Dr Farshid Keivanian is a PhD-qualified academic and researcher in computer science and information technology, with experience in university teaching, curriculum development, assessment design, research supervision, and applied research.

His research focuses on explainable and trustworthy artificial intelligence, machine learning, cybersecurity, intelligent optimisation, Edge AI, cyber-physical systems, Internet of Things (IoT), and secure intelligent systems. His work particularly explores interpretable and multi-objective AI methods for complex decision-making problems, including applications in healthcare, engineering, cybersecurity, IoT, and data analytics.

At the University of Technology Sydney (UTS), he contributes to teaching and assessment within the School of Computer Science, Faculty of Engineering and Information Technology, including software development and programming subjects.

He has published research in journals including Neurocomputing, Expert Systems with Applications, Journal of Computational Science, PLOS ONE, Electronics, and SpringerPlus, and has contributed to IEEE conferences and an Elsevier book chapter.

He is also actively involved in academic publishing and peer review, including service as an Associate Editor and Guest Editor, and as a reviewer for international journals in artificial intelligence and computational intelligence.