We advance enabling technologies designed to enhance predictive modeling, automation, and real-time decision-making for complex chemical, biological, energy, and food systems!

​

The research in our lab focuses on developing intelligent frameworks and the corresponding computational tools needed for

• Controlling complex process networks,

• Applied artificial intelligence in chemical, biological, and energy systems,

• Designing cyber-physical architectures for smart process manufacturing,

• Advancing system identification using machine learning and process data analytics.

Most of our work is computational, but we are intensely interested in laboratory automation to test hypotheses, validate model predictions, and design autonomous experiments.