Publications
AI-Driven Digital Twins in Modern Manufacturing
An inside look at how BMW leverages Digital Twins and real-time data to enable intelligent decision-making, scalable AI systems, and next-generation manufacturing excellence.
Prof.Dr. Ahmed Ebada Research Publications
Ebada is a professor, researcher, and an entrepreneur based in Munich, Germany. He has been working in industrial research. His research includes IoT, edge, wearables, biosensors, AI, speech recognition, cloud computing, big data analysis, robotics, and Entrepreneurship. He has served as an Associate Editor and peer reviewer for IEEE, Elsevier, and Springer Nature. His motto is that science is a way to improve people's lives, neither a tool for philosophy nor fame.
Jury Member – Automotive Testing Technology International (since 2025)
As a member of the judging panel for Automotive Testing Technology International, one of the world’s leading platforms in automotive technology and testing. Being part of this distinguished group of international experts reflects a long-standing journey in Artificial Intelligence, Digital Twins, and industrial innovation.I am proud to contribute my expertise to evaluating cutting-edge technologies and supporting the future of the automotive industry.
Digital Twins Evolution
Digital Twins have evolved from simple visualization tools into intelligent, data-driven systems that replicate real-world behavior. Digital Twins are used across development, production, and end-of-life simulation, enabling real-time validation, predictive insights, and continuous optimization.
