Nature-Inspired Computing Paradigms in Systems

Mohamed Arezki Mellal is a Professor at M'Hamed Bougara University of Boumerdes, Algeria. He was ranked among the top 2% of scientists worldwide by Stanford University (single-year 2022) and placed first by the 47th National University Commission of the MESRS for the professorship in Mechanical Engineering in 2022. He served as a visiting scholar at the University of Maryland, USA, and at other universities. He has been an invited keynote speaker at numerous conferences and is an associate editor of Frontiers in Mechanical Engineering (Topic: Mechatronics) an SCIE-indexed journal. His research interests encompass AI techniques for solving engineering problems, including system design and dependability, control, energy management, robotics, and manufacturing. He is the founder and director of CALCE (Center for Advanced Life Cycle Engineering) at the University of Maryland, which is funded by over 150 of the world’s leading electronics companies at more than US$6M/year. He is a Professional Engineer, an IEEE Fellow, an ASME Fellow, an SAE Fellow, and an IMAPS Fellow. He is currently serving as editor-in-chief of Circuit World. He served as editor-in-chief of IEEE Access for 6 years, as editor-in-chief of IEEE Transactions on Reliability for 9 years, and as editor-in-chief of Microelectronics Reliability for 16 years. He has also served on three U.S. National Academy of Science studies, two U.S. Congressional investigations in automotive safety, and as an expert to the U.S. FDA. He is also a Chair Professor. He consults for 22 major international electronics companies, providing expertise in strategic planning, design, test, prognostics, IP and risk assessment of electronic products and systems.

• Optimization1. RAMS+C (reliability, availability, maintainability, safety and cost)2. Optimal design3. Diagnostic4. Resilience and vulnerability5. Prognostics and Health Management (PHM)6. Risk assessment and mitigation7. Faults8. Obsolescence9. Lifetime and lifecycle predictionMethods of interest include, but are not limited to10. Genetic algorithms11. Particle swarm optimization12. Differential evolution13. Cuckoo algorithms14. Artificial bee colony15. Ant colony optimization16. Artificial neural networks17. Brain18. Inspired computing19. Hybrid techniques