Max Rabe, Ph.D.

Modeling minds, minding models.

About

As a cognitive scientist, I develop computational models that do more than describe patterns in human behavior—they make quantitative, testable predictions about the cognitive processes that give rise to them. My research combines cognitive theory, statistical modeling, and computational methods to better understand the mechanisms underlying the human mind.

I am a strong advocate for open science. I believe that scientific research should be transparent, reproducible, and accessible for everyone interested. Whenever possible, I openly share the code, data, and software behind my work so that others can build on it, scrutinize it, and extend it.

I am currently a postdoctoral researcher at the University of Potsdam in Ralf Engbert’s lab and a co-PI in Collaborative Research Center (SFB) 1287 (Project B03). I strongly value international academic exchange, which is why I also serve as the ERASMUS+ coordinator for the Department of Psychology and as a DAAD (German Academic Exchange Service) reviewer (Fachgutachter) for Psychology.

My work follows two complementary directions. First, I develop and extend computational models of cognition, including SEAM, an integrated model of sentence processing and eye-movement control during reading, and RStanTVA, a Bayesian implementation of the Theory of Visual Attention. Second, I develop statistical methods and open-source software that make advanced modeling more accessible, robust, and reproducible. This includes the R packages hypr, designr, and appRiori, which help researchers design experiments, analyze data, and build better models.

