About me

My background sits across two worlds that don't often meet: hands-on industrial automation (PLC ladder logic, Modbus, OPC-UA) and applied machine learning. Most of my work has been about closing that gap — taking real machine telemetry and turning it into something a control system can act on.

During my internship at Meshnet Electronics, I built real-time IoT monitoring systems using ESP32, OPC-UA, and Modbus for smart manufacturing, and developed ML-based predictive monitoring to support downtime reduction. On the side, I built a full Industry 4.0 simulation — the Smart Factory M221 AI/ML System — to explore how a virtual PLC, industrial protocols, and an ML service can form one closed control loop.

I'm now formally extending this into autonomous systems through an MSc at TH Ingolstadt, with the same throughline: instrumenting industrial and embedded systems, then adding the intelligence layer on top.