Adrian Pekar is a Senior Data Scientist and research-trained engineer with nine years of experience bridging academia and industry across Europe and New Zealand. He blends deep expertise in machine learning, network measurement, virtualisation and data-centre automation with proven leadership in R&D and team management, regularly translating complex technical ideas for non-technical stakeholders. His work spans applied research—postdoctoral and professorial roles at Victoria University and Budapest University of Technology—and production ML at CUJO AI®, delivering measurable operational gains such as dramatic VM provisioning speed-ups and data reduction methods for network flows. Adrian’s publications and technical projects emphasize practical solutions: anomaly detection, flow compression via auto-encoders, and adaptive aggregation that reduced IPFIX records by 28%. Comfortable working autonomously or leading teams, he brings a rare combination of hands-on systems engineering and rigorous academic methodology.
8 years of coding experience
12 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Technical University of Kosice, Slovak Republic
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