Use a QR Code reader on a mobile device to add this person as a contact:
Mohammad is a PhD candidate in the Department of Computing and Informatics, Bournemouth University, UK. He received his MSc in Informatics Engineering from Thishreen University, Syria. He worked as a teaching assistant at Thisreen University, Syria. His research is focused on the explainability and transparency of AI-based decision-making tools, i.e., the systematic design of explainability solutions for collaborative Human-AI decision-making environments.
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 is currently working on his PhD titled "A Design Method for Explainable AI Interfaces to enhance trust calibration" to guide designers and developers in enhancing trust calibration through XAI interface design.
Human-AI teaming and Explainable AI
- Naiseh, M., Cemiloglu, D., Althani, D., Jiang, N. and Ali, R., 2021. Explainable recommendations and calibrated trust: two systematic users’ errors. Computer.
- Naiseh, M., Althani, D., Jiang, N. and Ali, R., 2021. Explainable Recommendation: When Design meets Trust Calibration. World Wide Web Journal.
- Naiseh, M., 2020. Explainability Design Patterns in Clinical Decision Support Systems. In: The 14th International Conference on Research Challenges in Information Science 23-25 September 2020 Limassol, Cyprus. Proceedings - International Conference on Research Challenges in Information Science.
- Naiseh, M., Jiang, N., Ma, J. and Ali, R., 2020. Personalising explainable recommendations: Literature and conceptualisation. Advances in Intelligent Systems and Computing, 1160 AISC, 518-533.
- Aldhayan, M., Naiseh, M., McAlaney, J. and Ali, R., 2020. Online Peer Support Groups for Behavior Change: Moderation Requirements. Lecture Notes in Business Information Processing, 385 LNBIP, 157-173.
- Naiseh, M., Jiang, N., Ma, J. and Ali, R., 2020. Explainable Recommendations in Intelligent Systems: Delivery Methods, Modalities and Risks. Lecture Notes in Business Information Processing, 385 LNBIP, 212-228.
- Naiseh, M., 2021. Explainable recommendation: When design meets trust calibration – Research protocol. Bournemouth University.
- Naiseh, M., 2021. Explainable Recommendations and Calibrated Trust - Research Protocol. Bournemouth University.
Profile of Teaching UG
- Economics of Information Security
- Security Information and Event Management
- Ethical Hacking & Countermeasures
- Networks and Cyber Security
- PGR representative, SciTech Computing & Informatics Research
- Good Clinical Practice (GCP), 01 Nov 2019
- MSc in Master in Computer Science (2017)