Profile
Background
Dr. Kyriakopoulos research addresses adventurous cybersecurity challenges and underpins AI operations within Information & Operational Technology converged infrastructures. His work is in the intersection of cyber-physical environments and machine learning intelligence.
He has applied his research skills in autonomous decision making in cyber environments, Industry 4.0 environments (funded by Dstl and Innovate UK), smart vehicles (KTP), Electromagnetic Attacks (Dstl) and smart buildings (Industry funded). Specifically, he creates and leverages novel algorithmic approaches based on cutting-edge Machine Learning technology that drive autonomous decision making under uncertainty.
Besides using ML in cybersecurity, he also pushes the envelope in security for ML algorithms. He has published research work based on Evidence Theory to alter the algorithmic underpinnings of conventional ML algorithms in order to express their uncertainty when making decisions, which ultimately supports resilience and trustworthy ML. This leads to the creation of ML algorithms that are resilient to adversarial attacks, which is an area of increasing concern.
Finally, Dr. Kyriakopoulos has previously license research in defence sector companies and gained entrepreneurial skills for spinning-out developed research in threat modelling techniques. He has pitched the value proposition and business model to stakeholders and investors in Canary Wharf explaining the impact of his team’s solution to practitioners.