Curriculum Vitae

10/2026 – (current)		Ad-hoc reviewer, Journal of Experimental Psychology: Learning, Memory, and Cognition Learn more
10/2026 – 03/2027		Lecture (undergraduate level) on “Introduction to scientific work”, University of Potsdam
10/2026 – 03/2027		Lecture (undergraduate level) on “Introduction to psychology and its research methods”, University of Potsdam
10/2026 – 03/2027		Seminar (undergraduate level) on “Introduction to statistiscal programming with R”, University of Potsdam
08/2026		Attended European Conference on Eye Movements (ECEM) 2026, Ulm, Germany
06/2026 – (current)		Ad-hoc reviewer, Computational Brain & Behavior, Society for Mathematical Psychology Learn more
04/2026 – (current)		Selection committee member, PhD Fellowships, Deutscher Akademischer Austauschdienst (DAAD) Learn more
01/2026 – 06/2029		Board member, Integrated Graduate School (MGK), CRC 1287 “Limits of Variability in Language”, University of Potsdam Learn more
01/2026 – 12/2026		KoUP Cooperation Funding, University of Potsdam Learn more
10/2025 – 03/2026		Lecture (undergraduate level) on “Introduction to scientific work”, University of Potsdam
10/2025 – 03/2026		Lecture (undergraduate level) on “Introduction to psychology and its research methods”, University of Potsdam
10/2025 – 03/2026		Seminar (undergraduate level) on “Introduction to statistiscal programming with R”, University of Potsdam
05/2025 – 09/2025		Parental leave
04/2025 – 09/2025		Seminar (undergraduate level) on “Experimental psychological training”, University of Potsdam
03/2025		Attended Tagung experimentell arbeitender Psychologen (TeaP) 2025, Frankfurt (Main), Germany
12/2024 – (current)		ERASMUS+ coordinator (outgoing), Department of Psychology, University of Potsdam Learn more
11/2024		Attended Psychonomic Society 2024 Annual Meeting, New York City, NY, USA
10/2024 – 03/2025		Seminar (undergraduate level) on “Introduction to statistical programming with R”, University of Potsdam
10/2024 – (current)		Ad-hoc reviewer, Behavior Research Methods, Psychonomic Society Learn more
10/2024 – (current)		Postdoctoral Research Fellow, University of Potsdam
10/2024 – 03/2025		Seminar (graduate level) on “Hierarchical linear and logistic regression”, University of Potsdam
09/2024 – 12/2024		Seminar (graduate level) on “Experimental Methods 2”, University of Copenhagen
09/2024 – (current)		Ad-hoc reviewer, Journal of Memory and Language, Elsevier Learn more
06/2024 – (current)		Ad-hoc reviewer, Cognitive Psychology, Elsevier Learn more
04/2024 – (current)		Ad-hoc reviewer, Language, Cognition and Neuroscience, Taylor & Francis Learn more
04/2024		UFSKW Paper of the Month April 2024, Research Focus Cognitive Sciences (UFSKW), University of Potsdam Learn more
02/2024 – (current)		Postdoctoral Research Fellow, University of Copenhagen
05/2018 – 01/2024		Ph.D., Cognitive Science, University of Potsdam
11/2023 – (current)		Ad-hoc reviewer, Psychological Review, APA Learn more
10/2023 – 01/2024		Seminar (undergraduate level) on “Introduction to statistical programming with R”, University of Potsdam
04/2023 – 09/2023		Seminar (undergraduate level) on “Introduction to Human Memory”, University of Potsdam
10/2022 – 03/2023		Seminar (undergraduate level) on “Introduction to statistical programming with R”, University of Potsdam
13/09/2022		Tutorial on “Dynamical modeling of eye movements in reading”, Statistical Methods for Linguistics and Psychology (SMLP) 2022, University of Potsdam
09/2022 – 10/2022		Parental leave
02/2022 – 07/2022		Parental leave
11/2021		Attended Psychonomic Society 2021 Annual Meeting, New Orleans, LA, USA (virtual)
11/2021 – (current)		Ad-hoc reviewer, Cognition, Elsevier Learn more
21/07/2021 – 22/07/2021		Workshop on “Contrast coding using linear regression with hypr”, EMS-SCS 2021, St. Petersburg, Russia (virtual) Learn more
07/2021		UFSKW Paper of the Month July/August 2021, Research Focus Cognitive Sciences (UFSKW), University of Potsdam Learn more
06/2020 – (current)		Ad-hoc reviewer, Journal of Open Source Software (JOSS), Open Journals Learn more
06/2020 – (current)		Ad-hoc selection committee member, Outgoing student applications for Australian, Canadian, and US partner universities, University of Potsdam
06/2020		Attended SFB 1287 MGK Project Week, University of Potsdam, Germany (online)
05/2020		Attended repliCATS workshop, University of Melbourne, Australia (online)
02/2020		Attended 14th BremHLR Workshop on Parallel Programming with MPI and OpenMP, BremHLRN, University of Bremen, Germany
08/11/2019		Invited talk “Dynamical cognitive modeling: Bayesian inference of the SWIFT model”, University of Victoria, BC, Canada
11/2019		Attended Psychonomic Society 60th Annual Meeting, Montréal, QC, Canada
13/09/2019		Lecture on “Bayesian inference of the SWIFT model: Lecture on Dynamical Cognitive Modeling”, SMLP 2019, Potsdam, Germany Learn more
09/2019		Attended 3rd Statistical Methods for Linguists and Psychologists (SMLP), University of Potsdam, Germany
09/2019		Attended Cognitive Computational Neuroscience (CCN) 2019, Berlin, Germany Learn more
08/2019		Attended European Conference on Eye Movements (ECEM) 2019, Alicante, Spain
06/2019		Attended Conference for Research Software Engineers in Germany 2019 (deRSE19), Potsdam, Germany
03/2019		Attended Statistics for Big Data, Free University of Berlin, Germany
03/2019		Attended 2nd SFB 1294 Spring School on Data Assimilation, Dierhagen, Germany
02/2019		Attended SFB 1294 Python Workshop, Potsdam, Germany
11/2018		Selection committee member, Study Scholarship for North America 2019/20, Deutscher Akademischer Austauschdienst (DAAD)
11/2018 – 09/2020		Student Representative, Senate Commission on Research and Junior Scientists, University of Potsdam
10/2018		Attended HLRN-IV user workshop, University of Göttingen, Germany
09/2018		Attended 2nd Statistical Methods for Linguists and Psychologists (SMLP), Bayesian track, University of Potsdam, Germany
04/2018 – (current)		Campus Representative, APS Student Caucus
09/2016 – 04/2018		M.Sc., Psychology (Cognition and Brain Science), University of Victoria
01/2018 – 01/2024		Doctoral Research Fellow, University of Potsdam
11/2017		Attended Psychonomic Society 58th Annual Meeting, Vancouver, BC, Canada
09/2017 – 08/2018		Graduate Fellowship, University of Victoria Learn more
05/2017		Attended Northwest Cognition and Memory (NOWCAM), Burnaby, BC, Canada
03/2017 – 04/2019		Ad-hoc peer reviewer, Student Research Award, APS
01/2017 – 04/2017		Teaching Assistant, University of Victoria
11/2016		Attended Psychonomic Society 57th Annual Meeting, Boston, MA, USA
09/2016 – 04/2018		Graduate Study Scholarship, Deutscher Akademischer Austauschdienst (DAAD) Learn more
10/2012 – 08/2016		B.Sc., Psychology, University of Potsdam
10/2015 – 08/2016		Teaching/Laboratory Assistant, University of Potsdam
06/2015 – 08/2016		Director of Communication, Psychology Students Union, University of Potsdam
01/2015 – 04/2015		Research Internship, University of Victoria
01/2015 – 04/2015		PROMOS Scholarship, Deutscher Akademischer Austauschdienst (DAAD) Learn more
06/2014 – 08/2016		Research Assistant, University of Victoria

