Student projects

Open projects

• PhD position, SHARE project. Physics-informed generative models for synthetic energy data, with real operational data from Alliander. Start February 2027, application deadline 25 October 2026. See also the SHARE page.
• Master thesis: benchmarking deep generative models for energy time series. Systematic comparison of VAEs, GANs, diffusion models, and Gaussian processes on open smart-meter datasets, with a focus on physical plausibility. Connected to the SHARE project. Get in touch if you are interested.
• Other Master thesis and internship projects, including those in collaboration with industry, are listed on our group page.

Interested in Gaussian processes, time series, graph neural networks, or applications in energy, weather and climate? Get in touch, there is often room to define an additional project on these topics.

Previous master thesis projects

• 2024 Benedetta Felici “State-space Wishart Processes for Multivariate Count Data Time Series Analysis”
• 2024 Susanne van de Logt “Delving Deep: Predictive modelling of the soil thermal resistivity for cable temperature modelling” (Joint with Alliander)
• 2024 Ylja van Son “Overview of Variational Sequential Monte Carlo for multivariate stochastic volatility models”
• 2023 Tijn Berns “Improving Scenario-Based Assessment Of Automated Vehicles Using Event Data” (Joint with TNO)
• 2023 Frederike Elsmann “Precipitation Nowcasting Exploring the Impact of Echo Top Heights in Generative Models”
• 2023 Nathan Golden “Edge Classification using Graph Neural Networks for the N-1 Assessment of Energy Grid Reliability” (Joint with Alliander)
• 2022 Charlotte Cambier van Nooten “Precipitation nowcasting for high-intensity events using deep generative models” (Joint with KNMI)
• 2022 Jaap Dijkstra “Graph Neural Networks for Grid Expansion” (Joint with Alliander)
• 2021 Luke Reijnen “Scaling Graph Convolutional Neural Networks” (Joint with ING)
• 2021 Koert Schreurs “Precipitation Forecasting from Radar Images with Generative Adversarial Networks” (Joint with KNMI)
• 2020 Bob de Ruiter “Multi-model Ensemble for Medium-Term Precipitation Using Convolutional Neural Networks” (Joint with KNMI)
• 2020 Sonja Fúllhase “Testing the n−1 principle with Graph Neural Networks” (Joint with Alliander)
• 2019 Sander ter Stege “Optimal Demand Forecasting in-practice”

Previous bachelor thesis projects

• 2018 Jaap Dijkstra “Gaussian Processes versus Autoregressive Wild Bootstrap: Climate Application”