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The Intelligent Engineering Systems Lab develops computational and data-driven methods to understand, model, and control engineering systems. The group integrates physics-based modeling, machine learning, sensing, and simulation workflows to support reliable decision-making in research and field applications.
Modeling, monitoring, and decision-support methods for complex engineering systems.
Physics-informed and data-driven models for prediction, classification, and uncertainty-aware analysis.
Numerical simulation and scientific computing for materials, energy, and aerospace applications.
Sensor-driven data acquisition, visualization, and analytics for autonomous monitoring workflows.