Institute of Process Systems Engineering

Our research combines physics-based modeling, materials engineering, advanced experimentation, and data-driven methods to develop predictive solutions for complex process systems. By integrating these complementary approaches, we advance the design, optimization, monitoring, and control of sustainable industrial processes and functional materials.

We develop constitutive and multiphase models for complex fluids and implement them in open-source CFD frameworks such as OpenFOAM for large-scale simulations. Together with thermodynamic modeling and machine learning, these simulations provide detailed insight into fluid flow, heat and mass transfer, multiphase transport, and process performance, enabling more efficient and reliable engineering solutions.

A second major research area is the development of sustainable functional materials, with a particular focus on bio-based materials and environmentally benign synthesis routes. By combining material development with multiscale characterization, we establish structure–processing–property relationships that enable the rational design of materials with tailored mechanical, rheological, and functional properties.

Advanced rheological testing and in-situ characterization provide detailed insight into structural evolution across multiple length and time scales. Integrated with numerical simulations, sensor technologies, and machine learning, these experiments enable predictive material models, intelligent process monitoring, digital twins, and advanced process control.

Teaching is a core mission of our institute. We offer undergraduate and graduate courses in numerical methods, process design, process simulation, process data analytics, and related disciplines. Our goal is to provide students with a rigorous engineering foundation while equipping them with the computational, analytical, and digital skills needed to address the challenges of modern process engineering in industry, research, and academia.