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
2025
Function approximations for counterparty credit exposure calculationsDemeterfi D Glau K Wunderlich L
In
Arxiv 11-07-20252023
Neural network expression rates and applications of the deep parametric PDE method in counterparty credit riskGlau K
Annals of Operations Research,
Springer Nature vol. 336 (1-2), 331-357.
13-04-2023 2022
The deep parametric PDE method and applications to option pricingGlau K Wunderlich L
Applied Mathematics and Computation,
Elsevier vol. 432
01-11-2022 Hybrid Discretizations in Solid Mechanics for Non-linear and Non-smooth ProblemsBayat HR Krämer J Reese S Wieners C Wohlmuth B Wunderlich L
In
Non-Standard Discretisation Methods in Solid Mechanics,
Springer Nature 1-35.
01-01-2022 2021
Forecasting the Olympic medal distribution – A socioeconomic machine learning modelSchlembach C Schmidt SL Schreyer D Wunderlich L
Technological Forecasting and Social Change,
Elsevier, 121314-121314.
12-11-2021 Machine Learning for Business StudentsWunderlich L Higgins A Lichtenstein Y
Proceedings of the 26th ACM Conference on Innovation and Technology in Computer Science Education V. 1., 512-518.
26-06-2021 2019
A hybrid isogeometric approach on multi-patches with applications to Kirchhoff plates and eigenvalue problemsHorger T Reali A Wohlmuth B Wunderlich L
Computer Methods in Applied Mechanics and Engineering,
Elsevier vol. 348, 396-408.
01-05-2019 Biorthogonal splines for optimal weak patch-coupling in isogeometric analysis with applications to finite deformation elasticityWunderlich L Seitz A Alaydın MD Wohlmuth B Popp A
Computer Methods in Applied Mechanics and Engineering,
Elsevier vol. 346, 197-215.
01-04-2019 2018
Numerical evaluation of discontinuous and nonconforming finite element methods in nonlinear solid mechanicsBayat HR Krämer J Wulfinghoff S Reese S Wohlmuth B
Computational Mechanics 23-03-2018 2015
Trace and flux a priori error estimates in finite-element approximations of Signorni-type problemsSteinbach O Wohlmuth B
Ima Journal of Numerical Analysis,
Oxford University Press (OUP) vol. 36 (3), 1072-1095.
24-07-2015 Isogeometric mortar methodsBrivadis E Buffa A Wohlmuth B
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
EPSRC additional skills funding summer 2025Akram Alomainy,
Iran Roman, Ella Rice,
Maria Liakata,
Simon Dixon, Giorgio Chianello,
Andrew Livingston,
Kostas Papafitsoros,
Silvia Liverani,
Eleni Matechou and
Linus Wunderlich£180,000
Engineering and Physical Sciences Research Council 
01-10-2025 - 31-03-2026 Efficient interpolation of the implied volatilityKathrin Glau and
Linus Wunderlich£10,800
Numerical Algorithms Group Ltd01-11-2018 - 31-01-2019
Research Group
PhD Students
- Ivelina Mladenova
Deep Learning in Finance: Mathematical Foundations and Applications - Athanasios Polychronou
Data-Driven Image Processing Methods With Applications to Wildlife Conservation - Xiaocheng Wei
Solving Complex Dynamical Systems in Finance: Mathematical Foundations and Applications
