Stochastic control & games
Numerical methods for stochastic optimal control and differential games, with a focus on coupled forward–backward stochastic differential equations (FBSDEs), convergence, and time-inconsistent decision problems.
Research
My work connects stochastic analysis and numerical methods with machine learning, developing algorithms and studying when and why they converge.
Deep learning for stochastic equations
Deep learning algorithms for backward stochastic differential equations (BSDEs) and backward stochastic Volterra integral equations (BSVIEs), including problems with jumps, path dependence, and non-standard features.
Computational finance
Applications to portfolio optimization, derivative valuation, exposure profiles, and valuation adjustments (xVA), connecting numerical algorithms with problems in financial risk management.
Preprints
Google ScholarConvergence of fictitious play for fully coupled FBSDEs in finite-player stochastic differential games
arXiv:2607.08861 · Preprint
Multi-Layer Deep xVA: Structural Credit Models, Measure Changes and Convergence Analysis
arXiv:2502.14766 · Preprint
Publications
Most recent firstA Deep Solver for Backward Stochastic Volterra Integral Equations
SIAM Journal on Scientific Computing 48(2), C359–C384
The Deep Multi-FBSDE Method: A Robust Deep Learning Method for Coupled FBSDEs
Journal of Scientific Computing 106(3), article 77
On deep portfolio optimization with stocks, bonds and options
Journal of Computational Finance 29(1)
The One Step Malliavin scheme: new discretization of BSDEs implemented with deep learning regressions
IMA Journal of Numerical Analysis 44(6), 3595–3647
Convergence of a Robust Deep FBSDE Method for Stochastic Control
SIAM Journal on Scientific Computing 45(1), A226–A255
Deep learning for CVA computations of large portfolios of financial derivatives
Applied Mathematics and Computation 409, article 126399
A deep learning approach for computations of exposure profiles for high-dimensional Bermudan options
Applied Mathematics and Computation 408, article 126332
Doctoral thesis
Applied collaborations
Saab
Stochastic differential games and their applications to defense systems.
MN Asset Management / TU Delft
Development and back-testing of an optimal-execution model with Cornelis W. Oosterlee, including analysis of simulated slippage and liquidity across trading venues.
Syntronic
Machine learning research.