Bruno Nicenboim

Email: [initial].[lastname] [at] tilburguniversity.edu
Office: D108, Dante Building, Tilburg University
Address: Department of Computational Cognitive Science,
Cognitive Science and Artificial Intelligence
Tilburg University
PO Box 90153
5000 LE Tilburg
The Netherlands

About me

I’m an assistant professor at the department of Department of Computational Cognitive Science, Cognitive Science and AI, of Tilburg University, PI of the Computational Psycholinguistics Lab. Before that I did my PhD and Postdoc in Shravan Vasishth’s lab, at the Department of Linguistics of University of Potsdam, Germany.

My Main Interests

Computational Cognitive Modeling

I study computational cognitive modeling of psycholinguistic phenomena, with some examples below:

  • Nicenboim, B. (2023). “The CoFI Reader: A Continuous Flow of Information approach to modeling reading.” In: MathPsych/ICCM/EMPG. University of Amsterdam, the Netherlands. [read]

  • Nicenboim, B. and S. Vasishth (2018). “Models of Retrieval in Sentence Comprehension: A computational evaluation using Bayesian hierarchical modeling.” In: Journal of Memory and Language, 99, pp. 1–34. ISSN: 0749-596X. DOI: 10.1016/j.jml.2017.08.004. [read]

I am also interested in broader aspects of computational modeling:

  • Dubova, M., S. Chandramouli, G. Gigerenzer, P. Grünwald, W. Holmes, T. Lombrozo, M. Marelli, S. Musslick, B. Nicenboim, L. N. Ross, et al. (2025). “Is Ockham’s razor losing its edge? New perspectives on the principle of model parsimony.” In: Proceedings of the National Academy of Sciences, 122(5), p. e2401230121. DOI: 10.1073/pnas.2401230121. [read]
  • I was one of the organizers of the first Computational Psycholinguistics Meeting (2025): a new recurring meeting dedicated exclusively to computational psycholinguistics.
  • I organized the Lorentz Centre “Cognitive Modeling of Complex Behavior” workshop in January 2024, along with Riccardo Fusaroli and Marieke van Vugt. This hands-on event focused on collaborative modeling of cognitive phenomena. See here.

EEG in Psycholinguistics

I also work with EEG in psycholinguistics:

  • K. Stone, B. Nicenboim, S. Vasishth, et al. “Understanding the effects of constraint and predictability in ERP.” In: Neurobiology of Language (Dec. 2022), pp. 1-71. DOI: 10.1162/nol_a_00094. [read]

  • B. Nicenboim, S. Vasishth, and F. Rösler. “Are words pre-activated probabilistically during sentence comprehension? Evidence from new data and a Bayesian random-effects meta-analysis using publicly available data.” In: Neuropsychologia, 142 (2020), p. 107427. DOI: 10.1016/j.neuropsychologia.2020.107427. [read]

I also developed an R package for EEG data manipulation: eeguana.

Bayesian Statistics

Bayesian statistics provides a powerful framework for cognitive science by allowing principled uncertainty quantification and hierarchical modeling. I mostly work with Stan (and brms):

Data and Code

Most of the data and code from my published papers are available on the OSF website, with some exceptions in my GitHub repository.

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