The goal of the research group is to develop models and solutions to the general problems in the area of process systems engineering (PSE) using presciptive analytics techniques, such as mathematical programming and machine learning. Specifically, we are interested in three main categories of problems: optimal process design, optimal process operations, and robust supply chain network design. The models and algorithms developed in the group can be used in applications such as enterprise-wide process optimization (EWO), development of optimal carbon utilization paths, and resilient hydrogen supply chain networks design. We are an ambitious group, and we aim to influence the core decision-making of organizations of different scales, ranging from small teams in an enterprise to national organizations.