Dr Linus Wunderlich
Lecturer in Financial Mathematics
School of Mathematical Sciences
Queen Mary University of London
Research
Mathematical foundation of AI, Deep Neural Networks, Option Pricing, Counterparty Credit Risk, Chebyshev Interpolation, Deep parametric PDE method
Interests
Linus' research combines machine learning with numerical techniques in mathematical finance. His work includes solving high-dimensional PDEs with neural networks and accelerated risk computations using Chebyshev interpolations. His research interest extends to the mathematical understanding of artificial intelligence and their wider applications.
Publications

Publications of specific relevance to the Centre for Probability, Statistics and Data Science
2023

Glau K and
Wunderlich L (2023).
Neural network expression rates and applications of the deep parametric PDE method in counterparty credit risk. Annals of Operations Research,
Springer, 1-27.
13-04-20232022
Wunderlich L and Glau K (2022).
The Deep Parametric PDE Method and Applications to Option Pricing. Applied Mathematics and Computation,
Elsevier 02-07-20222021

Schlembach C, Schmidt SL, Schreyer D and
Wunderlich L (2021).
Forecasting the Olympic medal distribution – A socioeconomic machine learning model. Technological Forecasting and Social Change,
Elsevier, 121314-121314.
12-11-20212018

Bayat HR, Krämer J,
Wunderlich L, Wulfinghoff S, Reese S, Wohlmuth B and Wieners C (2018).
Numerical evaluation of discontinuous and nonconforming finite element methods in nonlinear solid mechanics. Computational Mechanics 23-03-20182015

Steinbach O, Wohlmuth B and
Wunderlich L (2015).
Trace and flux a priori error estimates in finite-element approximations of Signorni-type problems. IMA Journal of Numerical Analysis,
Oxford University Press (OUP) vol. 36 (3), 1072-1095.
24-07-2015
Brivadis E, Buffa A, Wohlmuth B and
Wunderlich L (2015).
Isogeometric mortar methods. Computer Methods in Applied Mechanics and Engineering,
Elsevier vol. 284, 292-319.
01-02-2015
Grants

Grants of specific relevance to the Centre for Probability, Statistics and Data Science
Efficient interpolation of the implied volatility 
Kathrin Glau and
Linus Wunderlich£10,800
Numerical Algorithms Group Ltd01-11-2018 - 31-01-2019