Summary
Kamil Jeřábek is a network security and AI researcher with 11 years of experience blending deep learning, representation learning and graph neural networks to advance network traffic analysis and cybersecurity. Based in Brno, he conducts post‑PhD research at FIT Brno University of Technology while working at CESNET and freelancing as a data scientist and consultant, helping organizations operationalize AI solutions and build data pipelines and compute clusters. His background includes hands‑on network engineering and kernel networking QA at Red Hat, long‑running involvement in RINASim/OMNeT++ simulation work, and international research stints at Strathmore and Liechtenstein—evidence of both practical systems expertise and academic rigor. He also teaches networking and forensics topics and holds an MBA alongside his PhD studies, bringing a rare mix of technical depth, teaching experience, and business perspective to applied research.
11 years of coding experience
6 years of employment as a software developer
ERASMUS+ Ph.D. Internship, ERASMUS+ Ph.D. Internship at University of Liechtenstein (Universität Liechtenstein)
Doctor of Philosophy - PhD, Information Technology, Doctor of Philosophy - PhD, Information Technology at Brno University of Technology, Faculty of Information Technology
Master of Business Administration - MBA, Master of Business Administration - MBA at University of St. Francis
ERASMUS+, ERASMUS+ at Strathmore University
Czech, English, Polish, Slovak