting Chen, Zhangyang Wang, Yang Shen NeurIPS 2020 (Accept rate: 20.1%) |
Reviewer of Conferences and Journals
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2024: ICLR, ICML, WWW, AAAI, AI, TNNLS 2023: ICLR, ICML, NeurIPS, WWW, KDD, SIGIR, TOIS, TKDE, TNNLS 2022: ICLR, ICML, NeurIPS, WWW, TOIS, TKDE 2021: NeurIPS |
Honors & Awards
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NeurIPS Scholar Award , 2023.11 |
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National Scholarship (PhD) , 2023.12 - University of Science and Technology of China |
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Longhu Scholarship, 2022.12 - University of Science and Technology of China |
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National Scholarship (Undergraduate) , 2018.12 - Harbin Engineering University |
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National Scholarship (Undergraduate) , 2017.12 - Harbin Engineering University |
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National Scholarship (Undergraduate) , 2016.12 - Harbin Engineering University |
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Outstanding Graduates , 2019 - Harbin Engineering University |
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"Study Star" on the Graduation Gold List , 2019 - Harbin Engineering University (Only One in the Entire School) |
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First-class Scholarship , 2016,2017,2018,2019 - Harbin Engineering University |
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Heilongjiang Province Outstanding Student , 2018 - Heilongjiang Province (< 1%) |
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School-level Study Role Model , 2017 - Harbin Engineering University (< 0.1%) |
Talks
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Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift, 2023.11 - AI TIME |
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Graph and Causality , 2023.10 - DataFun Causal Inference Summit |
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Graph Out-of-Distribution Generalization , 2023.03 - Ant Group |
Last update: 23 Dec, 2023. Webpage template borrows from Prof. Xiangnan He.