News
23 Jan 2024
Three papers are accepted by WWW on graph anomaly detection, invariant graph learning, and graph condensation.
22 Sep 2023
One paper is accepted by NeurIPS on graph neural network explanation.
16 Feb 2023
One paper is accepted by ICDE on loan default prediction.
25 Jan 2023
One paper is accepted by WWW on graph anomaly detection.
18 Oct 2022
One paper is accepted by WSDM on graph anomaly detection.
30 Jun 2022
One paper is accepted by FCS on self-supervised rumor detection.
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YUAN GAO
PhD student
School of Cyber Science and Techonology
Email: yuanga@mail.ustc.edu.cn
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I am a final year PhD student at the USTC Lab for Data Science, supervised by Prof. Xiangnan He and Prof. Xiang Wang. My research interest lies in graph anomaly detection and molecular / drug discovery. I have multiple publications that appear in top-tier conferences including WSDM (Oral), WWW, NeurIPS and ICDE.
In the Year of 2023:
Publication
In the Year of 2024: |
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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Invariant Graph Learning for Treatment Effect Estimation from Networked Observational Data
Yongduo Sui, Caizhi Tang, Zhixuan Chu, Junfeng Fang, Yuan Gao, Qing Cui, Longfei Li, Jn Zhou & Xiang Wang 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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Evaluating Post-hoc Explanations for Graph Neural Networks via Robustness Analysis
Junfeng Fang, Wei Liu, Xiang Wang, Zemin Liu, An Zhang, Yuan Gao & Xiangnan He NeurIPS 2023 (Full Oral, Accept Rate: 26.1%) |
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LightMIRM: Light Meta-learned Invariant Risk Minimization for Trustworthy Loan Default Prediction
Meng Jiang, Yang Zhang, Yuan Gao, Yansong Wang, Fuli Feng & Xiangnan He ICDE 2023 (Full) |
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Addressing Heterophily in Graph Anomaly Detection: A Perspective of Graph Spectrum
Yuan Gao, Xiang Wang*, Xiangnan He*, Zhenguang Liu, Huamin Feng & Yongdong Zhang WWW 2023 (Full Oral, Accept Rate: 19.2%) Codes |
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Alleviating Structural Distribution Shift in Graph Anomaly Detection
Yuan Gao, Xiang Wang*, Xiangnan He*, Zhenguang Liu, Huamin Feng & Yongdong Zhang WSDM 2023 (Full Oral, Accept Rate: 17.8%) Codes |
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Rumor Detection with Self-supervised Learning on Texts and Social Graph
Yuan Gao, Xiang Wang*, Xiangnan He*, Huamin Feng & Yongdong Zhang Frontiers of Computer Science (FCS) |
Rewards
| KDDCup 2022 Wind Power Forecasting (10/2490) |
Experiences
| Software Engineer - Machine Learning, Shopee (Singapore), Aug 2019 - Aug 2020 |
Services
| Program committee member of ECML-PKDD 2022, SIGIR 2023, WSDM2024, AAAI2024, WWW2024. |
Education
| University of Science and Techonology of China (USTC) PhD student in Computer Science Sep 2020 - Now, Hefei Advisor: Prof. Xiangnan He and Prof. Xiang Wang Mentor: Prof. Huamin Feng and Prof. Yongdong Zhang |
| University of Michigan (Umich) Master in Electrical and Computer Engineering Sep 2017 - June 2019, Ann Arbor |
| University of Electronic Science and Technology of China (UESTC) Bachelor in Electrical Engineering Sep 2013 - June 2017, Chengdu Advisor: Prof. Yang Han |
Last update: 6 Feb, 2024. Webpage template borrows from Prof. Xiangnan He.