Oguz Toragay

In 2022, I graduated with a Ph.D. from Industrial and Systems Engineering Department at Auburn University in Auburn/AL. I hold a M.Sc. degree in Industrial Engineering from Gazi University in Turkey and a B.Sc. degree in Applied Mathematics from Khayyam University in Iran. In Fall 2022 I started my career as a tenure-track Assisatnt Professor at the A. Leon Linton Department of Mechanical, Robotics, And Industrial Engineering at Lawrence Technological University in Detroit/MI.


During my Ph.D., I involved in a couple of projects. In collaboration with Mechanical Engineering and National Center for Additive Manufacturing Excellence (NCAME) at Auburn University, we worked on applications of various optimization methods to optimize the design of lightweight structures for Additive Manufacturing (AM). We proposed a new mathematical model for the complex problem of designing lightweight planar frame structures using Mixed Integer Quadratically Constrained Programming approach. Our paper, presenting the proposed idea, is under review with one of the major journals in the field, “Structural and Multidisciplinary Optimization Journal”.

Lightweight structures have applications in aerospace, automotive and medical fields for which having an optimized design is highly important. In our research, we tackle this engineering problem and I believe our contributions will have significant impact in the field. I am currently working on applications of Heuristic and Metaheuristic methods to solve large-scale design problems for AM. My research is impactful in terms of bringing the optimization methods and AM closer.

As a side-project, I worked on the applications of Markov Decision Process in the admission control to secure systems. In this task, we considered a system where requests for authentication come from several customer classes, where each class has a known impostor probability. The system has several authentication servers, characterized by error probabilities and operating costs. The objective is to balance security and user experience. We developed a novel heuristic approach to solve the problem in dramatically reduced solving time compared to the classical MDP solving methods. Using this approach we generated the optimal server assignment policy for authentication systems which could not be otherwise solved due to curse of dimensionality. This paper has been published in “Applied Stochastic Models in Business and Industry”.

For more details about my research topics and my current work, visit the “Research” tab.


For more comprehensive information about my teaching experience, kindly navigate to the “Teaching” section located at the top of this webpage. It contains detailed insights and specifics regarding my background in teaching.