About me

I work at the intersection of computer networks, data systems, and applied machine learning. My focus is understanding network behavior at scale and turning raw telemetry into information that is measurable, interpretable, and operationally useful, with particular interest in uncertainty, data quality, and decision-making in real monitoring systems.

I am a research engineer and PhD candidate at the Faculty of Information Technology, Czech Technical University in Prague and CESNET. In practice, I build systems that run continuously and handle large volumes of data, such as high-throughput flow processing pipelines, telemetry collectors, time-ordered databases, and analysis workflows combining classical statistics with modern machine learning.

My tech stack: Nix/OS (❤️), Grafana, Clickhouse, Kafka, C++, Python

Current research interests: active learning, network flows embeddings