Dr. John Oyewole is a scholar, engineer, and educator specializing in industrial and systems engineering, decision analytics, operations research, and engineering management. He has over 8 years of experience teaching a wide range of undergraduate and graduate courses, mentoring research students, preparing grant applications, and contributing to curriculum development at various universities. His research combines optimization, predictive analytics, simulation modeling, and systems engineering methods to tackle real-world challenges in logistics, manufacturing, and transportation systems.
Dr. Oyewole earned his Ph.D. in Industrial Engineering, with his doctoral work focusing on the development of integrated facility-location and transportation optimization models. His research areas include predictive maintenance, electricity allocation optimization, and machine learning for intelligent decision systems.
With over a decade of combined academic and industry experience, Dr. Oyewole has served as a Senior Lecturer, Postdoctoral Fellow, and Supply Chain Officer. His industry background involves leading optimization and process improvement initiatives that increased efficiency and reduced downtime in manufacturing systems. In academia, he has taught and supervised undergraduate and postgraduate students across various courses, including operations research, decision support systems, facility planning, engineering management, and simulation modeling. He has effectively delivered both online and in-person lectures using various customized learning management systems, ensuring quality student engagement, assessment, and feedback.
Beyond research, he is passionate about mentoring emerging engineers and scientists and advancing sustainable, data-driven decision-making in engineering systems. For leisure, he enjoys watching TV news, playing chess and soccer, and playing the guitar and keyboard.
Dr. Oyewole earned his Ph.D. in Industrial Engineering, with his doctoral work focusing on the development of integrated facility-location and transportation optimization models. His research areas include predictive maintenance, electricity allocation optimization, and machine learning for intelligent decision systems.
With over a decade of combined academic and industry experience, Dr. Oyewole has served as a Senior Lecturer, Postdoctoral Fellow, and Supply Chain Officer. His industry background involves leading optimization and process improvement initiatives that increased efficiency and reduced downtime in manufacturing systems. In academia, he has taught and supervised undergraduate and postgraduate students across various courses, including operations research, decision support systems, facility planning, engineering management, and simulation modeling. He has effectively delivered both online and in-person lectures using various customized learning management systems, ensuring quality student engagement, assessment, and feedback.
Beyond research, he is passionate about mentoring emerging engineers and scientists and advancing sustainable, data-driven decision-making in engineering systems. For leisure, he enjoys watching TV news, playing chess and soccer, and playing the guitar and keyboard.