Quanlong Guan

Professor, Jinan University
Vice Dean，Guangdong Institute of Smart Education,
College of Information Science and Technology,
Jinan University, Tianhe District, Guangzhou, China
gql [at] jnu.edu.cn
Jnu | Google scholar | Github || Scholat (Chinese) | DBLP | Orcid || CV

Dr. Quanlong Guan is currently a Full Professor at Jinan University. He visited Sencun Zhu’s group at The Pennsylvania State University in 2012. His research interests include robust machine learning, Data Security, semi-supervised learning, recommendation systems, and multimodal learning. He has published over 50 papers at leading conferences and journals such as AAAI, ICCV, CIKM, RESS, PR, KBS, etc. He has 1 highly cited paper in Google Scholar metrics. He serves as PC members for top conferences like AAAI, NeurIPS, IJCAI, CVPR, KDD, SIGIR, MM, WSDM etc. He leads several high-value projects, such as multimodal learning, recommendation systems, and Data security.

Research interest: Machine learning, multimodal learning, semi-supervised learning, recommendation systems, and related applications such as activity recognition, smart education, and computer vision. These days, I’m particularly interested in Multimodal representation Learning, [Large Language Models] (LLMs) for education (Multimodal，recommendation，RAG, Q&A, etc…) and Excises recommendation. See this page for more details. Interested in internship or collaboration? Contact me.

Announcement: I am actively seeking Ph.D. students. If you are interested in collaborating with me, please don’t hesitate to reach out. However, please be aware that I receive a high volume of emails daily, which may lead to some delays in my response. Your patience in this regard is greatly appreciated. Thank you. You can click here gql@jnu.edu.cn if you are interested!

News

Jul 21, 2024 One paper of our team has been accepted for “ACM MM”, a top-tier international Conference categorized as CCF A-class in Computer Graphics and Multimedia.
Apr 17, 2024 Two papers of our team has been accepted for “IJCAI 2024”, a top-tier international Conference categorized as CCF A-class in Artificial Intelligence.
Feb 20, 2024 One paper of our team has been accepted for “Artificial Intelligence”, a top-tier international Journal categorized as CCF A-class in Artificial Intelligence.[DOI]
Feb 1, 2024 One paper of our team has been accepted for “Information Fusion”, a top-tier international Journal categorized as SCI-1st class.[DOI]
Dec 28, 2023 Two of the team’s achievements have been accepted for “AAAI 2024”, a top-tier international conference categorized as CCF A-class in Artificial Intelligence.[html]
Dec 19, 2023 The team’s research achievements have been accepted for publication at “ICCV 2023”, a top-tier international conference categorized as CCF A-class in Artificial Intelligence.[pdf]

Highlights

  1. one of my papers is Top cited and downloaded article in Wiley Publisher. See here.
  2. In recognition of outstanding contributions to IJCAI 2023, I was awarded DISTINGUISHED PC MEMBER CERTIFICATE, The 32th International Joint Conference on Artificial Intelligence :
  3. I was as PC member list of AAAI 2021-,WSDM 2022-,IJCAI 2021-, CVPR 2023-, NeurIPS 2023-, KDD 2024-, ICML 2024-

Selected publications

  1. Boost Social Recommendation via Adaptive Denoising Network
    Xinran Chen, Quanlong Guan , and Chaobo He#
    Companion Proceedings of the ACM on Web Conference 2024, WWW, Singapore 2024 | [ HTML ]
  2. Generating Privacy-preserving Educational Data Records with Diffusion Model
    Quanlong Guan , Yanchong Yu, Xiujie Huang#, Liangda Fang#, Chaobo He, Lusheng Wu#, Weiqi Luo, and Guanliang Chen
    Companion Proceedings of the ACM on Web Conference 2024, WWW, Singapore 2024 | [ HTML ]
  3. On the Logic of Theory Change Iteration of KM-Update, Revised
    Liangda Fang, Tong Zhu, Quanlong Guan# , Junming Qiu#, Zhao-Rong Lai, Weiqi Luo, and Hai Wan
    Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, IJCAI-24 2024 | [ HTML ]
  4. A Multi-Valued Decision Diagram-Based Approach to Constrained Optimal Path Problems over Directed Acyclic Graphs
    Mingwei Zhang, Liangda Fang#, Zhenhao Gu, Quanlong Guan# , and Yong Lai
    Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, IJCAI-24 2024 | [ HTML ]
  5. Unveiling the Tapestry of Automated Essay Scoring: A Comprehensive Investigation of Accuracy, Fairness, and Generalizability
    Kaixun Yang, Mladen Rakovic, Yuyang Li, Quanlong Guan# , Dragan Gasevic, and Guanliang Chen#
    Thirty-Eighth AAAI Conference on Artificial Intelligence, AAAI 2024, Vancouver, Canada 2024 | [ HTML ]
  6. Diagnosing and Rectifying Fake OOD Invariance: A Restructured Causal Approach
    Ziliang Chen, Yongsen Zheng, Zhao-Rong Lai, Quanlong Guan# , and Liang Lin
    Thirty-Eighth AAAI Conference on Artificial Intelligence, AAAI 2024, Vancouver, Canada 2024 | [ HTML ]
  7. On the role of logical separability in knowledge compilation
    Junming Qiu, Wenqing Li, Liangda Fang#, Quanlong Guan# , Zhanhao Xiao, Zhao-Rong Lai, and Qian Dong
    Artif. Intell. 2024 | [ HTML ]
  8. A Retrospect to Multi-prompt Learning across Vision and Language
    Ziliang Chen, Xin Huang, Quanlong Guan# , Liang Lin, and Weiqi Luo
    International Conference on Computer Vision (ICCV) 2023 | [ HTML ]
  9. KG4Ex: An Explainable Knowledge Graph-Based Approach for Exercise Recommendation
    Quanlong Guan , Fang Xiao, Xinghe Cheng, Liangda Fang#, Ziliang Chen, Guanliang Chen, and Weiqi Luo
    Proceedings of the 32nd ACM International Conference on Information and Knowledge Management. 2023 | [ HTML ]
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