Person

Chiheb Ben Hammouda

Ph.D.
Chiheb Ben Hammouda
Lehrstuhl für Mathematics for Uncertainty Quantification

Adresse

Gebäude: 1953

Raum: 160

Pontdriesch 14-16

52062 Aachen

Kontakt

WorkPhone
Telefon: +49 177 51 177 82
 

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Postdoc an der RWTH Aachen, Promotion in Angewandter Mathematik und Computational Science und Diplomingenieur. Meine Forschungsexpertise ist eine Mischung aus mathematischer (stochastischer) Modellierung, numerischer Analyse und dem Entwurf und der Implementierung von rechnergestützten Simulationsmethoden.

 

Forschungsgebiete

  • Quantitative Finance
  • Computational Chemistry/Biology
  • Optimal Control for Renewable Energy
  • Uncertainty Quantification
  • Machine Learning
 

Publikationen

Veröffentlicht:

  • Bayer, C., Hammouda, C.B., and Tempone, R. “Hierarchical adaptive sparse grids and quasi-Monte Carlo for option pricing under the rough Bergomi model”. Quantitative Finance (2020): 20:9, 1457-1473. https://doi.org/10.1080/14697688.2020.1744700

  • Hammouda, C.B., Rached, N.B., and Tempone, R. “Importance sampling for a robust and efficient Multilevel Monte Carlo estimator for stochastic reaction networks”. Statistics and Computing (2020). https://doi.org/10.1007/s11222-020-09965-3

  • Hammouda, C.B., Moraes, A., and Tempone, R. “Multilevel hybrid split-step implicit tau-leap”, Numerical Algorithms (2017), 74(2):527-560. https://doi.org/10.1007/s11075-016-0158-z

Vorabdruck:

  • Bayer, C., Hammouda, C.B., Papapantoleon, A., Samet, M., and Tempone, R (2022). “Optimal Damping with Hierarchical Adaptive Quadrature for Efficient Fourier Pricing of Multi-Asset Options in Lévy Models”. ArXiv preprint arXiv:2203.08196. https://doi.org/10.48550/arXiv.2203.08196

  • Bayer, C., Hammouda, C.B., and Tempone, R. (2021) "Numerical Smoothing with Hierarchical Adaptive Sparse Grids and Quasi-Monte Carlo Methods for Efficient Option Pricing”. ArXiv preprint arXiv:2111.01874. https://doi.org/10.48550/arXiv.2111.01874

  • Hammouda, C.B., Rached, N.B., Wiechert, S., and Tempone, R. (2021) “Optimal Importance Sampling via Stochastic Optimal Control for Stochastic Reaction Networks.” ArXiv preprint arXiv:2110.14335. https://doi.org/10.48550/arXiv.2110.14335

  • Bayer, C., Hammouda, C.B., and Tempone, R. (2020) "Numerical smoothing and hierarchical approximations for efficient option pricing and density estimation”. ArXiv preprint arXiv:2003.05708. https://doi.org/10.48550/arXiv.2003.05708

Google Scholar: Dr. Chiheb Ben Hammouda

LinkedIn: Dr. Chiheb Ben Hammouda

 

Lehrtätigkeit

Co-Dozentin der folgenden Lehrveranstaltungen an der RWTH Aachen University:

  • Numerical Methods for Stochastic Differential Equations with Connections to Machine Learning.
  • Stochastic Numerics with Applications in Simulation and Data Science.
  • Numerical methods for Random Partial Differential Equations: Hierarchical Approximation and Machine Learning Approaches.