Xenia Mountrouidou
Xenia Mountrouidou

Principal Cyber Data Scientist

Xenia Mountrouidou is a Principal Cyber Data Scientist at Expel with versatile experience in academia and industry. She has over 10 years of research experience in network security, machine learning, and data analytics for computer networks. She enjoys researching novel intrusion detection techniques, finding interesting patterns with machine learning algorithms, and writing Python scripts to automate boring tasks. Her research interests revolve around network security, Internet of Things, intrusion detection, and machine learning.

She has authored scholarly papers in the areas of network security and machine learning. She has presented her work at academic and industry conferences such as USENIX Security, IEEE Big Data, BSides Security, and Interop.

Download CV
Interests
  • Machine Learning for Security
  • Intrusion Detection Systems
  • Network Security
  • IoT Security
  • Data Science
Education
  • PhD in Computer Science

    North Carolina State University

  • M.S. in Computer Engineering

    University of Patras

  • B.S. in Computer Science

    University of Crete

đź“š My Research
I am a researcher at the intersection of machine learning and security, focusing on harnessing ML to detect abnormal system behavior and enhance defenses against evolving threats. I am particularly passionate about developing robust, secure ML models and exploring how generative AI (GAI) can unlock new opportunities for security detection and automation. My primary research interests include network security and machine learning, where I work on innovative solutions to protect modern cyber ecosystems.
Selected Publications
(2021). IoT Metrics and Automation for Security Evaluation. In IEEE CCNC 2021.
(2021). Worth the wait? Time window feature optimization for intrusion detection. In IEEE Cyberhunt 2019.
Recent & Upcoming Talks
Recent Posts