Simon Iwan Stingelin

Dr. Simon Iwan Stingelin is a Lecturer in Mathematics at the Institute of Applied Mathematics and Physics (IAMP) within the School of Engineering at Zurich University of Applied Sciences (ZHAW). His work focuses on scientific computing and algorithmics, with particular expertise in numerical methods and mathematical modeling.

Dr. Stingelin's research interests span multiple domains of applied mathematics and computational science. He specializes in modeling and numerical simulation with emphasis on electrodynamics, fluid dynamics, and mechanics. His work also encompasses optimal control of partial differential equations and model reduction techniques. As an educator, he teaches advanced courses in numerical analysis and higher mathematics, with a focus on practical applications in engineering.

His publication record demonstrates expertise across computational mathematics, fluid dynamics, and control theory. Recent work includes Bayesian analysis of NMR spectra, modeling of peristaltic pumps considering viscoelastic materials, and teaching methodologies for finite element methods using NGSolve. His research shows a consistent trajectory from theoretical mathematical problems to practical engineering applications, with publications spanning from foundational mathematical problems to applied engineering solutions.

Dr. Stingelin leads and contributes to multiple research projects including

• Raman for Process Analytics (Deputy Project Leader, ongoing)
• Automatic Counting of Varroa Mites in Bee Colonies (Project Leader, completed)
• Position Error Correction Algorithm (Team Member, completed)
• SCIS Simulation Based Calibration of Infusion Systems (Team Member, completed)
• Optical Gas Sensor with Ceramic Cell (Team Member, completed)

His teaching approach emphasizes hands-on computational methods, particularly through the use of NGSolve for finite element analysis. He has developed course materials that integrate Jupyter notebooks and interactive learning environments to teach Higher Analysis and Numerics to engineering students across multiple disciplines including Computer Science, Mechanical Engineering, Electrical Engineering, Systems Engineering, and Aviation.