Research

The long-term research goal is to build AI models for modern Education, such as Deep learning models, pre-trained models and large models. We create new theory, algorithms, applications, and open-sourced library to achieve our goal. These days, we are specifically interested in Knowledge Representation and Reasoning, Trustworthy, Security and Data Privacy and AI For Education.

Our research consists of the following topics with selected publications: [View by year] [Google scholar]

Awards

• [On the role of logical separabilityin knowledge compilation]. Computer Academy of Guangdong, [Best Paper Award ‘24] .
• [Students’experience of online learning during the COVID-19pandemic: A province-wide survey study]. British Journal Of Educational Technology, [Top Cited Article ‘21-22] .
• [Students’experience of online learning during the COVID-19pandemic: A province-wide survey study]. British Journal Of Educational Technology, [Top Downloaded Article ‘21-22] .
• [Adaptive Convolutional Time Series Evaluation for Attack Behavior Postures]. 2024 lnternational conference on ElectricalElectronics and Information science(EEIS 2024), [Best Paper Award] .

New: Knowledge Representation and Reasoning

Evaluation: (website: https://github.com/chanllon)

• [Neurocomputing’25] HCKGL: Hyperbolic collaborative knowledge graph learning for recommendation. Huijuan Hu, Chaobo He, Xinran Chen, Quanlong Guan.
• [Neural Networks’25] Explainable exercise recommendation with knowledge graph. Quanlong Guan, Xinghe Cheng, Fang Xiao, Zhuzhou Li, Chaobo He, Liangda Fang, Guanliang Chen, Zhiguo Gong, Weiqi Luo.
• [TKDE’25] Rethinking Variational Bayes in Community Detection from Graph Signal Perspective. [IEEE Transactions on Knowledge and Data Engineering] Junwei Cheng, Yong Tang, Chaobo He, Pengxing Feng, Kunlin Han, Quanlong Guan.
• [Neural Networks’25] Signed graph embedding via multi-order neighborhood feature fusion and contrastive learning . Chaobo He, Hao Cheng, Jiaqi Yang, Yong Tang, Quanlong Guan.
• [C&E’25] Can AI support human grading? Examining machine attention and confidence in short answer scoring. [Computers & Education] Yuheng Li, Mladen Raković, Namrata Srivastava, Xinyu Li, Quanlong Guan, Dragan Gašević, Guanliang Chen.
• [COLING’25] KVFKT: A New Horizon in Knowledge Tracing with Attention-Based Embedding and Forgetting Curve Integration. [Proceedings of the 31st International Conference on Computational Linguistics]. Quanlong Guan, Xiuliang Duan, Kaiquan Bian, Guanliang Chen, Jianbo Huang, Zhiguo Gong, Liangda Fang.
• [MM’24] Reason-and-execute prompting: Enhancing multi-modal large language models for solving geometry questions. [Proceedings of the 32nd ACM International Conference on Multimedia ]. Xiuliang Duan, Dating Tan, Liangda Fang, Yuyu Zhou, Chaobo He, Ziliang Chen, Lusheng Wu, Guanliang Chen, Zhiguo Gong, Weiqi Luo, Quanlong Guan.
• [IJCAI’24] On the logic of theory change iteration of KM-update, revised. [Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence]. Liangda Fang, Tong Zhu, Quanlong Guan, Junming Qiu, Zhao-Rong Lai, Weiqi Luo, Hai Wan.
• [IJCAI’24] A multi-valued decision diagram-based approach to constrained optimal path problems over directed acyclic graphs. [Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence]. Mingwei Zhang, Liangda Fang, Zhenhao Gu, Quanlong Guan, Yong Lai.
• [WWW’24] Boost Social Recommendation via Adaptive Denoising Network. Xinran Chen, Chaobo He, Quanlong Guan.
• [AAMAS’24] Generalized Strategy Synthesis of Infinite-state Impartial Combinatorial Games via Exact Binary Classification. [Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems]. Liangda Fang, Meihong Yang, Dingliang Cheng, Yunlai Hao, Quanlong Guan, Liping Xiong.
• [Information Fusion’24] Detecting communities with multiple topics in attributed networks via self-supervised adaptive graph convolutional network. [Information Fusion]. Chaobo He, Junwei Cheng, Guohua Chen, Quanlong Guan, Xiang Fei, Yong Tang.
• [AAAI’24] Unveiling the tapestry of automated essay scoring: A comprehensive investigation of accuracy, fairness, and generalizability. Kaixun Yang, Mladen Raković, Yuyang Li, Quanlong Guan, Dragan Gašević, Guangliang Chen.
• [AAAI’24] Diagnosing and Rectifying Fake OOD Invariance: A Restructured Causal Approach. Ziliang Chen, Yongsen Zheng, Zhao-Rong Lai, Quanlong Guan, Liang Lin.
• [AIJ’24] On the role of logical separability in knowledge compilation. [Artificial Intelligence]. Junming Qiu, Wenqing Li, Liangda Fang, Quanlong Guan, Zhanhao Xiao, Zhao-Rong Lai, Qian Dong.
• [CIKM’23] A Deep Conditional Generative Approach for Constrained Community Detection. Chaobo He, Junwei Cheng, Quanlong Guan, Xiang Fei, Hanchao Li, Yong Tang.
• [CIKM’23] Kg4ex: An explainable knowledge graph-based approach for exercise recommendation. Quanlong Guan, Fang Xiao, Xinghe Cheng, Liangda Fang, Ziliang Chen, Guanliang Chen, Weiqi Luo.
• [ICCV’23] A retrospect to multi-prompt learning across vision and language. Ziliang Chen, Xin Huang, Quanlong Guan, Liang Lin, Weiqi Luo.

