Overview
Background
My research focuses on data science methods, including theory and application for various real-world scenarios, such as recommender systems, social network, urban computing, engineering, law, health etc. I am particularly interested into graph neural networks, large language models (LLMs, MLLMs), etc.
- I am actively looking for PhD students (multiple positions) starting in Year 2026. Please visit: https://ruihongqiu.github.io/recruit-phd/
- I am actively looking for thesis/honours/research/RA students yearly. Please visit: https://ruihongqiu.github.io/recruit-thesis/
Availability
- Dr Ruihong Qiu is:
- Available for supervision
Qualifications
- Doctor of Philosophy of Computer Science (Information Technology), The University of Queensland
Research impacts
I have be granted the Australian Research Council Discovery Early Career Researcher Award (ARC DECRA) 2025-2028.
Works
Search Professor Ruihong Qiu’s works on UQ eSpace
2022
Journal Article
Long short-term enhanced memory for sequential recommendation
Duan, Jiasheng, Zhang, Peng-Fei, Qiu, Ruihong and Huang, Zi (2022). Long short-term enhanced memory for sequential recommendation. World Wide Web, 26 (2), 1-23. doi: 10.1007/s11280-022-01056-9
2022
Journal Article
Exploiting positional information for session-based recommendation
Qiu, Ruihong, Huang, Zi, Chen, Tong and Yin, Hongzhi (2022). Exploiting positional information for session-based recommendation. ACM Transactions on Information Systems, 40 (2) 3473339, 1-24. doi: 10.1145/3473339
2022
Conference Publication
Contrastive learning for representation degeneration problem in sequential recommendation
Qiu, Ruihong, Huang, Zi, Yin, Hongzhi and Wang, Zijian (2022). Contrastive learning for representation degeneration problem in sequential recommendation. WSDM '22: Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining, Virtual, AZ, United States, 21 - 25 February 2022. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3488560.3498433
2022
Journal Article
An integrated first principal and deep learning approach for modeling nitrous oxide emissions from wastewater treatment plants
Li, Kaili, Duan, Haoran, Liu, Linfeng, Qiu, Ruihong, van den Akker, Ben, Ni, Bing-Jie, Chen, Tong, Yin, Hongzhi, Yuan, Zhiguo and Ye, Liu (2022). An integrated first principal and deep learning approach for modeling nitrous oxide emissions from wastewater treatment plants. Environmental Science and Technology, 56 (4) acs.est.1c05020, 2816-2826. doi: 10.1021/acs.est.1c05020
2021
Conference Publication
Mitigating Generation Shifts for Generalized Zero-Shot Learning
Chen, Zhi, Luo, Yadan, Wang, Sen, Qiu, Ruihong, Li, Jingjing and Huang, Zi (2021). Mitigating Generation Shifts for Generalized Zero-Shot Learning. MM '21: ACM Multimedia Conference, Online, 20 - 24 October 2021. Washington, DC United States: Association for Computing Machinery. doi: 10.1145/3474085.3475258
2021
Conference Publication
CausalRec: causal inference for visual debiasing in visually-aware recommendation
Qiu, Ruihong, Wang, Sen, Chen, Zhi, Yin, Hongzhi and Huang, Zi (2021). CausalRec: causal inference for visual debiasing in visually-aware recommendation. MM '21: ACM Multimedia Conference, Virtual, 20-24 October 2021. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3474085.3475266
2021
Conference Publication
Semantics disentangling for generalized zero-shot learning
Chen, Zhi, Luo, Yadan, Qiu, Ruihong, Wang, Sen, Huang, Zi, Li, Jingjing and Zhang, Zheng (2021). Semantics disentangling for generalized zero-shot learning. 2021 IEEE/CVF International Conference on Computer Vision (ICCV), Montreal, QC Canada, 10-17 October 2021. Piscataway, NJ USA: Institute of Electrical and Electronics Engineers. doi: 10.1109/iccv48922.2021.00859
2021
Conference Publication
Learning to diversify for single domain generalization
Wang, Zijian, Luo, Yadan, Qiu, Ruihong, Huang, Zi and Baktashmotlagh, Mahsa (2021). Learning to diversify for single domain generalization. 2021 IEEE/CVF International Conference on Computer Vision (ICCV), Montreal, QC Canada, 10-17 October 2021. Piscataway, NJ USA: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICCV48922.2021.00087
2021
Conference Publication
Memory augmented multi-instance contrastive predictive coding for sequential recommendation
Qiu, Ruihong, Huang, Zi and Yin, Hongzhi (2021). Memory augmented multi-instance contrastive predictive coding for sequential recommendation. IEEE International Conference on Data Mining, Auckland, New Zealand, 7-10 December 2021. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICDM51629.2021.00063
2020
Conference Publication
GAG: global attributed graph neural network for streaming session-based recommendation
Qiu, Ruihong, Yin, Hongzhi, Huang, Zi and Chen, Tong (2020). GAG: global attributed graph neural network for streaming session-based recommendation. International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual Event China , 25-30 July 2020. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3397271.3401109
2020
Journal Article
Exploiting cross-session information for session-based recommendation with graph neural networks
Qiu, Ruihong, Huang, Zi, Li, Jingjing and Yin, Hongzhi (2020). Exploiting cross-session information for session-based recommendation with graph neural networks. ACM Transactions on Information Systems, 38 (3) 22, 1-23. doi: 10.1145/3382764
2019
Conference Publication
Rethinking the item order in session-based recommendation with graph neural networks
Qiu, Ruihong, Li, Jingjing, Huang, Zi and Yin, Hongzhi (2019). Rethinking the item order in session-based recommendation with graph neural networks. CIKM '19 28th ACM International Conference on Information and Knowledge Management, Beijing, China, 3 - 7 November, 2019. New York, New York, USA: ACM Press. doi: 10.1145/3357384.3358010
Supervision
Availability
- Dr Ruihong Qiu is:
- Available for supervision
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Available projects
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Advancing Reasoning Ability in Diffusion Large Language Models
Investigate the development of enabling diffusion large language models to achieve advanced reasoning ability.
Supervision history
Current supervision
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Doctor Philosophy
Fairness in Graph Representation Learning Models
Principal Advisor
Other advisors: Professor Helen Huang
-
Doctor Philosophy
Exploring the Trustworthiness of Information Retrieval in the Era of Large Language Models
Principal Advisor
Other advisors: Professor Helen Huang
-
Doctor Philosophy
Towards Privacy-Preserving and Fairness-Aware Federated Recommendation Systems
Principal Advisor
Other advisors: Professor Helen Huang
-
Doctor Philosophy
Towards Explainable Multi-source Multivariate Time-series Analysis
Associate Advisor
Other advisors: Associate Professor Jiajun Liu, Associate Professor Sen Wang
-
Doctor Philosophy
Multi-Modal Perception for Context-Aware Systems
Associate Advisor
Other advisors: Professor Helen Huang, Dr Yujun Cai
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Doctor Philosophy
efficiency oriented multimedia system
Associate Advisor
Other advisors: Professor Helen Huang
-
Doctor Philosophy
Auditing Privacy Policy Compliance of IoT Applications
Associate Advisor
Other advisors: Professor Helen Huang
-
Doctor Philosophy
Data-Driven Crop Breeding: Enhancing Disease Resistance through Vision-based Digital Phenotyping
Associate Advisor
Other advisors: Professor Helen Huang, Associate Professor Sen Wang
-
Doctor Philosophy
Data quality assurance in digitalisation of urban water management
Associate Advisor
Other advisors: Professor Helen Huang, Honorary Professor Zhiguo Yuan, Dr Jiuling Li
Media
Enquiries
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