I am a Junior Researcher at the Chair of IT Security. I hold a Master's degree in Digital Communications Networks from the University of Leeds in the United Kingdom, where I conducted research on a study titled “Congestion Testbed for Low Power and Lossy Networks”. I later continued my studies and earned a Master's degree in Business Administration (MBA) from EIDHI International University, USA. I have also participated in industry roles for several years. My expertise encompasses consultancy, implementation, and project management across diverse domains, including Public Key Infrastructure (PKI), Network Security, and Internet of Things (IoT). I hold certifications in CCNA R&S, CCNA Security, and NSE Fortinet.

My research area focuses on Intrusion Detection Systems (IDS) for Critical Infrastructures, more specifically on the application of artificial intelligence (AI) and machine learning (ML) methods to traffic analysis.

I am currently contributing to the KISS_KI project. Our aim is to develop and test self-learning attack detection algorithms for network monitoring in industrial control systems. To achieve this, I am focused on evaluating and refining our artificial intelligence (AI)-based anomaly detection system. This process enables us to attain optimal results in detecting potential threats on critical infrastructures.