About me
I am a PhD researcher in computational linguistics at the QLVL Research Group, KU Leuven, and a member of the Marie Skłodowska-Curie Doctoral Network CASCADE. My research focuses on semantic and conceptual change, particularly on how changes in meaning can be detected, modelled, and explained through linguistic behaviours.
My current research spans three related lines. First, I work on interpretable, theory-driven computational methods for studying semantic change. Second, I develop research software for large-scale linguistic analysis. Third, I investigate how data quality, annotation, task formulation, and methodological choices interact and shape the conclusions drawn from computational models.
Before joining KU Leuven, I completed an MSc in Linguistics at the University of Stirling. I have also worked on applied NLP problems involving speech recognition, speech translation, large language models.
Outside research, my main interests are martial arts and classical singing.
Research interests
My main research interests are:
- Interpretable, theory-driven computational modelling of semantic change (Transparent Semantic Change Detection; ReFRAME or Remain).
- Research software for linguistic analysis (SynFlow).
- The interaction between data, methods, and evaluation (Evaluating the Evaluator; Methods, Data, and Conceptual Change).
I also explore interdisciplinary applications of these methods, such as in the history of science (Discursive Parallels of the Chemical Revolution), and in other fields where computational approaches can help trace and interpret change over time.
More recently, I have been learning about complex systems, time-series modelling, and financial engineering.
If any of these topics sound interesting, feel free to reach out.
Contact me
Recent news
2026
July 2026
- My abstract “Underlying Dimensions of Semantic Change” was accepted for presentation at the Digital Humanities Congress 2026 at the University of Sheffield.
Conference
June 2026
- Our paper “Methods, Data, and Conceptual Change: Reflections from Two Quantitative Diachronic Case Studies”, with Catherine Wong and Susan Fitzmaurice, was accepted for publication in the Journal of Open Humanities Data.
Paper
May 2026
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Our paper “ReFRAME or Remain: Unsupervised Lexical Semantic Change Detection with Frame Semantics” was accepted at *SEM 2026.
ACL Anthology -
Our paper “Evaluating the Evaluator: Problems with SemEval-2020 Task 1 for Lexical Semantic Change Detection” was accepted for publication in the Journal of Open Humanities Data.
Paper
March 2026
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My abstract “Lexical Semantic Change Detection? A Good Parser Might Be Enough!” was accepted for presentation at the 1st LOT Conference.
Conference -
I was invited to give a talk on “Underlying Dimensions of Semantic Change” at the Leuven.AI NLP & Text Mining Seminar.
February 2026
- Our abstract “From Parsers to Prompts: Combining AI and Linguistics for Interpretable Language Evolution” was accepted for the AI in Language Evolution Workshop at Evolang 2026.
Evolang 2026
January 2026
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Our paper “Transparent Semantic Change Detection with Dependency-Based Profiles” was accepted at LChange’26, co-located with EACL 2026.
ACL Anthology -
Our book chapter “Discursive Parallels of the Chemical Revolution: Topic Modelling and Distributional Analysis” was accepted for publication in Understanding Science with Large Language Models? Potentials for the History, Philosophy, and Sociology of Science.
Chapter -
Two of my abstracts were accepted for presentation at ICAME 47 in Koblenz:
- “SynFlow: Continuous Semantic Change Analysis via Dependency Co-occurrences”
- “Conceptual Change during the Chemical Revolution: Air, Acid, and Water in the Royal Society Corpus”
Conference
2025
November 2025
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My abstract “Slot-Filler Distributional Changes in Times of Scientific Debate: A Case Study of Air” was accepted for presentation at Quantitative Diachronic Linguistics and Cultural Analytics at King’s College London.
Conference -
I was invited to give a talk on “SynFlow: Continuous Semantics Change Analysis via Dependency Co-occurrences” in the Data in Historical Linguistics Seminar Series.
Seminar series