Trustworthy, Security and Data Privacy

• [WWW’24] Generating Privacy-preserving Educational Data Records with Diffusion Model Quanlong Guan, Yanchong Yu, Xiujie Huang, Liangda Fang, Chaobo He, Lusheng Wu, Weiqi Luo, Guanliang Chen.
• Open-source:
  • Educational Data Privacy with Diffusion Model
• [RESS’25] Phase combination for reliability analysis of dynamic k-out-of-n Phase-AND mission systems . Chaonan Wang, Shenghui Luo, Guizhuang Chen, Zhitao Wu, Wenjing Rong, Quanlong Guan.
• [RESS’25] Reliability analysis of IoV-based vehicle monitoring systems subject to cascading probabilistic common cause failures. Chaonan Wang, Yingxi Lie, Yuchang Mo, Quanlong Guan.
• [TITS’25] An Efficient and Multi-Dimensional Privacy-Preserving Platoon Communication Scheme in Vehicular Networks.[IEEE Transactions on Intelligent Transportation Systems]. Nuo Xu, Zhiquan Liu, Xuming Han, Quanlong Guan, Heng Sun, Xiujie Huang, Jianfeng Ma.
• [RESS’25] Efficient reliability analysis of generalized k-out-of-n phased-mission systems. Guizhuang Chen, Yuliang Hu, Chaonan Wang, Zhitao Wu, Wenjing Rong, Quanlong Guan.
• [IOT’24] Hybrid Transfer and Self-Supervised Learning Approaches in Neural Networks for Intelligent Vehicle Intrusion Detection and Analysis. Tian Zhang, Cuifeng Du, Yuyu Zhou, Quanlong Guan, Zhiquan Liu, Xiujie Huang, Zhiguo Gong, Lianbing Deng, Yang Li.
• [ISSRE’24] Exact Computation of Network Reliability with Sentential Decision Diagrams.[2024 IEEE 35th International Symposium on Software Reliability Engineering (ISSRE)] Delong Li, Jiayu Zeng, Liangda Fang, Chaonan Wang, Lin Cui, Quanlong Guan.
• [TR-IEEE’24] Reliability analysis of phased-mission smart home systems with cascading common cause failures. [IEEE Transactions on Reliability]. Qian Chen, Chaonan Wang, Quanlong Guan, Jiaqi Shi.
• [Measurement’24] Online kinematic calibration of robot manipulator based on neural network. Yueke Kong, Lin Yang, Chuxin Chen, Xiaojun Zhu, Di Li, Quanlong Guan, Guanglong Du.
• [TVT’24] Vsrq: Quantitative assessment method for safety risk of vehicle intelligent connected system.[IEEE Transactions on Vehicular Technology]. Tian Zhang, Wenshan Guan, Hao Miao, Xiujie Huang, Zhiquan Liu, Chaonan Wang, Quanlong Guan, Liangda Fang, Zhifei Duan.
• [RESS’23] Efficient reliability approximation for large k-out-of-n cold standby systems with position-dependent component lifetime distributions. Chaonan Wang, Xiaolei Wang, Liudong Xing, Quanlong Guan, Chunhui Yang, Min Yu.
• [RESS’23] Efficient performability analysis of dynamic multi-state k-out-of-n: G systems. Chaonan Wang, Shuli Wang, Liudong Xing, Quanlong Guan.
• [RESS’23] Phase reduction for efficient reliability analysis of dynamic k-out-of-n phased mission systems. Chaonan Wang, Liudong Xing, Jingui Yu, Quanlong Guan, Chunhui Yang, Min Yu.