15 April 2025
I am an interdisciplinary PhD Candidate at the Institute for Information Law, the Institute for Informatics, and affiliated with the Data Science Centre. I work at the intersection of law, economics and data science - more specifically, in the realm of compliance and incentive-related behavior in digital ecosystems. In my research, I use data science as a methodology to support my empirical research agenda. For instance, I apply it to look into behavioral aspects of compliance.
An important focus of my PhD is building a bridge between legal research and data science methodology, and experimenting with these methodologies to determine which are effective for legal research.
I recently completed a project on compliance behavior in the Ethereum ecosystem, working with a colleague to gather and analyze real-world data around the moderation of sanctioned transactions by Ethereum actors. I integrated various methodologies – including statistics and anomaly detection tools - to draw conclusions about compliance behavior. The project was selected for presentation at an IEEE conference this summer, and will result in the publication of a short paper. I hope to apply parts of this methodology in future projects as well.
I appreciate the opportunity to participate in courses and workshops on methodology, which are really helpful when you’re still developing your methodological skills. I also recently attended an event with other Data Science Centre PhD’s, which was a great way to learn from each other’s experiences, discuss methods, and enjoy the benefits of an interdisciplinary environment.
At the moment, I like to use anomaly detection tools for my research, but I’m eager to keep expanding my knowledge.
Python, 100%! It’s super versatile.