Postdoctoral researcher
University of Verona
Deep learning methods for BSDEs with non-standard features, with applications to mathematical finance and risk management.
Curriculum vitae
Research in stochastic control, numerical methods, and mathematical finance.
Research experience
Postdoctoral researcher
Utrecht University
Convergence of deep learning methods for coupled FBSDEs and development of methods that address convergence failures.
PhD research
CWI · TU Delft / Utrecht University
Neural networks for stochastic control and decision making in mathematical finance.
Education
PhD
Utrecht University
Neural networks for stochastic control and decision making in mathematical finance.
MSc in Engineering Mathematics
Chalmers University of Technology
Thesis: Approximate stochastic control based on deep learning and FBSDEs.
Undergraduate degree in Engineering Mathematics
Chalmers University of Technology
Thesis: Simulations of Cox–Ingersoll–Ross processes.
Awards & recognition
SIAM High Impact Article Recognition
Convergence of a robust deep FBSDE method for stochastic control, SIAM Journal on Scientific Computing.
Best Youngster Presenter Award
International Conference on Computational Finance, Wuppertal.
Academic service
Referee for journals including:
- SIAM Journal on Scientific Computing
- Journal of Machine Learning Research
- Annals of Applied Probability
- Automatica
- Applied Mathematics and Computation
- Applied Numerical Mathematics
- Annals of Operations Research
- IMA Journal of Numerical Analysis
Technical background
Python for scientific computing, stochastic simulation, and deep learning; TensorFlow and Keras; MATLAB and R. Additional experience with FEniCS, Java, and C.
Languages: Swedish (native) and English (fluent).