Logo Utrecht University

Nationaal Politielab AI – Utrecht


Scientific director

Prof. Dr. Floris Bex

PhD students

Michiel Bron, MSc
Many important facts in police complaints or incident reports are recorded in unstructured free text. This data is difficult to analyse for a computer. These documents must be provided with tags and other metadata to aid analysis. However, this is a time-consuming process if this has to be done manually. My research project aims to create a system that automatically provides these documents with the correct tags. Through the use of new machine learning techniques, we aim to minimise the number of manually tagged documents data needed for the model's training.
Mijke van den Hurk, MSc
I do research on the field of Social Simulation, where the aim is to build a multi-agent based model that can be used to simulate complex (social) systems. Agents represent humans with needs, identities and relations. These kind of models can give insights on social and dynamical processes, and support policy making within the system. The aim of my research is to build a virtual world that can be used by the Dutch Police for analysis on social-cultural issues or testing of interventions on criminal organizations.
Laurens Müter, MSc
To extract information from social media, I try to find textual and divergence patterns in micro-blogs related to incidents.
Daphne Odekerken, MSc
A dialogue system, or conversational agent, is an agent that communicates with another agent. Dialogue has been studied in the domains of human-computer interaction and formal argumentation. In my dissertation research, I explore the possibilities of combining these two approaches into hybrid argumentative-conversational agents in the legal domain. By combining the strengths of machine learning based conversational agents and formal argumentation, I aim to develop agents that can accurately and efficiently respond to natural language input by asking relevant questions and drawing explainable conclusions. In my function as AI Scientist at the Dutch National Police, I am currently implementing a dialogue system for the automatic intake of complaints of online trade fraud.
Joeri Peters, MSc
My research is related to the idea of intelligent monitoring. To be able to anticipate to developments in society in an early stage, it is important to reason with scenarios and data. For this purpose I apply scenario analysis, argumentation and strategy definition. I am developing formalisms and methods that enable reasoning with scenarios comparable to their application in murder cases: with evidence, alternative stories, alibis etc.
Marcel Robeer, MSc
New techniques in the field of Machine Learning (ML) offer the Dutch Police many opportunities for data-driven analysis and decision-making. However, the complexity of these methods makes it unclear how the decisions made using these ML models were generated from the data. For the Police, it is of vital importance that decisions made are grounded in findings and supported by facts that strengthen the case. In my PhD, I investigate and develop methods for (interactively) explaining decisions made by artificial intelligence (AI) systems, in a human-understandable, useful and truthful manner.
Remi Wieten, MSc
I am a PhD student at the Department of Information and Computing Sciences at Utrecht University with a background in Mathematics (BSc) and Forensic Science (MSc). In my project, I am concerned with: (1) developing methods and techniques for the (semi-)automated construction of Bayesian networks (BNs) from arguments; and (2) designing argumentation-based techniques for reasoning about BNs, which can aid experts in validating, refining and choosing between constructed BNs.

Senior researchers

Dr. AnneMarie Borg
In several of the components of the police project we work with formal argumentation. For this purpose we work with structured argumentation in dynamic settings, something which is relatively unknown. In my research I aim at developing argumentation frameworks that can be implemented in the police project.
Dr. Jelte Mense
My main research at the Police Lab AI revolves around how the police can use AI and data science to become more effective. I am also interested in how the police can leverage open data such as news to detect and anticipate important developments that could be relevant to the Netherlands. Next to data science methods I am also passionate about agent-based modelling and social simulation, for example through exploring the effectiveness of police interventions in criminal networks in computer models.
Dr. Marijn Schraagen
I am a computational linguist working on a variety of topics in information retrieval and classification. I obtained a bachelor and master degree in Artificial Intelligence from Utrecht University and a PhD in Data Mining from Leiden University. My application areas of interest include computational historical sociolinguistics and NLP in the legal domain.
Dr. Bas Testerink
Teamlead TWO (Driebergen, Odijk, Utrecht)
Team scientific developments (Dutch abbreviation: TWO) is a scientific R&D team at the police which acts as a bridge between academic theory and police practice. We are particularly interested in research regarding A) data acquisition, such as active learning, B) analysis, monitoring and control of systems, such as game theory and normative systems, C) optimalisation, such as reinforcement learning, D) efficient data usage, such as transfer learning.

In addition, I'm also active in the field of A.I. & ethics. I do this from a technological perspective, as I'm not an ethicist myself.

Student researchers

Drs. Dennis Craandijk
Formal argumentation is characterized by some hard reasoning problems which are currently only solvable by symbolic algorithms. However, recent advances in neural networks which can operate on graphs, have opened up the possibility to use learning-based methods on such reasoning problems. My research aims at bridging the gap between symbolic-based and learning-based AI by applying these learning-based methods to logical reasoning problems in argumentation.