Jaesung Lee

Jaesung Lee is an Assistant Professor in the Department of Industrial & Systems Engineering at Texas A&M University. He holds a Ph.D. in Industrial & Systems Engineering from the University of Wisconsin-Madison (2022), an M.S. in Statistics from the same institution (2022), an M.S. in Management Engineering from KAIST (2013), and a B.S. in Industrial Systems & Information Engineering from Korea University (2011).

His research focuses on integrating domain knowledge with data science methodologies to address challenges in advanced engineering systems. Key areas include statistical modeling, machine learning, IoT-enabled systems, and smart manufacturing. He develops methods for process monitoring, diagnostics, and optimization, leveraging Bayesian approaches and Gaussian processes. Current projects involve physics-informed machine learning for bone stiffness estimation, reinforcement learning for maintenance policies, and collaborative research on inkjet-printed sensors.

Lee teaches courses like ISEN 350 (Quality Engineering) and ISEN 614 (Advanced Quality Control). His work emphasizes data-driven decision-making in manufacturing and healthcare systems. Collaborations include projects with Dr. Yuxiao Zhou and Ph.D. students T. Srikitrungruang and S Aghaee.