Our research group focuses on mathematical optimization, machine learning, and process systems engineering applications. We specialize in robust optimization techniques to address uncertainty in various decision-making processes. We leverage machine learning, specifically deep learning and physics-informed machine learning, to develop innovative solutions for data-driven modeling and optimization. Based on those, we explore process operations, production planning, supply chain optimization, process design, and control applications in various process systems.