Eva Flonner
Vienna University of Economics and Business
Eva Flonner is a researcher and lecturer specializing in financial mathematics and quantitative finance. She earned her PhD in Mathematics in Economics and Business from Vienna University of Economics and Business in 2025, where her dissertation on neural stochastic differential equations and stochastic filtering in finance was awarded the Dr. Maria Schaumayer prize. Her work bridges theoretical mathematical aspects with real-world financial applications, focusing on Bayesian methods, models under partial information, and optimal portfolio strategies. She is especially interested in marriage of approximation theory and machine learning in finance. Eva Flonner presented her research at international conferences and workshops. Beyond research, Eva Flonner is an experienced and passionate educator, and she has worked on industry projects in equity research, ESG scoring, and digital finance transformation.
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Articles by Eva Flonner
Robust financial calibration: a Bayesian approach for neural stochastic differential equations
This paper offers a Bayesian framework for the calibration of financial models using neural stochastic differential equations.