About Me

I am currently a PhD researcher at the DTAI lab of the KU Leuven.


For the list of my publications, I refer to my Google Scholar page.

Work Experience

Aug. 2019 — present PhD Researcher, Department of Computer Science, KU Leuven

Leuven, Belgium PhD researcher on artificial intelligence, verifiability, and NLP at the DTAI lab.

Mar. 2019 — Jun. 2019 Part-time Student Researcher, Department of Computer Science, KU Leuven

Leuven, Belgium Published a paper on detecting ad hominem fallacies (i.e. personal attacks) in online debates and presented the paper at ACL 2019 in the Student Research Workshop.

Oct. 2018 — Jun. 2019 Master's student, CNH Industrial

Leuven, Belgium Created a deep learning pipeline to detect obstacles in front of combine harvesters with radar data for my advanced master’s thesis.

Sep. 2017 — Jul. 2018 Master's student, Nokia Bell Labs

Antwerp, Belgium Designed and developed two complementary systems for symptom detection and diagnosis of failures in distributed stream processing systems (WWS), based on the network topology, for my master's thesis.


Sep. 2018 — Jun. 2019 Advanced master in Artificial Intelligence, KU Leuven

Leuven, Belgium Master's thesis under Johan Suykens in collaboration with CNH Industrial. Elective courses on genetic algorithms, fake news, and SVMs.

Sep. 2017 — Jul. 2018 Master of Electronics and ICT Engineering Technology, KU Leuven Ghent, Belgium
  • Cross platform chat application in React Native
  • Distributed multiplayer turn based game (Uno)
  • OpenCL and CUDA photo editor with an Qt GUI.
  • Elective course: Embedded systems with lab on ARM Cortex M-series microprocessors.
Sep. 2014 — Jul. 2017 Bachelor of Electronics and ICT Engineering Technology, KU Leuven Ghent, Belgium

Bachelor's thesis: visualization and problem detection on train carriages. [code]

Other activities

I'm a teaching assistant the introductory course in Artificial Intelligence with online videos (2019-present) and databases (2020-2021).

And I have supervised or am currently supervising these master's students and interns:

  • Thomas Bauwens, 2023. BPE.
  • João Pedro Olinto Dossena, 2023. Learning what to learn: Generating language lessons using BERT.
  • Andru Cristian Onciul, 2023. How different classes of AI models incorporate or exacerbate existing biases in the data.
  • Maarten Van den Hof, 2022. Satire generation using transformers.
  • Damian Vlaicu, 2022. Prosody prediction from text. Acapela
  • Antoine Van Luchem, 2022. A domain-specific language for open world learning in Haskell. PL group
  • Bruno Vandekerkhove, 2021 (ongoing). Neural networks in Haskell. PL group
  • Lara Pollet, 2021. Learning to Rank Generated Portmanteaus. Published at ICCC'21
  • Andrea Martens, 2020 (ongoing). .Predicting Traffic Violations.
  • Nicholas Wellens, 2021. Morpheme-based tokenizers for language models
  • Elias Regopoulos, 2020. Kiwi.
  • Siddharth Rajkumar Agarwal, 2020. Bias in language models.
  • Jonas Vandamme, 2019. Coreference resolution with rule-based systems in Dutch based on semantic relations.

I've reviewed for the following venues: