Dr Ismail Alarab
Senior Lecturer in Computer Science & AI
About
Ismail Alarab, (Meng, MSc, PGCert, PhD, FHEA) is a Senior Lecturer in Computer Science & AI at University of Chichester, with research interests in next-generation AI, including agentic and proactive AI systems, and autonomous and adaptive machine learning methods for healthcare, computing, and engineering applications. He completed his PhD in AI in December 2022, focusing on blockchain networks. He holds a PGCert in Higher Education (Bournemouth University), an MSc in Signal and Image Processing (Université Grenoble Alpes), and an MEng in Telecommunications (Lebanese University).
His teaching spans artificial intelligence, machine learning, programming, databases, mobile application development, and cloud computing. He integrates strong theoretical foundations with practical implementation, emphasising emerging technologies and real-world applications.
Dr Alarab has supervised undergraduate and postgraduate research projects in AI applications across blockchain, digital health, biomedical systems, and business analytics. He has published peer-reviewed research in international journals and IEEE conferences. He is actively engaged in applied AI research and industry collaboration, including a Knowledge Transfer Partnership (KTP) and a Community Diagnostics Centre (CDC) initiative in partnership with NHS Trusts.
Teaching
- Artificial Intelligence
- Machine Learning
- Cloud Computing and Big Data
- Programming
- Mobile Applications Development
- Databases
- Mathematics for Computer Graphics
- Data Processing and Analytics
- Blockchain
External Responsibilities
- KTP (Co-I) – Intelligent moderation and assistance for commercial image sharing website Videscape t/a ClickASnap (Innovate UK, 2025) – In Progress
- IEEE Transactions on Knowledge and Data Engineering – Reviewer
- Elsevier, Neural Networks – Reviewer
- Non-visiting External Examiner, University of Malta (2024/2025)
Publications
Journals
- Alarab, I. et al. (2023). Graph-based LSTM for anti-money laundering in Bitcoin networks. Neural Processing Letters.
- Alarab, I. et al. (2022). Adversarial attack for uncertainty estimation in neural networks. Multimedia Tools and Applications.
- Alarab, I. et al. (2022). Effect of data resampling in imbalanced blockchain data. Data Science and Management.
Conferences
- Alarab, I. et al. (2020). Graph convolutional networks for anti-money laundering in Bitcoin blockchain. ICMLC 2020.
- Alarab, I. et al. (2020). Comparative analysis of supervised learning for AML detection. ICMLC 2020.
- Xu, W., Alarab, I. et al. (2022). VR football match re-enactment using AI agents. IEEE AI & Virtual Worlds Conference.
Book chapters
- Nacer, M.I., Prakoonwit, S., Alarab, I. (2021). AI, blockchain and IoT for patient relationship management.
- Nacer, M.I., Prakoonwit, S., Alarab, I. (2021). Blockchain as complementary technology for IoT: A survey.
External Profiles
Google Scholar: Google Scholar | Ismail Alarab
ORCID Profile: https://orcid.org/0000-0001-8320-6423
Research
Dr Alarab’s current research focuses on autonomous AI, XAI, and applied AI solutions for real-world deployment, especially in healthcare. His earlier work explored uncertainty estimation, explainable AI, adversarial robustness, and graph-based learning (GNN) models in blockchain analytics and healthcare applications.
He is currently part of collaborative research initiative with local NHS Trusts through a Community Diagnostics Centre (CDC) at the Bognor Regis campus, to support interdisciplinary research in medical diagnostic and healthcare innovation.
PhD supervision interests
PhD supervision interests include agentic AI systems, applied AI solutions with real-world impact, and healthcare-focused AI applications (Currently accepting PhD students).
Prospective PhD applicants are welcome to contact me to discuss potential research opportunities: i.alarab@chi.ac.uk
Other department members
