An effective research program in the systems area is necessarily interdisciplinary in nature. Systems engineering overlaps with applied mathematics and computer science and applications of systems engineering can be found in almost any engineering discipline as well as in physics, biology, and the life sciences. The main focus of our research is on developing novel systems engineering techniques for, and applying sophisticated methods to, complex dynamic systems in order to understand their function up to the point that predictions about future behavior under different conditions are possible. The systems under study range from applications in systems biology and medicine to traditional chemical engineering processes.
Our research group focuses on two general areas: One is the development of new techniques for systems analysis (e.g., sensitivity analysis, experimental design, parameter estimation, or model reduction) with an emphasis on methods for nonlinear systems and/or significant levels of uncertainty in the model. The second general area is the application of these techniques to specific biochemical systems, such a signal transduction or metabolic pathways, to investigate biomarkers for diseases with poorly understood pathophysiology, but also to processes in the chemical process industries that are characterized by complex physicochemical interactions. Work in all application areas is always performed in close collaboration with other research groups or industry as it is essential to combine any modeling approach with experimental, clinical, or plant data.
Strong interactions exist between the "methods" and the "application" areas in our group, as certain applications drive the need for new techniques to be developed, while at the same time, it becomes possible to answer specific questions about a system due to newly developed methods. One particularly intriguing aspect is that new systems analysis techniques can be used for different applications with only minor modifications.