>30-year track record in the reliability domain. Application areas range from healthcare, gas and oil explorations, semiconductors and my current position in Philips Lighting where he is responsible for Solid State Lighting reliability. Besides that, he holds a professor position at the University of Delft, The Netherlands. His scientific interests are solid state lighting, microelectronics and microsystems technologies, virtual prototyping, virtual reliability qualification and designing for reliability of microelectronics and microsystems. He acts as the chair for the organizing committee of the IEEE conference EuroSimE and has authored and co-authored more than 350 scientific publications, including journal and conference papers, book or book chapters and invited keynote lectures. He holds 20 patents. He is a certified DFSS Black Belt.

Klaus Pressel received his PhD in Physics from the University of Stuttgart on research of point defects in III/V semiconductors. He then changed to IHP Frankfurt (Oder), where he focused on Si and SiGe design and technology. In 2001 Klaus joined Infineon Technologies at Regensburg, where he focuses now on innovations in assembly and packaging technology. His special interests are system integration, high frequency applications, and chip-package-board/system co-design. Throughout his carrier reliability of semiconductor devices played a major role. Klaus has been project leader of various European ECSEL JU and EUREKA projects. His ECSEL JU project ESiP, where reliability of SiP was a core topic, received the ECSEL JU innovation award in 2013. Klaus is representing Infineon in various international technical committees, e.g. SEMI Advanced Packaging Conference, IEEE ESTC conference, the Eureka XECS program, and supports the European ECS-SRIA as well as the IEEE Heterogenous Integration Roadmap. Klaus is author/co-author of more than 200 publications in semiconductor physics and technology, circuit design, assembly and interconnect technology and owns/co-owns more than 20 patents.

>100 SCI/SCIE journals, > 1000 conferences).

Chapter 1. Material characterization.- Chapter 2. Smart optical inline metrology.- Chapter 3. Automated classification of semiconductor defect density SEM images using deep learning.- Chapter 4. An Artificial Intelligence-based Framework for Burn-in Reduction in the Semiconductor Manufacturing Industry.- Chapter 5. An Artificial Intelligence-based Framework for Burn-in Reduction in the Semiconductor Manufacturing Industry.- Chapter 6. Early Lifetime Estimation for Automotive Lidar using Realistic L4 Usage Profiles.- Chapter 7. Improving the reliability of automotive sensors.- Chapter 8. Reliability improvements for in-wheel motor.- Chapter 9. Big Data Streaming and Data Analytics Infrastructure for Efficient AI-Based Processing.- Chapter 10. An Outlook on Power Electronics Reliability and Reliability Monitoring.- Chapter 11. Digital Twin Technology in Electronics.- Chapter 12. A Framework for Applying Data-driven AI/ML Models in Reliability. Chapter 13. Health monitoring fatigue properties of solder Interconnects in LED drivers.- Chapter 14. Compiling Hybrid Models for embedded architectures using TensorflowLite for Microcontrollers.- Chapter 15. Design support for reliable integrated circuits.- Chapter 16. Outlook: the future of reliability.