r. Mohammed Al Awadh is an Associate Professor of Industrial Engineering at King Khalid University with extensive experience in applied research, academic supervision, and consulting across the domains of quality engineering, safety management, reliability analysis, and AI-driven industrial systems. His research focuses on developing data-driven decision-support models to improve performance, safety, and sustainability in engineering and service sectors.

He has led and co-authored numerous studies integrating statistical modeling, machine learning, and multi-criteria decision-making (MCDM) techniques for industrial optimization and educational performance analysis. His recent work includes the AI-Driven Model for Optimizing Airport Queuing Systems, presented at the 15th IEOM International Conference (Singapore, 2025), and the application of Principal Component Analysis (PCA) and Cluster Analysis to evaluate national student performance data.

Dr. Al Awadh’s research extends to predictive maintenance, TQM and EFQM excellence models, occupational safety and fire prevention systems, and digital transformation frameworks. He frequently collaborates with industry and government entities to translate research into practical solutions aligned with Saudi Vision 2030.

He employs advanced tools such as SPSS, R, Python, and Minitab to conduct reliability analysis (Weibull), ANOVA, DOE, SEM, and PCA, and actively mentors graduate and undergraduate students in applied research and innovation projects.