Bruno Nicenboim

Email: [initial].[lastname] [at] tilburguniversity.edu
Office: D108, Dante Building, Tilburg University
Address: Department of 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 Cognitive Science and AI of Tilburg University and a guest researcher at the department of Linguistics the University of Potsdam, Germany. Before that I did my PhD and Postdoc in Shravan Vasishth’s lab, at the Department of Linguistics of University of Potsdam, Germany.

[Mastodon] [Twitter] [Github] [ORCID] [OSF]



My main interests

Computational (cognitive) modeling in a Bayesian framework (using Stan)

Some representative examples:

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

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

EEG

Some representative examples:

[1] 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.

[2] 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.

[3] An R package for the manipulation of EEG data: https://bnicenboim.github.io/eeguana/.

Bayesian statistics

Some representative examples:

[1] B. Nicenboim and S. Vasishth. “Statistical methods for linguistic research: Foundational Ideas - Part II”. In: Language and Linguistics Compass 10.11 (2016), pp. 591-613. DOI: 10.1111/lnc3.12207.

[2] D. J. Schad, B. Nicenboim, P. Bürkner, et al. “Workflow Techniques for the Robust Use of Bayes Factors”. In: Psychological methods (2022). DOI: 10.1037/met0000472.

[3] Bayesian statistics for cognitive scientists textbook (in progress) together with Shravan Vasishth and Daniel Schad.

[4] Stan for cognitive science website with resources for Bayesian modeling with Stan.


Data and code

Data and code for my published papers is mostly in the OSF website (with some exceptions in my github repo). And I’m also contributing to the list of publicly available psycholinguistics datasets.


News

The 57th Annual Meeting of the Society for Mathematical Psychology (MathPsych) and the 22nd International Conference on Cognitive Modeling (ICCM) will happen at Tilburg University, the Netherlands. The dates of the conference are July 19 to 22, 2024. (https://mathpsych.org/conference/15/).

I obtained a NWO Open Competition SGW XS grant The project’s aim is to gather self-paced EEG data for benchmarks and computational modeling.

Together with Riccardo Fusaroli and Marieke van Vugt, we organized a Lorentz Centre “Cognitive Modeling of Complex behaviour” hands-on workshop in January 2024. The core of the workshop was self-organized group work, where participants together tackle the modeling of a phenomenon of interest. See here.


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