People

2.Biography

Dr. Zhengyang Wu is an associate professor and a professor-level senior engineer at the Colledge of Computer Science of South China Normal University. He is a senior member of the China Computer Federation (CCF) and an executive member of the CCF Collaborative Computing Committee. He was a visiting scholar at RMIT University from 2019 to 2020 and Sun Yat-sen University from 2024 to 2025.

Dr. Wu presided over the general project of the National Natural Science Foundation of China， and the characteristic innovation project of Guangdong Provincial Universities. He serves as the contact person for the National Key R&D Program. He has published more than 30 papers in high-level academic journals and conferences such as IEEE TKDE， Information Science， Knowledge-Based Systems， IEEE TCSS， WWW， ICONIP， KSEM， etc.， and has obtained more than 10 invention patents and software copyrights as the first/corresponding author.

Dr. Wu has served as a project reviewer for the National Natural Science Foundation of China， a reviewer for CCF journals such as Chinese Journal of Computers， and a reviewer for SCI journals such as KBS and IEEE ToE.

3.Research Interests

Educational Data Mining， AI for Education， Knowledge Discovery

4.Email

Wuzhengyang@m.scnu.edu.cn

5.Academic

Papers:

[1]  Zetao Zheng， Zhengyang Wu*， Zahir Tar， Jia Zhu*， Ke Deng. CeKT: Knowledge Tracing for Predicting Collective Performance on Exercise Sequence. IEEE Transactions on Computational Social Systems， Early Access

[2] Zhanxuan Chen， Zhengyang Wu*， Qiuying Ye， Yunxuan Lin. Interaction Sequence Temporal Convolutional Based Knowledge Tracing.  International Conference on Intelligent Computing (ICIC 2024)， August 5-8， 2024， Tianjin， China. (CCF C)

[3] Zhengyang Wu， Ke Deng*， Judy Qiu， Yong Tang*. ExamGAN and Twin-ExamGAN for Exam Script Generation. IEEE Transactions on Knowledge and Data Engineering， February，2023.Online.(SCI， IF:9.235)

[4]  Jinwei Zhou， Zhengyang Wu*， Chengzhe Yuan， Lizhang Zeng. A Causality-Based Interpretable Cognitive Diagnostic Model.  2023 International Conference on Neural Information Processing(ICONIP). CCF-C， In Neural Information Processing. ICONIP 2023. Lecture Notes in Computer Science， vol 14449. Springer， Singapore. pp. 214–226

[5]  Zhanxuan Chen， Zhengyang Wu*， Yong Tang. TGKT-based Personalized Learning Path Recommendation with Reinforcement Learning.  The 16th International Conference on Knowledge Science， Engineering and Management (CCF C)， August 16-18， 2023

[6]  Zhengyang Wu， Li Huang， Qionghao Huang， Changqin Huang*， Yong Tang*. SGKT: Session Graph-Based Knowledge Tracing for Student Performance Prediction. Expert Systems With Applications， June， 2022 (SCI， IF:8.665)

[7]  Zhengyang Wu*， Ming Li， Yong Tang*， Qingyu Liang. Exercise Recommendation Based on Knowledge Concept Prediction. Knowledge-Based Systems， Dec，2020， (SCI， IF:8.139)

[8]  Zhengyang Wu， Tao He， Chenjie Mao， Changqin Huang*. Exam Paper Generation Based on Performance Prediction of Student Group . Information Sciences， 532:72-90， Sept. 2020. (SCI， IF:8.233)

Projects:

[1] National Natural Science Foundation of China (62377015). Learning Evaluation and Prediction Based on Dynamic Heterogeneous Graph Decoupling Representation in Large-scale Online Education Scenarios. 2024.01-2027.12.

[2] Characteristic Innovation Project of Guangdong Provincial Colleges and Universities(2024KTSCX094). Research on High Robustness Retrieval Enhancement Generative Model Based on Hierarchical Reinforcement Learning. 2024.10-2026.10.