A complete record of
research and scholarship.

Ben Hammouda, C., Chupin, M., Münker, S., & Tempone, R. (2026). Filtered Markovian Projection: Dimensionality Reduction in Filtering for Stochastic Reaction Networks. Statistics and Computing, 36, Article 189. https://doi.org/10.1007/s11222-026-10939-0

Wu, X., Ben Hammouda, C., & Oosterlee, C. W. (2026). SigMA: Path Signatures and Multi-Head Attention for Learning Parameters in fBm-Driven SDEs. Neurocomputing, 682, 133499. https://doi.org/10.1016/j.neucom.2026.133499

Hermans, T. H. J., Ben Hammouda, C., Treu, S., Tiggeloven, T., Couasnon, A., Busecke, J. J. M., & van de Wal, R. S. W. (2025). Computing Extreme Storm Surges in Europe Using Neural Networks. Natural Hazards and Earth System Sciences, 25(11), 4593–4612. https://doi.org/10.5194/nhess-25-4593-2025

Ben Hammouda, C., Rezvanova, E., von Schwerin, E., & Tempone, R. (2024). Lagrangian Relaxation for Continuous-Time Optimal Control of Coupled Hydrothermal Power Systems Including Storage Capacity and a Cascade of Hydropower Systems with Time Delays. Optimal Control Applications and Methods, 45(5), 2279–2311. https://doi.org/10.1002/oca.3155

Bayer, C., Ben Hammouda, C., & Tempone, R. (2024). Multilevel Monte Carlo with Numerical Smoothing for Robust and Efficient Computation of Probabilities and Densities. SIAM Journal on Scientific Computing, 46(3), A1514–A1548. https://doi.org/10.1137/22M1495718

Ben Hammouda, C., Ben Rached, N., Tempone, R., & Wiechert, S. (2024). Automated Importance Sampling via Optimal Control for Stochastic Reaction Networks: A Markovian Projection-Based Approach. Journal of Computational and Applied Mathematics, 446, 115853. https://doi.org/10.1016/j.cam.2024.115853

Bayer, C., Ben Hammouda, C., Papapantoleon, A., Samet, M., & Tempone, R. (2023). Optimal Damping with Hierarchical Adaptive Quadrature for Efficient Fourier Pricing of Multi-Asset Options in Lévy Models. Journal of Computational Finance, 27(3), 43–86. https://www.risk.net/journal-of-computational-finance/7958695/optimal-damping-with-a-hierarchical-adaptive-quadrature-for-efficient-fourier-pricing-of-multi-asset-options-in-levy-models

Ben Hammouda, C., Ben Rached, N., Tempone, R., & Wiechert, S. (2023). Learning-Based Importance Sampling via Stochastic Optimal Control for Stochastic Reaction Networks. Statistics and Computing, 33, Article 58. https://doi.org/10.1007/s11222-023-10222-6

Bayer, C., Ben Hammouda, C., & Tempone, R. (2022). Numerical Smoothing with Hierarchical Adaptive Sparse Grids and Quasi-Monte Carlo Methods for Efficient Option Pricing. Quantitative Finance, 23(2), 209–227. https://doi.org/10.1080/14697688.2022.2135455

Bayer, C., Ben Hammouda, C., & Tempone, R. (2020). Hierarchical Adaptive Sparse Grids and Quasi-Monte Carlo for Option Pricing under the Rough Bergomi Model. Quantitative Finance, 20(9), 1457–1473. https://doi.org/10.1080/14697688.2020.1744700

Ben Hammouda, C., Ben Rached, N., & Tempone, R. (2020). Importance Sampling for a Robust and Efficient Multilevel Monte Carlo Estimator for Stochastic Reaction Networks. Statistics and Computing, 30(6), 1665–1689. https://doi.org/10.1007/s11222-020-09965-3

Ben Hammouda, C., Moraes, A., & Tempone, R. (2017). Multilevel Hybrid Split-Step Implicit Tau-Leap. Numerical Algorithms, 74, 527–560. https://doi.org/10.1007/s11075-016-0158-z

Trevisani, D., López-Salas, J. G., Ben Hammouda, C., & Oosterlee, C. W. (2026). A Damped SWIFT Method for European Option Pricing: Coefficients Decay, Truncation, and Error Analysis. arXiv preprint arXiv:2607.21109. https://doi.org/10.48550/arXiv.2607.21109

Ben Hammouda, C., Samet, M., & Tempone, R. (2026). Data-Driven Stochastic Optimal Control for Intraday Electricity Trading by Renewable Producers. arXiv preprint arXiv:2604.27700. https://doi.org/10.48550/arXiv.2604.27700

Ben Hammouda, C., & Nguyen, T. N. (2026). Single- and Multi-Level Fourier-RQMC Methods for Multivariate Shortfall Risk. arXiv preprint arXiv:2602.06424. https://doi.org/10.48550/arXiv.2602.06424

Bayer, C., Ben Hammouda, C., Papapantoleon, A., Samet, M., & Tempone, R. (2024). Quasi-Monte Carlo for Efficient Fourier Pricing of Multi-Asset Options. arXiv preprint arXiv:2403.02832. https://doi.org/10.48550/arXiv.2403.02832

Ben Hammouda, C. (2020). Hierarchical Approximation Methods for Option Pricing and Stochastic Reaction Networks [Doctoral dissertation, King Abdullah University of Science and Technology]. https://repository.kaust.edu.sa/items/a1115d4e-a162-44b6-a6dd-f348280253ef

Ben Hammouda, C. (2015). Drift-Implicit Multi-Level Monte Carlo Tau-Leap Methods for Stochastic Reaction Networks [Master’s thesis, King Abdullah University of Science and Technology]. https://repository.kaust.edu.sa/items/2c6b5e98-2d43-45e9-a837-28b02d5fa3bb

Ben Hammouda, C. (2013). Numerical Methods for Uncertainty Quantification in Option Pricing [Bachelor’s thesis, École Polytechnique de Tunisie].

Ben Hammouda, C., Chen, Y., Denic, D., Jacobs, T., & Sanders, P. (2025). Tackling Multicollinearity in Marketing Mix Models: A Bayesian Hierarchical Shrinkage Approach. Scientific Proceedings of the Study Group Mathematics with Industry 2025. https://www.swi-wiskunde.nl/swi2025/wp-content/uploads/sites/30/2025/07/SWI-2025-scientific-proceedings-Opella.pdf