Siu-Ming Yiu

Siu-Ming Yiu is affiliated with the University of Hong Kong in China and has an extensive research portfolio primarily in the field of Computer Science. Their work spans multiple subfields including Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Signal Processing, and Computational Theory and Mathematics.

Their recent scholarly output includes papers on diverse topics such as drug discovery, secure multi-party computation, privacy-preserving clustering, blockchain-based secret sharing, and insider threat prediction in forensic investigations. Notable publications include Compound-protein interaction prediction by deep learning: Databases, descriptors and models (2022) in Drug Discovery Today; Efficient two-party privacy-preserving collaborative k-means clustering protocol supporting both storage and computation outsourcing (2020) in Information Sciences; Fair hierarchical secret sharing scheme based on smart contract (2020) also in Information Sciences; Generic server-aided secure multi-party computation in cloud computing (2021) in Computer Standards & Interfaces; and Insider threat prediction based on unsupervised anomaly detection scheme for proactive forensic investigation (2021) in Forensic Science International Digital Investigation.

Their research covers key topics such as Cryptography and Data Security, Privacy-Preserving Technologies in Data, Computational Drug Discovery Methods, Blockchain Technology Applications and Security, Cryptographic Implementations and Security, Adversarial Robustness in Machine Learning, and Digital and Cyber Forensics.

Frequent coauthors who have collaborated extensively with them include Zoe L. Jiang, Jian-Yu Shi, Junbin Fang, Hui Yu, and Qianru Zhang.

Their publications have appeared repeatedly in venues such as arXiv (Cornell University), Expert Systems with Applications, Information Sciences, Forensic Science International Digital Investigation, and Frontiers in Microbiology, reflecting a broad engagement with interdisciplinary platforms.

• Compound-protein interaction prediction by deep learning: Databases, descriptors and models (2022, Drug Discovery Today)
• Efficient two-party privacy-preserving collaborative k-means clustering protocol supporting both storage and computation outsourcing (2020, Information Sciences)
• Fair hierarchical secret sharing scheme based on smart contract (2020, Information Sciences)
• Generic server-aided secure multi-party computation in cloud computing (2021, Computer Standards & Interfaces)
• Insider threat prediction based on unsupervised anomaly detection scheme for proactive forensic investigation (2021, Forensic Science International Digital Investigation)

• Zoe L. Jiang
• Jian-Yu Shi
• Junbin Fang
• Hui Yu
• Qianru Zhang

• arXiv (Cornell University)
• Expert Systems with Applications
• Information Sciences
• Forensic Science International Digital Investigation
• Frontiers in Microbiology

• Cryptography and Data Security
• Privacy-Preserving Technologies in Data
• Computational Drug Discovery Methods
• Blockchain Technology Applications and Security
• Cryptographic Implementations and Security
• Adversarial Robustness in Machine Learning
• Digital and Cyber Forensics