- Dr Naiseh has an interdisciplinary profile putting together academic and professional practice expertise in both Artificial Intelligence (AI) and Human-Computer Interaction (HCI). His main research interest is in the domain of trustworthy autonomous systems and in particular on explainability, interpretability and fairness of AI systems.
- Dr Naiseh looks at methods, tools, and approaches to bridge the gap between the technical side of AI technologies and human-centred design practices. He uses quantitative and qualitative research approaches to provide recommendations for the design of safe and trustworthy autonomous systems.
Explainable Machine Learning
Machine Learning/ Deep Learning
Mohammad Naiseh is a Post-doctoral Research Fellow in human-AI interaction and interface design. He is interested in how the explainability and transparency of AI systems can enhance the performance of the human-AI team. His current work addresses virtual assistants in automated vehicles, clinical decision support systems and human-swarm teaming in UAV operations.
Mohammad has a keen interest in studying user trust, which he defines as a crucial requirement of deploying AI-based solutions in real-world problems as it has dynamic nature (over-trust and under-trust). He focuses on the principles, methods and tools needed to engineer trust-aware technology to calibrate trust in such technologies.
He works in the Trustworthy in Autonomous Systems Hub (TAS-hub), led by Prof. Sarvapali D. (Gopal) Ramchurn, investigating how autonomous systems can operate to benefit, rather than harm society, and in doing so facilitate appropriate trust.
He received his PhD from the Department of Computing and Informatics at Bournemouth University with a thesis titled: C-XAI: Design Method for Explainable AI Interfaces to Enhance Trust Calibration.
Mohammad has served as a Reviewer/PC/AC member for the Persuasive Technology Conference, DARS, BESC, CHI, INTERACT and organiser of the workshop series on Human-AI Interaction. He is also a reviewer in many top international journals such as the International Journal of Human-Computer Studies, Journal of Reasonable Technology, Nature Scientific Reviews and Information Systems journal.