Jaesung Lee

I am an Assistant Professor in the Department of Industrial & Systems Engineering (ISEN) at Texas A&M University. I received my Ph.D. in Industrial Engineering from the University of Wisconsin - Madison in 2022. 

My research focuses on data-driven models integrated with domain knowledge. My research interests lie in advanced statistical models and data mining methods to address critical challenges in advanced Engineering processes and systems, including emerging manufacturing processes and IoT-enabled connected systems. My research focuses on data-driven modeling, analysis, design and control of manufacturing/Engineering quality and process. In manufacturing domain, I have been establishing data-driven methods for monitoring, diagnosis, prognostics, and decision-making.

Specifically, my research topics include 

• Mathematical/probability modeling of complex Engineering processes and systems

• Uncertainty quantification along with prediction/inference

• Surrogate modeling to facilitate numerical simulation and enhance digital twins.

• Data-driven design/optimization of processes and products 

• Statistical process and quality control

• Nonparametric statistical modeling and machine learning methods

• Manufacturing system decision making.

Please see the research page for details.

If you want to discuss collaboration or research ideas, please feel free to email me (j.lee at tamu.edu).

If you are interested in a Ph.D. position, please email me (j.lee at tamu.edu) with your curriculum vitae and transcripts (undergraduate and Master's if applicable). Optionally, you can also provide your state of purpose and research publications/projects you worked on. Qualifications include strong mathematical and/or statistical backgrounds. Strong coding skills are preferred.

Link: (Google scholar) (Linkedin)