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6Recent Utrecht courses & seminars
4Current PhD researchers
40+Master’s & bachelor’s students
1Master’s track co-designed

Upcoming teaching

Courses in 2026–2027.

Planned Utrecht and national Mastermath teaching for the coming academic year.

01Spring 2027

Mastermath · M2 · 8 EC

Numerical Methods for Stochastic Differential Equations

A mathematically rigorous, computational course on numerical methods for Itô SDEs. It covers strong and weak approximation, Euler–Maruyama and Milstein schemes, error and complexity analysis, and Monte Carlo computation with variance reduction, quasi-Monte Carlo, importance sampling, and multilevel Monte Carlo, with introductions to stochastic control and connections to machine learning.

Mastermath course
02Fall 2026

Master’s course · Utrecht University

Mathematical (Sustainable) Finance and Risk Management

A rigorous, application-oriented course co-taught with Kees Oosterlee and Lech Grzelak. It connects stochastic modelling and risk theory with computational and data-driven methods for market, credit, operational, systemic, climate, and energy-market risks, including risk measures, fixed income, model validation, stress testing, and renewable-energy uncertainty.

UU course catalogue

Past Utrecht teaching

Courses and seminars previously taught.

Courses and seminars across bachelor’s, local master’s, national Mastermath, and summer-school settings.

01Fall 2024 & Spring 2026

Mastermath · M2 · 8 EC

Numerical Methods for Stochastic Differential Equations

Two earlier editions of the national Mastermath course on strong and weak SDE approximation, numerical error and complexity, Monte Carlo variance reduction, quasi-Monte Carlo, importance sampling, multilevel Monte Carlo, and introductory stochastic control.

Mastermath course
02Spring 2026

Master’s seminar · 7.5 EC

Stochastic Optimal Control: Theory, Numerics and Applications

A research seminar co-taught with Kees Oosterlee on the mathematical foundations, numerical approximation, and current applications of stochastic optimal control.

Course details
03Fall 2025

Master’s course · 7.5 EC

Mathematical (Sustainable) Finance and Risk Management

Co-taught with Kees Oosterlee and Lech Grzelak, the course develops financial risk modelling through stochastic methods, computation, and data, with topics spanning market and credit risk, tail-risk measures, fixed income, model validation, sustainable finance, climate stress, and energy markets.

Course details
042023–2025

Bachelor’s course

Programming for Mathematics

An introduction to programming for mathematics, emphasizing algorithmic thinking, Python implementation, and computational exploration of mathematical problems.

Course details
052024–2026

Bachelor’s course

Python and R

Scientific programming and data analysis in Python and R for students connecting mathematics with economics, modelling, and data science.

Course details
06Aug 2024

Summer-school mini-course

Introduction to Stochastic Modelling for Chemical and Biological Systems

An accessible introduction to stochastic reaction models, simulation algorithms, and the relation between stochastic and deterministic descriptions of chemical and biological systems.

Mini-course programme
2025

New master’s track

Mathematical & Computational Finance

Co-designer and coordinator of Utrecht University’s Mathematical and Computational Finance track, launched in Fall 2025. It brings mathematical finance, risk, stochastic modelling, numerical methods, machine learning, computation, and data science into a connected study path.

Explore the master’s track

Earlier teaching

Experience across institutions and levels.

2020–2023Instructor

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
  • Seminars in data science, uncertainty quantification, and multilevel Monte Carlo
Jun 2021Co-instructor with Nadhir Ben Rached

Helmholtz School for Data Science in Life, Earth and Energy

  • Uncertainty Quantification in a Nutshell: The Bayesian Framework for Inverse Problems

An intensive mini-course on Bayesian inverse problems, covering prior–likelihood–posterior modelling and computational methods including Markov chain Monte Carlo.

Mini-course details
2016–2020Teaching assistant

KAUST

  • Numerical Linear Algebra
  • Multivariate Statistics
  • Numerical Methods for Stochastic Differential Equations
  • Stochastic Methods for Engineers

Doctoral mentoring

PhD supervision

Four current PhD researchers, including one incoming visiting researcher, plus one completed doctorate and one completed visiting PhD project across Utrecht, KAUST, RWTH Aachen, SUSTech, and SWUFE.

