Nature-Inspired Computing Paradigms in Systems

Prof. Mellal is a Professor at the Department of Mechanical Engineering, Faculty of Technology, M’Hamed Bougara University, Boumerdes, Algeria. He was temporarily associated with Teaching and Research (ATER) at the Department of Industrial Engineering and Maintenance, University Institute of Technology Louis Pasteur, University of Strasbourg, France. He is affiliated to the LMSS Laboratory (Solid Mechanics and Systems Laboratory, M’Hamed Bougara University, Algeria) and was affiliated to the Control, Vision and Robotics team of the ICube Laboratory (The Engineering Science, Computer Science and Imaging Laboratory, University of Strasbourg, France).Prof Mellal has contributed to papers on reliability and cost optimization of fuel cell systems, heat and power dispatch using flower pollination algorithms, and heterogeneous components in pharmaceutical production plants, among many others. 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