Dr Farzad Arabikhan
Summary
I am currently a Senior Lecturer at the School of Computing, University of Portsmouth. In my PhD, I used Artificial Intelligence techniques (Complex Fuzzy Rule-Based Networks and Genetic Algorithm) to develop a predictive model for adopting Telecommuting. I gained an MSc in Transportation Systems and Planning at the Sharif University of Technology, Tehran, Iran.
Research interests
- Computational Intelligence (Fuzzy Logic, Rule-Based Systems, Neural Networks and Genetic Algorithm)
- Intelligent Transportation Systems
- Activity Based Transport Modelling
Teaching responsibilities
I am currently involved as unit coordinator, lecturer and tutor in the following units:
- Practical Data Science
- Computer Architecture
- Network Fundamentals
I am also unit facilitator for the off-campus units:
- Transportation Engineering
- Design of Transportation Infrastructure
Research outputs
2025
Explainable AI for federated learning-based intrusion detection systems in connected vehicles
Taheri, R., Jafari, R., Arabikhan, F., Gegov, A., Ichtev, A.
18 Nov 2025, In: Electronics. 14, 22, 18p., 4508
Research output: Article
Trustworthy and reliable AI for heart disease diagnosis: advancing ethical and explainable healthcare decision-making
Gogi, G., Gurung, S. K., Gegov, A., Arabikhan, F., Ichtev, A.
14 Nov 2025,
Research output: Conference contribution
Explainable artificial intelligence for intrusion detection in connected vehicles
Taheri, R., Gegov, A., Arabikhan, F., Ichtev, A., Georgieva, P.
10 Nov 2025,
Research output: Conference contribution
Unveiling vulnerabilities in deep learning-based malware detection: Differential privacy driven adversarial attacks
Taheri, R., Shojafar, M., Arabikhan, F., Gegov, A.
1 Oct 2025, In: Computers and Security
Research output: Article
Evaluating project manager competencies using explainable artificial intelligence
Nejad, A. A. F., Arabikhan, F., Gegov, A., Ichtev, A.
3 Sep 2025,
Research output: Conference contribution
Data-driven predictive modelling of agile projects using explainable Artificial Intelligence
ForouzeshNejad, A. A., Arabikhan, F., Gegov, A., Jafari, R., Ichtev, A.
1 Jul 2025, In: Electronics (Switzerland). 14, 13, 25p., 2609
Research output: Article
Machine learning-based prediction of Clostridium growth in pork meat using explainable artificial intelligence
Ince, V., Bader-El-Den, M., Alderton, J., Arabikhan, F., Sari, O. F., Sansom, A.
21 Jan 2025, In: Journal of Food Science and Technology, 109421
Research output: Article
2024
Optimizing project time and cost prediction using a hybrid XGBoost and simulated annealing algorithm
Forouzesh Nejad, A. A., Arabikhan, F., Aheleroff, S.
1 Dec 2024, In: Machines. 12, 12, 25p., 867
Research output: Article
Agile project status prediction using interpretable machine learning
Forouzesh Nejad, A. A., Arabikhan, F., Williams, N. L., Gegov, A., Sari, O. F., Bader-El-Den, M.
9 Oct 2024,
Research output: Conference contribution
Machine learning approach into bacterial relationship: exploring 16S rRNA metabarcoding with association rule mining
Sari, O. F., Bader-El-Den, M., Ince, V., Arabikhan, F.
9 Oct 2024,
Research output: Conference contribution