Dr Leishi Zhang


NameDr Leishi Zhang
Job titleReader in Computing
Research instituteSchool of Engineering, Technology and Design

Research outputs

Investigating the security issues of multi-layer IoMT attacks using machine learning techniques

Al Sukhni, B., Manna, S., Dave, J. and Zhang, L. 2022. Investigating the security issues of multi-layer IoMT attacks using machine learning techniques.

Designing a system to mimic expert cognition: An initial prototype

Hepenstal, Sam, Zhang, Leishi and William Wong, B. L. 2022. Designing a system to mimic expert cognition: An initial prototype. Proceedings of the Human Factors and Ergonomics Society Annual Meeting. 66 (1), pp. 2057-2061. https://doi.org/10.1177/1071181322661092

An analysis of expertise in intelligence analysis to support the design of human-centered artificial intelligence

Hepenstal, S., Zhang, L. and Wong, BL William 2021. An analysis of expertise in intelligence analysis to support the design of human-centered artificial intelligence. https://doi.org/10.1109/SMC52423.2021.9659095

Automated identification of insight seeking behaviours, strategies and rules: a preliminary study

Hepenstal, S., Zhang, L. and Wong, BL William 2021. Automated identification of insight seeking behaviours, strategies and rules: a preliminary study. Sage Journals: Proceedings of the Human Factors and Ergonomics Society Annual Meeting . (65), pp. 1269-1273. https://doi.org/https://doi.org/10.1177/1071181321651348

Developing conversational agents for use in criminal investigations

Hepenstal, S., Zhang, L., Kodagoda N. and Wong B.L.W 2021. Developing conversational agents for use in criminal investigations. ACM Transactions on Interactive Intelligent Systems. 11 (3-4), pp. 1-35. https://doi.org/10.1145/3444369

A granular computing approach to provide transparency of intelligent systems for criminal investigations

Zhang, L. 2021. A granular computing approach to provide transparency of intelligent systems for criminal investigations. in: Pedrycz, W. and Chen, S.-M. (ed.) Interpretable Artificial Intelligence: A Perspective of Granular Computing Cham Springer.
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