Ph.D. student Tatthapong Srikitrungruang was selected as a finalist in the 2026 INFORMS QSR Best Student Paper Competition. Tatthapong will present this work at the 2026 INFORMS Annual Meeting in San Francisco. Congratulations, Tatthapong!
Data Science Lab
Texas A&M University Industrial & Systems Engineering
My research establishes domain-informed statistical and machine learning methods for engineering systems under uncertainty. I integrate physical laws and other domain knowledge with imperfect data to infer unobserved system properties, quantify uncertainty, and enable prediction and decision-making.
Jaesung Lee
Assistant Professor
Industrial & Systems Engineering
Research focus
My current research focuses on Bayesian modeling and uncertainty quantification, physics-informed machine learning for inverse problems, and digital twin systems. These methods are applied to critical problems in advanced manufacturing and healthcare and biomechanics, including patient-specific prediction and evaluation, inference of heterogeneous physical properties, prognostics and reliability, and data-driven engineering decision-making.
- Domain-informed statistical machine learning and uncertainty quantification
- Bayesian inference and physics-informed machine learning for inverse problems
- Digital twins and predictive analytics
- Prognostics, reliability, and decision-making under uncertainty
- Applications in advanced manufacturing and healthcare/biomechanics
Research directions
010203
AI for Engineering Systems
Monitoring, diagnostics, prognostics and decision-making for complex engineering systems.
AI for Engineering Processes
Data-driven modeling, quality control and optimization for advanced engineering processes.
Physics-Informed AI
Physics-informed inference of heterogeneous physical properties from noisy observations.
Latest news
Dr. Lee served as a panelist at the Doctoral Student Colloquium, sharing advice with doctoral students preparing for academic careers.
Tatthapong received second place in the ISEN Best Presentation Competition organized by the INFORMS Student Chapter at Texas A&M University.
Prospective Students & Collaborators
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 statement of purpose and research publications/projects you worked on. Qualifications include strong mathematical and/or statistical backgrounds. Strong coding skills are preferred.
j.lee@tamu.eduJaesung 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.
Education
- PhD 2022Industrial & Systems EngineeringUniversity of Wisconsin–Madison, Madison, WI
- MS 2020StatisticsUniversity of Wisconsin–Madison, Madison, WI
- MS 2013Management EngineeringKAIST, Seoul, South Korea
- BFE 2011Financial EngineeringKorea University, Seoul, South Korea
- BS 2011Industrial Systems Information EngineeringKorea University, Seoul, South Korea
Courses taught
- ISEN 350 Quality Engineering
- ISEN 614 Advanced Quality Control
- DAEN 210 Uncertainty Modeling
- I have developed and offered DAEN 210 for the Data Engineering program newly offered by the department.
Research Interests & recognition
- Advanced Statistical modeling and data mining methods in the application of advanced Engineering processes and systems.
- Data-driven modeling, analysis, design, and control of emerging advanced manufacturing processes
- Data-driven analytics for IoT-enabled smart manufacturing, service, and healthcare systems
Research Recognition
- Recognized as a top-viewed article, Advanced Materials Technologies, 2023.
- Featured Article in ISE Magazine, IISE, 2022
Awards and Honors
- 2025–26 Montague-Center for Teaching Excellence (CTE) Scholar, Texas A&M University, 2025
- University-wide recognition for excellence and innovation in undergraduate teaching (includes a $6,500 teaching grant)
- QSR Best Referred Paper Competition Finalist, INFORMS Annual Meeting, 2025
- QCRE Student Paper Competition Finalist (Ph.D. Student: Sina Aghaee), IISE Annual Conference & Expo, 2025
- IISE Transactions Best Paper Award, IISE, 2024
- Best paper award, Management and Innovation Technology International Conference, 2015
- Best Master’s Thesis Award, KAIST, 2013
Industry & funding partners
My research group has been working with industry collaborators and supported by multiple institutions:
Industrial Research Collaborators:
- EOS North America, 3Degrees
Funding Partners:
- NSF, NIH, LIFT, U.S. Department of War/Defense, TAMIDS, Crider Foods