Teaching

I have been involved in the follow

• Machine Learning (2025): Teacher and lab sessions coordinator for this Bsc. AI course
• Data Mining Techniques (2024): Coordinator of this Msc. AI course
• Machine Learning & Reasoning in Health (2023-current): Guest lecturer for this Msc. AI course

I have helped organise the Reinforcement Learning Summer School, read more in this blog post.

Below is an overview of Bsc. and Msc. thesis projects I have supervised. In case you are interested in my notes on thesis supervision, read more in this blog post.

Msc theses

2024

• Cas Oude Hoekstra, “Symbolic Quantile Regression”
• Jakub Lewkowicz, “Multi-Objective Reinforcement Learning for Portfolio Allocation”
• Lisa Beek, “Multi-objective Deep Reinforcement Learning for Workforce Planning”
• Yassin ben Allal, “The application and benefits of applying Reinforcement Learning in Slate Recommender Systems”
• Marcia van der Poel, “Personalized advice for Diabetes Type 2 management using Machine Learning”

before 2024

• Haritha Jayaraman, “Estimating the value of a policy based on a guideline based metric using OPE”
• Stefan Petrescu, “Rethinking Log Parsing in the Context of Modern Software Ecosystems”
• Yannick Smit, “Strategic Workforce Planning with Deep Reinforcement Learning”
• Michal Nauman, “Low-Variance Policy Gradient Estimation with World Models”
• Azamat Omuraliev, “Reinforcement Learning for Controllable Text Summarization”
• Mickey van Zeelt, “Gathering External Evaluations on Chatbot Conversations”
• Tim Nederveen, “Reducing Expert Interference in Time Series Anomaly Detection Model Re-evaluations”
• Rob Wanders “Predicting Number of Transactions with Echo State Networks”
• Luca Simonetto “Generating Spiking Time Series with Generative Adversarial Networks: an Application on Banking Transactions”
• Ilse Goedhart “Predicting IT Performance using Quantile Regression”

Bsc theses

2024

• Angel Valencia Orama, Dylan Feteridge & Eduardo Tomasi Kruel, “Human-centered Gameplaying with Deep Reinforcement Learning”
• Luigi Tisci, “Reinforcement Learning from Human Feedback for Workforce Optimization”

before 2024

• Daniel van der Riet, “Safe Reinforcement Learning with a Learned Transition Function”
• Claudia-Violeta Grigorias, “Learning safe behaviours with dynamic hyperparameters in Reinforcement Learning”