I am currently a postdoctoral researcher at the CWI (Centrum Wiskunde & Informatica) in Amsterdam. My research interests are in the domain of machine learning, applied probability, and partial differential equations. My current focus is on the theoretical aspects of neural networks, understanding how and why they work, and their applications in mathematical finance and engineering.
I obtained my PhD cum laude from the University of Bologna in Financial Mathematics as part of the Marie-Curie Industrial Doctorates and Horizon2020 project WakeUpCall under the supervision of Prof. Andrea Pascucci and Prof. Cornelis W. Oosterlee. I have obtained my Master's degree in Quantitative Finance at the VU Amsterdam and my Bachelor's degree in Applied Mathematics from the Delft University of Technology.
Machine learning (Neural networks, Gaussian processes, Bayesian modelling), Applied probability(Stochastic processes, Interacting Particle Systems), Partial Differential Equations, Financial mathematics
My current work in machine learning:
Understanding neural networks: loss surface structure; generalisation bounds; optimization algorithms; the links between neural networks and PDEs; neural networks in a limiting setting (Gaussian process behavior, interacting particle systems)
Applications of neural networks in financial applications and engineering applications: solving PDEs; time series forecasting, option pricing, calibration
May 2019 "Generalization in fully-connected neural networks for time series forecasting" got accepted to the ICML Time Series Workshop
May 2019 "The effects of optimization on generalization in infinitely wide neural networks" got accepted to the ICML Workshop on Understanding and Improving Generalization in Deep Learning
March 2019 "Generalization in neural networks for time series forecasting" will be presented at the SIAM Conference on Financial Mathematics and Engineering in Toronto, Canada, June 2019