README

I’m an Assistant Professor and part of the Tilburg Algorithm Observatory at the Department of Cognitive Science and Artificial Intelligence of Tilburg University. I work on algorithm monitoring and auditing, specifically relating to privacy, security, and harms in Machine Learning (and Natural Language Processing). Generally, I’m interested in the (harmful) effects of intelligent systems on our lives; systems that uncover our personal information, monitor and change our behavior, subtly restrict our exposure to information, and treat us unfairly.

Expertise

I have a multidisciplinary background in humanities and computer science. My primary area of expertise is identifying and attempting to subvert (harmful) inferences made through Machine Learning (ML). I have mainly worked on adversarial attacks on Deep Learning algorithms trained on language data (Natural Language Processing or NLP), with a focus on privacy and security. My work critically analyzes the current, and more distant impact such algorithms have on society. I’m a strong advocate of a user-centered, open-source approach to ML, and the automation of society in general.

Within NLP, I have worked on various topics such as (adversarial) stylometry (or author profiling), cyberbullying/toxicity detection, data augmentation through lexical substitution, language generation, machine translation, and more generally scientific development of reproducible research pipelines.

Academic Background

Teaching

I’m the course coordinator for both Data Processing (Python course) in context of our Data Science master, and Language & AI (NLP for Data Science course) for our joint Data Science bachelor with TU/e. I previously taught Text Mining and Spatio-temporal Data Analysis (both one semester), and Data Mining (five years). Ifocus on innovating the courses I am involved in, primarily by connecting theory to practical use cases. I believe this makes the lectures more fun, and easier to conceptualize the utility of the material. It also provides a soft introduction to applications students might see in their future careers. A recent example is my EDUiLAB project to familiarize Data Processing students with code versioning, repositories, and build servers using GitHub.

(Scientific) Development

During a mix of my studies in AI and a minor in (applied) Computer Science, I learned to speak most notably Python, PHP, and Java. During this time, I also became an avid Linux user and, by extension, very enthusiastic about open-source and open-science initiatives. The latter I wrote a commentary on, and recently converted into an educational innovation project. During my Masters, I ran a sole proprietorship in web development and data collection, and scripting was a large part of my activities as a student assistant. During my PhD, I was (partly) responsible for server maintenance at both research groups, which—combined with my modest home server park—has made me quite comfortable with system administration. All in all, I typed a whole bunch of code for websites, wrappers, and research (tools). I strongly believe all scientific work should not only be completely open and reproducible, but also usable and extendable. A good example of this, is my W-NUT paper, and its demo: tōku. More examples can be found here.

Personal

Apart from my main activity in life (providing often noisy feedback signals to the developmental marvel that is my son), I enjoy (too) many things outside of academia: heavy music (yearly most frequent albums below, I’m unfortunately also into vinyl, I play guitar, drums, and some piano), food (cooking and eating, I’m particular fond of (South)-East Asian cuisine, BBQ, stews, and Erwtensoep), video games (RPGs/shooters, but tbf I mostly have an ungodly amount of hours on the EA Skate games), binging Crunchyroll shows, and deadlifting in my garage.