Kathrin Glau currently is a Lecturer in Financial Mathematics at Queen Mary University of London and a Fellow at EPFL (Ecole Polythechnique Federale Lausanne) co-funded by Marie Skłodowska-Curie. Between 2011 and 2017 she was Junior Professor at the Technical University of Munich. Prior to this she worked as a postdoctoral university assistant at the chair of Professor Walter Schachermayer at the University of Vienna. In September 2010 she completed her doctoral thesis on the topic of Feynman-Kac representations for option pricing in Lévy models at the chair of Ernst Eberlein.
Kathrin’s research in computational finance reaches across the borders of finance, stochastic analysis and numerical analysis. At the core of her current research is the design and implementation of complexity reduction techniques for finance. Key to her approach is the decomposition of algorithms in an offline phase, which is a learning step, and a fast and accurate online phase. The methods range from model order reduction of parametric partial differential equations to learning algorithms and are designed to facilitate such diverse tasks as uncertainty quantification and calibration, real-time pricing, real-time risk monitoring, and intra-day stress testing. For example she developed a pricing algorithm based on Magic Point Integration.
TUM Junior Fellow 2011-2017 EPFL Fellow co-funded by Marie Sk?odowska-Curie 2018-2019
