Matthias Seiss

Matthias Seiß is a Researcher at the University of Kassel's Faculty of Mathematics and Computer Science, Department of Algebra and Differential Equations. His research focuses on differential equations, algebraic geometry, and their applications in mathematical biology and systems theory. He has collaborated on topics such as singular initial value problems, chemical reaction network reduction, and differential Galois theory.

Seiß has taught courses like Mathematical Biology, Linear Algebra, and Differential Algebra, leading exercise sessions and seminars. His work bridges algebraic methods with computational and applied mathematics, addressing challenges in modeling biological systems and analyzing complex dynamical behaviors.

Key contributions include studies on Markov chain models, conservation laws in chemical networks, and numerical methods for singular equations. He is involved in projects like the Symbiont initiative, advancing symbolic computation in differential equations. His research has been published in journals such as SIAM Journal on Applied Dynamical Systems and Communications in Algebra.