Gabriel Lipnik
Gabriel Lipnik is an AI engineer and applied mathematician working on production-grade machine learning, artificial intelligence, and optimisation systems. His work focuses on bridging the gap between advanced models and real-world deployment, with a particular interest in MLOps, trustworthy AI, and regulatory-ready ML systems.
He has contributed to large-scale optimization and AI projects in the mobility and infrastructure domain, where reliability, traceability, and operational robustness are critical.
Gabriel is particularly interested in practical approaches to making machine learning systems more transparent, monitorable, and production-ready.
Session
The EU AI Act is often seen as a legal concern, but many of its requirements directly affect everyday ML workflows. This talk shows data scientists and ML engineers where the regulation impacts the machine learning lifecycle and presents concrete, low-overhead patterns to make ML systems more AI Act–ready, without slowing down development.