I am a Ph.D. student at the School of Computer Science, Nanjing University of Posts and Telecommunications, supervised by Prof. Haiping Huang. I obtained my B.E. degree from the same institution in 2021. My research interests include privacy-preserving machine learning, natural language processing, AI for software security, and trustworthy AI. Currently, I am a visiting student at the School of Information and Communication Technology, Griffith University, working under the supervision of Prof. Leo Zhang and Prof. Yanjun Zhang.

Publications

You can also find my articles on my DBLP.

2025

• (DASFAA’25) Shuyu Chang, Rui Wang, Peng Ren, Qi Wang, Haiping Huang. A Large Language Model Guided Topic Refinement Mechanism for Short Text Modeling. In Proceedings of the 30th International Conference on Database Systems for Advanced Applications. URL: Arxiv

• (WWW’25) Rui Wang, Jiahao Lu, Xincheng Lv, Shuyu Chang, Yansheng Wu, Yuanzhi Yao, Haiping Huang, Guozi Sun. Mining User Preferences from Online Reviews with the Genre-aware Personalized neural Topic Model. In Proceedings of The Web Conference 2025. URL: OpenReview

• (WSDM’25) Rui Wang, Xing Liu, Yanan Wang, Shuyu Chang, Yuanzhi Yao, Haiping Huang. Mining Topics towards ChatGPT Using a Disentangled Contextualized-neural Topic Model. In Proceedings of the 18th ACM International Conference on Web Search and Data Mining. DOI: 10.1145/3701551.3703534

2024

• (TIFS) Shuyu Chang, Zhenqi Shi, Fu Xiao, Haiping Huang, Xingchen Liu, Chaorun Sun. Privacy-Enhanced Frequent Sequence Mining and Retrieval for Personalized Behavior Prediction. In IEEE Transactions on Information Forensics and Security. DOI: 10.1109/TIFS.2024.3391928
• (IPM) Rui Wang, Peng Ren, Xing Liu, Shuyu Chang, Haiping Huang. DCTM: Dual Contrastive Topic Model for identifiable topic extraction. In Information Processing & Management. DOI: 10.1016/j.ipm.2024.103785

2021

• (MONET) Shuyu Chang, Rui Wang, Haiping Huang, Jian Luo. TA-BiLSTM: An Interpretable Topic-Aware Model for Misleading Information Detection in Mobile Social Networks. In Mobile Networks and Applications. DOI: 10.1007/s11036-021-01847-w

Projects

• (2024 - Present) PhD Student Researcher. Open Fund of Provincial Key Laboratory, “Deep Learning-Based Smart Contract Vulnerability Detection and Robustness Assessment”
  • Role: Conceptualization, Formal analysis, Methodology
  • Tools: Python, Solidity, Pytorch, Prompt engineering, Adversarial attack and defense
• (2022 – 2024) PhD Student Researcher. OPPO, “Privacy-Enhancing Techniques in Machine Learning on Smartphones”
  • Role: Formal analysis, Methodology, Software
  • Tools: Java, Python, TensorFlow, Differential privacy, Federated learning, Machine learning

Skills

• Artificial Intelligence: Deep learning, Large language models, Prompt engineering, Topic modeling, Self-supervised learning, etc.
• Deep Learning Framework: PyTorch, HuggingFace transformers, Tensorflow (Part).
• Coding: Python, Java, C++.
• Privacy Protection: Federated learning, Differential privacy, Searchable encryption.
• Languages: Strong reading, writing, and basic English speaking competencies, Fluent Mandarin Chinese.
• Miscellaneous: LaTeX typesetting and publishing.