Current · Supervisor2025–present · Utrecht University

Truong Nguyen

Efficient Computational Methods for XVAs and Risk Measures

Current · Co-supervisor2024–present · KAUST

Maksim Chupin

Scalable Numerical Methods for High-Dimensional Stochastic Reaction Network

Joint supervision with Raúl Tempone

Current · Co-supervisor2024–present · RWTH Aachen

Michael Samet

Data-Driven Modelling and Optimal Strategies in Renewable Energy Markets

Joint supervision with Raúl Tempone

Incoming · Host & academic supervisorNov 2026–Sep 2027 · Utrecht University

Kexin Shao

Efficient Simulation Algorithms in Finance: Methods and Applications

Visiting from Southern University of Science and Technology; funded by the China Scholarship Council

Completed visit · Host & co-supervisorSep–Dec 2023 · Utrecht University

Xianglin Wu

SigMA: Path Signatures and Multi-Head Attention for Learning Parameters in fBm-Driven SDEs

Joint supervision with Kees Oosterlee; visiting from the School of Mathematics, Southwestern University of Finance and Economics, China

Published research outcome
Completed · Co-supervisor2021–2024 · RWTH Aachen

Sophia Wiechert

Importance Sampling via Stochastic Optimal Control and Dimensionality Reduction

Joint supervision with Raúl Tempone

Postdoctoral Research Scientist, RWTH Aachen University

Thesis record

Selected student work

Projects shaped around real research questions.

A small selection from more than forty master’s and bachelor’s students and research-project participants.

01
Master’s thesis2025–2026

A Meyer Wavelet Fourier Method for Option Pricing

Jord van Eldik · Computational finance

02
Bachelor’s thesis2026

Neural Network Solutions to Stochastic Reaction Networks

Yoey Tolboom · Scientific machine learning

03
Bachelor’s thesis2026

Stochastic Approximation Methods for Multivariate Systemic Risk Measures

Lucas Beernink · Risk measurement

04
Orientation in Mathematical Research Project2025–2026

Machine Learning for Imbalanced Regression

Five-student team · Extreme events

05
Orientation in Mathematical Research Project2025

Signature Volatility Models in Quantitative Finance

Six-student team · Data-driven finance

06
Master’s thesis2024

Bayesian Hierarchical Models for Forecasting Student Enrolment Counts

Laura Robinson · Industry collaboration

Mathware Engineer, Sioux Technologies

Selected progression

Where former students and researchers continued.

Selected academic and professional destinations reported in the current CV.

01

Sophia Wiechert

PhD · stochastic optimal control and importance sampling

Postdoctoral Research Scientist, RWTH Aachen University
02

Maksim Chupin

Master’s thesis · dimensionality reduction in stochastic filtering

PhD candidate, KAUST
03

Michael Samet

Master’s thesis · Fourier pricing and hierarchical quadrature

PhD candidate, RWTH Aachen University
04

Laura Robinson

Master’s thesis · Bayesian forecasting of student enrolment

Mathware Engineer, Sioux Technologies
05

Yosr Samet

Master’s thesis · rough volatility models and option pricing

Quantitative Investment Strategist, Allianz Global Investors

The complete record includes doctoral supervision, master’s and bachelor’s theses, and Orientation in Mathematical Research projects; second-reader roles are listed separately in the CV and are not included here.

Full supervision record

For prospective students

Research projects that connect mathematics and computation.

Bachelor’s and master’s projects are tailored to the student’s background, programme requirements, interests, and available timeframe. Availability and scope vary by semester.

01

Computational finance & risk

Option pricing, multivariate risk, Fourier methods, Monte Carlo and quasi-Monte Carlo, rough volatility, and reliable numerical approximation.

Explore this research hub
02

Energy & power systems

Renewable-energy systems and markets, stochastic optimal control, reinforcement learning, storage, forecasting, and operational decisions under uncertainty.

Explore this research hub
03

Stochastic optimal control

Dynamic programming, numerical control, reinforcement learning, automated importance sampling, and decision-making under uncertainty in energy, power, finance, and stochastic systems.

Explore the research overview
04

Stochastic biochemical systems

Stochastic reaction networks, filtering, parameter inference, rare-event simulation, importance sampling, and multilevel computation.

Explore this research hub
05

Scientific machine learning & extremes

Structure-aware learning, parameter inference, imbalanced learning for rare and extreme events, reduced representations, and uncertainty-aware data-driven models.

Explore this research hub

Students can use the research hubs and publication record to understand the scientific context, then get in touch with their background, interests, and preferred timeframe.

Research hubs Publications Discuss a project

Postdoctoral funding opportunities

Develop a fellowship proposal together.

I welcome enquiries from prospective postdoctoral researchers interested in developing a Marie Skłodowska-Curie Actions (MSCA) Postdoctoral Fellowship proposal in stochastic numerics, uncertainty quantification, scientific machine learning, or their applications.

Please get in touch well in advance of the relevant deadline to discuss research fit and proposal development.

MSCA Postdoctoral Fellowships Discuss a proposal