The AI lab at TPM strives to take students and enthusiasts onboard when and where possible. This page provides information about AI related MSc. thesis topics, internships, research assistantships and AI-related courses. These courses are within the faculty, at our university, other Dutch universities and also online. If you have any ideas or questions, feel free to share them with us through this email:

AI master specialization

Research assistantships

Note that there is a possibility to propose your own ideas about internships or thesis topics. If you want more information, have questions or want to share your ideas, feel free to reach us through our email address, or make an appointment to discuss it together.

Yasin Sarı

Title of project: SMASH: An open-source python library for smart direct policy search
Supervised by: Jazmin Zatarain Salazar

Start date 11-08-2021
End date 11-12-2021


The goal of the internship is to develop a Python implementation of the smart direct policy search (SMASH) framework to develop and test multi-objective policy design. AI-based routines will be enabled within the framework to systematically test competing policy formulations. An existing source code in C++ will be utilized as the basis for the Python implementation. A couple of examples from the domain of water policy will also be integrated to the framework as example test cases. The SMASH platform will contribute to the long-term ambition of developing a suite of open-source Python libraries for AI based decision support. 


Jonas Lechner

Title of project: Machine Learning in Agent Based Modelling
Name of company: TPM AI Lab

Start date 08-11-2021
End date 28-01-2022


The field of agent-based modelling and simulation (ABMS), a bottom-up simulation method where agents interact and make decisions, has shown tremendous growth in the last decades. At the same time, the ABMS models became more and more complicated, which led to certain research challenges for ABMS such as preparing the input data or making large-scale models more effective. Research proposes that Machine Learning (ML) can help in overcoming these challenges. My research internship focused on exactly this intersection of ML in ABMS. At the TPM AI Lab a team of experienced researchers has already started studying this research field and constructed a paper draft on the usage of ML techniques in ABMS. My main task within the internship was to assist in the finalization of the paper by bringing in a fresh and creative perspective.

Felicity Reddel

Title of project: Agent-Based Misinformation Modeling Internship
Name of company: Ministry of the Interior and Kingdom Relations

Start date 30-08-2021
End date 19-12-2021


In my internship, I am trying to support the Ministry of the Interior and Kingdom Relations by creating an agent-based model of misinformation on social media. Policymakers need to prioritize between different intervention options. However, estimating the effect that a policy might have on a large group of people is difficult – especially if there are uncertain external factors in the mix. A well-validated agent-based model can help here because it makes it possible to explore the effects of interventions under different conditions. Thus, it is a cost-effective and safe way to gather evidence for evidence-based decision making. I am designing and implementing a model which will enable such exploration. Furthermore, the model is aimed to be easily extendable. As such, it will hopefully offer an easy entry point for others to investigate other research questions around misinformation on social media and aid the search for robust interventions.

AI related courses

/* */