My research interests lie in data science, statistics, AI, and nonlinear optimization for complex engineering systems. To date, I have focused on developing digital twin calibration methodologies for energy systems such as building energy and wind power systems. In parallel, I have advanced data science techniques to improve process diagnosis and control in manufacturing systems. Ongoing research directions include:

• AI-driven digital twins in biomanufacturing systems
• Medical image processing using diffusion models

Methodologies

Design and analysis of computer experiments (sequential design and Bayesian optimization), diffusion models, nonlinear optimization, survival analysis, data assimilation, machine learning.

Applications

Digital twin calibration, online learning and adaptive control, transfer learning, quality and reliability engineering, operational decision-making.

Domains

Energy systems (building energy and wind power), manufacturing systems (biomanufacturing and materials), healthcare systems (medical image processing)