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Dr Ruihong Qiu
Dr

Ruihong Qiu

Email: 

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 2025.

Availability

Dr Ruihong Qiu is:
Available for supervision

Qualifications

  • Doctor of Philosophy of Computer Science (Information Technology), The University of Queensland

Works

Search Professor Ruihong Qiu’s works on UQ eSpace

22 works between 2019 and 2024

1 - 20 of 22 works

2024

Journal Article

A data-driven method for estimating sewer inflow and infiltration based on temperature and conductivity monitoring

Ge, Jingyu, Li, Jiuling, Qiu, Ruihong, Shi, Tao, Zhang, Chenming, Huang, Zi and Yuan, Zhiguo (2024). A data-driven method for estimating sewer inflow and infiltration based on temperature and conductivity monitoring. Water Research, 261 122002, 122002. doi: 10.1016/j.watres.2024.122002

A data-driven method for estimating sewer inflow and infiltration based on temperature and conductivity monitoring

2024

Conference Publication

CaseLink: inductive graph learning for legal case retrieval

Tang, Yanran, Qiu, Ruihong, Yin, Hongzhi, Li, Xue and Huang, Zi (2024). CaseLink: inductive graph learning for legal case retrieval. 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, Washington, DC, United States, 14-18 July 2024. New York, NY, United States: ACM. doi: 10.1145/3626772.3657693

CaseLink: inductive graph learning for legal case retrieval

2024

Conference Publication

Abstract and explore: a novel behavioral metric with cyclic dynamics in reinforcement learning

Zhu, Anjie, Zhang, Peng-Fei, Qiu, Ruihong, Zheng, Zetao, Huang, Zi and Shao, Jie (2024). Abstract and explore: a novel behavioral metric with cyclic dynamics in reinforcement learning. 38th AAAI Conference on Artificial Intelligence (AAAI) / 36th Conference on Innovative Applications of Artificial Intelligence / 14th Symposium on Educational Advances in Artificial Intelligence, Vancouver, Canada, 20-27 February 2024. Palo Alto, CA, United States: Association for the Advancement of Artificial Intelligence. doi: 10.1609/aaai.v38i15.29660

Abstract and explore: a novel behavioral metric with cyclic dynamics in reinforcement learning

2024

Book Chapter

CaseGNN: Graph Neural Networks for Legal Case Retrieval with Text-Attributed Graphs

Tang, Yanran, Qiu, Ruihong, Liu, Yilun, Li, Xue and Huang, Zi (2024). CaseGNN: Graph Neural Networks for Legal Case Retrieval with Text-Attributed Graphs. Lecture Notes in Computer Science. (pp. 80-95) Cham: Springer Nature Switzerland. doi: 10.1007/978-3-031-56060-6_6

CaseGNN: Graph Neural Networks for Legal Case Retrieval with Text-Attributed Graphs

2024

Book Chapter

Balanced and explainable social media analysis for public health with large language models

Jiang, Yan, Qiu, Ruihong, Zhang, Yi and Zhang, Peng-Fei (2024). Balanced and explainable social media analysis for public health with large language models. Databases Theory and Applications: 34th Australasian Database Conference, ADC 2023 Melbourne, VIC, Australia, November 1–3, 2023 Proceedings. (pp. 73-86) edited by Zhifeng Bao, Renata Borovica-Gajic, Ruihong Qiu, Farhana Choudhury and Zhengyi Yang. Heidelberg, Germany: Springer. doi: 10.1007/978-3-031-47843-7_6

Balanced and explainable social media analysis for public health with large language models

2023

Conference Publication

CaT: balanced continual graph learning with graph condensation

Liu, Yilun, Qiu, Ruihong and Huang, Zi (2023). CaT: balanced continual graph learning with graph condensation. 23rd IEEE International Conference on Data Mining (IEEE ICDM), Shanghai, China, 1-4 December 2023. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/icdm58522.2023.00141

CaT: balanced continual graph learning with graph condensation

2023

Conference Publication

Prompt-based effective input reformulation for legal case retrieval

Tang, Yanran, Qiu, Ruihong and Li, Xue (2023). Prompt-based effective input reformulation for legal case retrieval. 34th Australasian Database Conference, Melbourne, VIC Australia, 1-3 November 2023. Cham, Switzerland: Springer Cham. doi: 10.1007/978-3-031-47843-7_7

Prompt-based effective input reformulation for legal case retrieval

2023

Conference Publication

Beyond double ascent via recurrent neural tangent kernel in sequential recommendation

Qiu, Ruihong, Huang, Zi and Yin, Hongzhi (2023). Beyond double ascent via recurrent neural tangent kernel in sequential recommendation. 22nd IEEE International Conference on Data Mining (ICDM), Orlando, FL USA, 28 November-1 December 2022. New York, NY USA: Institute of Electrical and Electronics Engineers. doi: 10.1109/icdm54844.2022.00053

Beyond double ascent via recurrent neural tangent kernel in sequential recommendation

2022

Other Outputs

Modelling sequential patterns of user behaviour in recommender systems

Qiu, Ruihong (2022). Modelling sequential patterns of user behaviour in recommender systems. PhD Thesis, School of Information Technology and Electrical Engineering, The University of Queensland. doi: 10.14264/09e70dc

Modelling sequential patterns of user behaviour in recommender systems

2022

Conference Publication

FluMA: An Intelligent Platform for Influenza Monitoring and Analysis

Chen, Xi, Chen, Zhi, Wang, Zijian, Qiu, Ruihong and Luo, Yadan (2022). FluMA: An Intelligent Platform for Influenza Monitoring and Analysis. 33rd Australasian Database Conference (ADC), Sydney, NSW Australia, 2-4 September 2022. Heidelberg, Germany: Springer. doi: 10.1007/978-3-031-15512-3_12

FluMA: An Intelligent Platform for Influenza Monitoring and Analysis

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

Long short-term enhanced memory for sequential recommendation

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

Exploiting positional information for session-based recommendation

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

Contrastive learning for representation degeneration problem in sequential recommendation

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

An integrated first principal and deep learning approach for modeling nitrous oxide emissions from wastewater treatment plants

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

Mitigating Generation Shifts for Generalized Zero-Shot Learning

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

CausalRec: causal inference for visual debiasing in visually-aware recommendation

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

Semantics disentangling for generalized zero-shot learning

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

Learning to diversify for single domain generalization

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

Memory augmented multi-instance contrastive predictive coding for sequential recommendation

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

GAG: global attributed graph neural network for streaming session-based recommendation

Funding

Current funding

  • 2025 - 2027
    Lifelong Paradigms for Versatile, Robust and Agile Recommender Systems
    ARC Discovery Early Career Researcher Award
    Open grant

Past funding

  • 2022 - 2024
    Developing a proof-of-concept self-contact tracing app to support epidemiological investigations and outbreak response (Australia-Korea Joint Call for Joint Research Projects - ATSE Tech Bridge Grant)
    Australian Academy of Technological Sciences and Engineering
    Open grant

Supervision

Availability

Dr Ruihong Qiu is:
Available for supervision

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Supervision history

Current supervision

Media

Enquiries

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