I am a PhD student in Computational Linguistics, supervised by Prof. Dr. Lena A. Jäger and co-supervised by Prof. Dr. Ebling. I have a Master's degree in Digital Linguistics from UZH.
I did my master's thesis project with Prof. Dr. Lena A. Jäger and Dr. Ethan Wilcox on Mouse Tracking for Reading (MoTR): A New Incremental Processing Paradigm (which was awared by the University of Zurich with the Semesterpreis). In this project, we present a method that aims to be cheap and easy but at the same time a better proxy for the gold-standard eye-tracking. With MoTR, participants see very blurry text and hover their mouse over text to bring that text into clarity. Thus, participants can read relatively naturally, including being able to skip words or regress, and researchers get reading location for each time point similar to that from eye-tracking.
I am currently working on MeRID and MultiplEYE projects.
Teaching
| Semester | Course |
|---|---|
| HS 2026 | Lecturer of Computational cognitive modeling of language processing |
| HS 2023 | TA in Quantitative Methods |
| FS 2023 | TA in Eye tracking: Experiment design and machine learning methods |
| FS 2023 | TA in Programming Techniques in Computational Linguistics 2 |
| HS 2022 | TA in Language Data Processing |
Publications
ZORA Publication List
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Publications
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Eyettention II: A dual-sequence architecture for modeling fixation location, within-word landing position, and fixation duration in reading Behavior Research Methods, 58, 257. https://doi.org/10.3758/s13428-026-03118-6
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MultiplEYE Data Collection Guidelines PsychArchives. https://doi.org/10.23668/psycharchives.21734
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The MultiplEYE Text Corpus: Towards a Diverse and Ever-Expanding Multilingual Text Corpus 6706–6721. https://doi.org/10.63317/42gkpf6a6x2x
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Replicate Me if You Can: Assessing Measurement Reliability of Individual Differences in Reading Across Measurement Occasions and Methods Cognitive Science, 50, e70121. https://doi.org/10.1111/cogs.70121
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Modeling Bottom-up Information Quality during Language Processing (C. Christodoulopoulos, T. Chakraborty, C. Rose, & V. Peng, Eds.; pp. 11709–11721). Association for Computational Linguistics. https://doi.org/10.18653/v1/2025.emnlp-main.592
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Using Information Theory to Characterize Prosodic Typology: The Case of Tone, Pitch-Accent and Stress-Accent In W. Che, J. Nakatumba-Nabende, E. Shutova, & M. T. Pilehvar (Eds.), Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics: Vol. 1: Long Papers (pp. 24439–24451). Association for Computational Linguistics. https://doi.org/10.18653/v1/2025.acl-long.1192
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MultiplEYE: Creating a Multilingual Eye-Tracking-While-Reading Corpus (Y. Sugano, M. Khamis, A. Chetouani, L. Sidenmark, & A. Bruno, Eds.; p. 111). ACM Digital library. https://doi.org/10.1145/3715669.3726843
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Proxy-Based Pre-Training for Eye-Tracking Applications (Y. Sugano, M. Khamis, A. Chetouani, L. Sidenmark, & A. Bruno, Eds.; p. 26). ACM Digital library. https://doi.org/10.1145/3715669.3723113
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Using MoTR to Probe Agreement Processing in Russian Open Mind, 9, 1682–1710. https://doi.org/10.1162/OPMI.a.35
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Mouse Tracking for Reading (MoTR): A new naturalistic incremental processing measurement tool Journal of Memory and Language, 138, 104535. https://doi.org/10.1016/j.jml.2024.104534
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Mouse Tracking for Reading (MoTR): A New Incremental Processing Paradigm (Master’s thesis, University of Zurich) https://doi.org/10.5167/uzh-259944