Michael Borth

Michael Borth is a seasoned Senior Research Fellow at TNO, with a career spanning over two decades in research and development. Borth previously held a similar position at ESI, where contributions included the formation of the Systems-in-Context team, focusing on embedded AI for cyber-physical systems, digital twins, and applied data science. Prior experience at Daimler involved advancements in E/E architectures and model-driven engineering, enhancing processes and tool chains in cooperation with Advanced Engineering and Mercedes-Benz Development. Borth holds a PhD and a diploma in Computer Science from Ulm University, with significant research achievements in data mining, particularly in developing standards like CRISP-DM and improving automotive safety and quality.