My research interests lie in industrial data science, statistics, artificial intelligence (AI), and nonlinear optimization for energy, manufacturing, and other 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 enhance automation and improve process control in hybrid and smart manufacturing systems. Ongoing research directions include:

• AI-driven digital twins for complex engineering systems
• IoT-enabled data science and AI for improving quality and reliability in large-scale engineering systems

Methodologies

Design and analysis of computer experiments, statistical machine learning, nonlinear optimization, survival analysis, and AI.

Applications

Digital twin calibration, quality and reliability engineering, and operational decision-making.