Qianru Zhang (张倩茹)
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Qianru Zhang (张倩茹) |
About
I am a forth-year Ph.D student at the University of Hong Kong (HKU), majoring in Computer Science, supervised by Professor Yiu Siu-Ming. My research focuses on optimizing graph-based models, including GCNs, contrastive learning, transformers, diffusion models, reinforcement learning, and LLMs. By exploring underlying principles and mathematical frameworks, I develop innovative algorithms that effectively leverage the structural properties of graph/image data. This approach enhances accuracy, scalability, and interpretability. For example, I advance our understanding of graph algorithms in spatial-temporal graphs, recommendation systems, and bioinformatics.
Graph Data Mining
Spatial-Temporal Graphs (AI for Urban Science)
AI for Physical Science
AI for Biology Science
Recently, I am interested in Large Language Models (LLMs) / Diffusion Models / Mamba for Urban / Biology / Physical Science. If you would like to work with me, please kindly contact me.
I am looking for Postdoc positions. If you have suitable positions, please don't hesitate to contact me.
Highlights
- WWW 2023 Our paper titled "Automated Spatio-Temporal Graph Contrastive Learning" is the first one to optimize contrastive learning for ubran science area [Blog].🤩
- ICML 2023 Our paper titled "Spatial-Temporal Graph Learning with Adversarial Contrastive Adaptation" attracts high attentions [Blog].
- ICDE 2023 Our paper titled "Online Anomalous Subtrajectory Detection on Road Networks with Deep Reinforcement Learning" is adopted in real applications (DiDi project and UW planning project).🤩
- Highly cited paper Our paper titled "Building Auto-Encoder Intrusion Detection System based on Random Forest Feature Selection'' is highly cited (citations: 266 from 2020.9).
News
- [Mar. 2024] One paper about Graph Augmentation for Recommendation was accepted by ICDE 2024.🤩 See you in Utrecht, Netherlands!
- [Nov. 2023] One paper about Improving Factual Error Correction by Learning to Inject Factual Errors was accepted by AAAI 2024. Congrats to Xingwei He!
- [Apr. 2023] One paper about Spatial-Temporal Graph Learning with Adversarial Contrastive Adaptation was accepted by ICML 2023.
- [Jan. 2023] One paper about Automated Spatio-Temporal Graph Contrastive Learning was accepted by WWW 2023.
- [Nov. 2022] One paper about Online Anomalous Subtrajectory Detection on Road Networks with Deep Reinforcement Learning was accepted by ICDE 2023.
- [Apr. 2022] One paper about On Predicting and Generating a Good Break Shot in Billiards Sports was accepted by SDM 2022.
- [May. 2021] One paper about Error-Bounded Online Trajectory Simplification with Multi-Agent Reinforcement Learning was accepted by SIGKDD 2021.
Selected Publications
A Survey of Generative Techniques for Spatial-Temporal Data Mining.
Qianru Zhang, Haixin Wang, Cheng Long, Liangcai Su, Xingwei He, Jianlong Chang, Tailin Wu, Hongzhi Yin, Siu-Ming Yiu, Qi Tian and Christian S. Jensen.
[Paper]Graph Augmentation for Recommendation.
Qianru Zhang, Lianghao Xia, Xuheng Cai, Siuming Yiu, Chao Huang, and Christian S. Jensen.
ICDE 2024. [Paper] [Code]Spatial-Temporal Graph Learning with Adversarial Contrastive Adaptation.
Qianru Zhang, Chao Huang, Lianghao Xia, Zheng Wang, Siu-Ming Yiu, and Ruihua Han.
ICML 2023. [Paper] [Code]Online Anomalous Subtrajectory Detection with Road Network Enhanced Reinforcement Learning.
Qianru Zhang, Zheng Wang, Cheng Long, Chao Huang, Siu-Ming Yiu, Yiding Liu, Gao Cong, and Jieming Shi.
ICDE 2023. [Paper] [Code]Automated Spatio-Temporal Graph Contrastive Learning.
Qianru Zhang, Chao Huang, Lianghao Xia, Zheng Wang, Zhonghang Li, and Siu-Ming Yiu
WWW 2023 ( Accepted at the highest rank (2.75/3.0)). [Paper] [Code]On Predicting and Generating a Good Break Shot in Billiards Sports.
Qianru Zhang, Zheng Wang, Cheng Long, and Siu-Ming Yiu.
SDM 2022. [Paper]Improving Factual Error Correction by Learning to Inject Factual Errors.
Xingwei He, Qianru Zhang, Along Jin, Jun Ma, Yuan Yuan, and Siu-Ming Yiu.
AAAI 2024.Error-Bounded Online Trajectory Simplification with Multi-Agent Reinforcement Learning.
Zheng Wang, Cheng Long, Gao Cong, and Qianru Zhang.
SIGKDD 2021.Accelerated Collision-Free Robot Motion Planner with Dual Proximal Methods.
Ruihua Han, Shuai Wang, Shuaijun Wang, Zeqing Zhang, Qianru Zhang, Hao Qi, and Jia Pan.
IEEE RA-L 2023.Building Auto-Encoder Intrusion Detection System based on Random Forest Feature Selection.
Xukui Li, Wei Chen, Qianru Zhang, and Lifa Wu.
Computers and Security 2020 (Highly cited paper).
Academic Services and Invited Talks
- Reviewers for WWW'2024, ICLR'2024, Nerips'2023
- Invited talks titled "Robust and Efficient Spatial-Temporal Graph Learning" @ South China Normal University (Nov. 2023) and @Westlake University (Dec 2023).
Work Experiences
- NLP Engineer (Special offer) @ Alibaba Group, 2019.7-2020.8
- Federated Learning Research Intern @ Webank, 2019.3-2019.5
Teaching Assistant
- COMP7405 Techniques in Computational Finance, 2021.1 - 2021.5
- FITE7405 Techniques in Computational Finance, 2022.1 - 2022.5
- FITE7405 Techniques in Computational Finance, 2023.1 - 2023.5
- FITE7405 Techniques in Computational Finance, 2024.1 - 2024.5
Awards
- Top 40 Recipients of the Baidu Research Fellowships Worldwide, 2023.
- Student Travel Award, ACM WWW, 2023.
- Postgraduate Scholarship (HKU), 2020.9-2024.9.
- Merit Student of Jiangsu Province (Top 1%).
- National Scholarship (Top 1%).
- Fist-class Scholarship (Three times) (Top 5%).
