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.
13-04-20232022
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.
01-01-20222021
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.
26-06-20212020
An approach to construct a three-dimensional isogeometric model from μ-CT scan data with an application to the bridge of a violinMarschke S Wunderlich L Ring W Achterhold K Pfeiffer F
Computer Aided Geometric Design,
Elsevier vol. 78
01-03-20202019
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
Isogeometric shape optimization for nonlinear ultrasound focusingMuhr M Nikolić V Wohlmuth B Wunderlich L
Evolution Equations and Control Theory,
American Institute of Mathematical Sciences (Aims) vol. 8 (1), 163-202.
01-01-20192018
Numerical evaluation of discontinuous and nonconforming finite element methods in nonlinear solid mechanicsBayat HR Krämer J Wulfinghoff S Reese S Wohlmuth B
Computational Mechanics 23-03-20182017
Reduced Basis Isogeometric Mortar Approximations for Eigenvalue Problems in VibroacousticsHorger T Wohlmuth B Wunderlich L
In
Model Reduction of Parametrized Systems,
Springer Nature 91-106.
01-01-20172015
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
The Influence of Quadrature Errors on Isogeometric Mortar MethodsBrivadis E Buffa A Wohlmuth B Wunderlich L
Lecture Notes in Computational Science and Engineering. vol. 107, 33-50.
01-01-2015
Numerical methods for lambda quantiles: robust evaluation and portfolio optimisationPeri I Wunderlich L
Siam Journal on Financial Mathematics,
Society For Industrial and Applied Mathematics
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
Chebyshev Approximations and Neural Networks: a Hybrid Method For Parametric Risk Calculations
News
July 2026
15 July 2026
On Monday 13 July, we had the pleasure to host 36 school students from two schools, Barking Abby School (year 11) and Reach Academy Feltham (year 12) for a unique educational experience. The students were introduced to elements of statistical ecology and artificial intelligence via our novel interactive educational platform "From Pixels to Populations" ... [more]
