Tilburg Algorithm Observatory, Assistant Professor at the Department of Cognitive Science & AI, Tilburg University

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đź‘‹ Hi


I’m an Assistant Professor at the Department of Cognitive Science and Artificial Intelligence of Tilburg University. I work on algorithmic monitoring and auditing as part of the Tilburg Algorithm Observatory, and am 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.

Tilburg Algorithm Observatory | Tilburg University

I defended my dissertation “User-centered Security in Natural Language Processing” in January 2023, supervised by Grzegorz Chrupała, Eric Postma, and Walter Daelemans.

I'm a member of the faculty council (DCA.I.) and the Data Science and Society program committee.

⚗️ Research


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. Here are a few selected papers to give you an idea:

SOBR: A Corpus for Stylometry, Obfuscation, and Bias on Reddit

Adversarial Stylometry in the Wild: Transferable Lexical Substitution Attacks on Author Profiling

Current limitations in cyberbullying detection: On evaluation criteria, reproducibility, and data scarcity

Towards Replication in Computational Cognitive Modeling: a Machine Learning Perspective

🏫 Teaching


I’m currently 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 (JADS). Previously, I taught Text Mining and Spatiotemporal Data Analysis (both one semester), and Data Mining (five years). I focus 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. Here are the associated course pages (on Notion):

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