Dr. Qin, Shengzhi

PhD HKU
Lecturer
 

 

Dr. Shengzhi Qin (Brian) received his Ph.D. in Cyber Security from The University of Hong Kong (HKU) in 2024, supervised by Dr. K.P. Chow, and his Bachelor of Engineering in Information Security from the University of Electronic Science and Technology of China (UESTC) in 2018. He is currently a Lecturer in the School of Computing and Data Science at HKU (Shanghai).

Dr. Qin’s research focuses on digital forensics and cybersecurity. His work includes anomaly detection in cyber-physical systems using transformer-based models, imbalanced malware detection, vulnerability knowledge graph reasoning, blockchain forensics, and cryptocurrency tracing. He serves as the organizing committee member for the International Digital Forensics Challenge (IDFC) and a full member of the Information Security and Forensics Society (ISFS).

Research Interests

Digital Forensics and Investigation, Internet of Things (IoT) Security, AI-Driven Security Data Analytics,  Blockchain Forensics

Selected Publications

• Qin, Shengzhi, and Kam-Pui Chow. “Improving Android Malware Detection in Imbalanced Data Scenarios.” IFIP International Conference on Digital Forensics, 2024.
• Shengzhi Qin, Yubo Lang, and K.P. Chow. “Traceable Transformer Based Anomaly Detection on Water Treatment System.” IFIP International Conference on Digital Forensics, 2023.
• Qin, Shengzhi, Qiaokun Wen, and Kam-Pui Chow. “Predicting the Locations of Unrest Using Social Media.” IFIP International Conference on Digital Forensics, 2021.
• Qin, Shengzhi, and K. P. Chow. “Automatic Analysis and Reasoning Based on Vulnerability Knowledge Graph.” Cyberspace Data and Intelligence, and Cyber-Living, Syndrome, and Health. Springer, 2019.