How can technical systems be optimized and industrial production be improved? Which investment portfolio should be chosen? How can massive data sets be analyzed and processed efficiently and what does "efficient" actually mean?Such questions are central for the research training group "Applied Algorithmic Mathematics", paying tribute to the fact that in a technical world aiming at the efficient use of resources the quantitative description of technical and economical processes plays a major role.Methods for modeling and analyzing practical problems and developing suitable algorithms are provided by mathematics and related areas of computer science, of course in close collaboration with scientists working at the "industrial front end". The research training group is based in the department of mathematics at the Technische Universität München. Also colleagues from the computer science department and from the department of philosophy, philosophy of science, and statistics at the Ludwig-Maximilians-Universität München are involved. Research in the research training group "Applied Algorithmic Mathematics" can roughly be divided into the areas Applied Analysis, Applied Geometry, Discrete Mathematics, Computer Science, Numerical Analysis and Stochastics. Special emphasis is placed on stochastic and discrete models for problems concerning the analysis, processing and visualization of massive data. Key areas of application include financial economy, material and medical science.
DFG Programme
Research Training Groups
