Dr Petar Radanliev obtained his Ph.D at University of Wales in 2014 and continued with Post-Doctoral research at Imperial College London, Massachusetts Institute of Technology, the University of Cambridge and the University of Oxford.
Dr Radanliev was a Prince of Wales Innovation Scholar - 2010/2013 and Fulbright Visiting Fellow - 2017.
His current research is oriented around identifying a dynamic and self-adapting system supported with Artificial Intelligence/Machine Learning and real-time intelligence for predictive cyber risk analytics, integrated into a cognition engine for edge computing which uses machine learning to automate anomaly detection.
This research work is to secure the edge by predicting cyber risk loss magnitude through dynamic analytics of cyber-attack threat event frequencies. Significantly the challenges Dr Radanliev's project addresses are socio-technical, relating strongly to technology, regulation, economics, interventions, and directly relates to industries and their supply chains and control systems. For example he is investigating the perceptions of risk and trustworthiness that emerge as a result of machine agency, which interact with regulation, standards and policy on the one hand and design and engineering on the other, spanning the physical and behavioural sciences.
This research is funded by the Cisco Research Centre and by the PETRAS|EPSRC National Centre of Excellence for loT Systems Cybersecurity.