Publications

Rabe, M. M. & Kliegl, R. (September 2026). Bridging statistical and computational approaches to modeling eye movements in reading using a Linked Mixture Model. Talk presented at European Conference on Eye Movements (ECEM) 2026, Ulm, Germany.
Rabe, M. M. & Kyllingsbæk, S. (2026). Enhancing TVA with Bayesian methods: A tutorial and new insights into computational modeling of visual attention using RStanTVA. Manuscript submitted for publication. DOI PsyArXiv
Granziol, U. , Rabe, M. M. , Gallucci, M., Spoto, A. , & Vidotto, G. (2025). Not another post-hoc paper: A new look at contrast analysis and planned comparisons. Advances in Methods and Practices in Psychological Science, 8(1). DOI
Granziol, U. , Rabe, M. M. , Spoto, A. , Vidotto, G. , & Gallucci, M. (2025). appRiori: Code and Obtain Customized Planned Comparisons with 'appRiori' [R package].
Rabe, M. M. & Kyllingsbæk, S. (March 2025). Is the Future of TVA Bayesian?. Talk presented at Tagung experimentell arbeitender Psychologen (TeaP) 2025, Frankfurt am Main, Germany.
Rabe, M. M. & Kyllingsbæk, S. (2025). RStanTVA: TVA Models in 'Stan' using 'R' and 'StanTVA' [R package].
Engbert, R. & Rabe, M. M. (2024). Tutorial on dynamical modeling of eye movements in reading. Journal of Mathematical Psychology, 119, Article 102843. DOI PsyArXiv
Rabe, M. M. & Kyllingsbæk, S. (November 2024). Enhancing TVA with Bayesian methods using RStanTVA: New insights into computational modeling of visual attention. Poster presented at MathPsych @Psychonomics Satellite Meeting 2024, New York City, NY, USA. URL DOI
Rabe, M. M. , Paape, D. , Mertzen, D. , Vasishth, S. , & Engbert, R. (2024). SEAM: An integrated activation-coupled model of sentence processing and eye movements in reading. Journal of Memory and Language, 135, Article 104496. DOI arXiv
Rabe, M. M. (2024). Modeling the interaction of sentence processing and eye-movement control in reading (Ph.D.). Supervisors: R. Engbert and S. Vasishth . Universität Potsdam, Germany. DOI URN PDF
Engbert, R. , Rabe, M. M. , Kliegl, R. , & Reich, S. (2021). Sequential data assimilation of the SEIR model for COVID-19. Bulletin of Mathematical Biology, 83, Article 1 (2021). DOI medRxiv PDF
Engbert, R. , Rabe, M. M. , Schwetlick, L. , Seelig, S. A. , Reich, S. , & Vasishth, S. (2021). Data assimilation in dynamical cognitive science. Trends in Cognitive Science, 26(2), 99–102. DOI
Rabe, M. M. , Chandra, J. , Krügel, A. , Seelig, S. A. , Vasishth, S. , & Engbert, R. (2021). A Bayesian approach to dynamical modeling of eye-movement control in reading of normal, mirrored, and scrambled texts. Psychological Review, 128(5), 803–823. DOI PsyArXiv
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Rabe, M. M. , Paape, D. , Vasishth, S. , & Engbert, R. (November 2021). SEAM: An integrated activation-coupled model of sentence processing and eye movements in reading. Poster presented at Psychonomic Society 62nd Annual Meeting (virtual).
Rabe, M. M. , Vasishth, S. , Hohenstein, S. , Kliegl, R. , & Schad, D. J. (2020). hypr: An R package for hypothesis-driven contrast coding. The Journal of Open Source Software, 5(48), Article 2134. DOI PDF
Seelig, S. A. , Rabe, M. M. , Malem-Shinitski, N. , Risse, S. , Reich, S. , & Engbert, R. (2020). Bayesian parameter estimation for the SWIFT model of eye-movement control during reading. Journal of Mathematical Psychology, 95, Article 102313. DOI arXiv PDF
Rabe, M. M. , Chandra, J. , Krügel, A. , Seelig, S. A. , & Engbert, R. (November 2019). Bayesian inference of dynamical cognitive and oculomotor processes in the SWIFT model of reading. Poster presented at Psychonomic Society 60th Annual Meeting, Montréal, QC, Canada. DOI PDF
Rabe, M. M. , Chandra, J. , Krügel, A. , Seelig, S. A. , & Engbert, R. (August 2019). Bayesian inference of the SWIFT model: Reading mirrored, scrambled, and normal texts. Poster presented at European Conference on Eye Movements (ECEM) 2019, Alicante, Spain. DOI PDF
Rabe, M. M. , Kliegl, R. , & Schad, D. J. (2019). designr: Balanced factorial designs with crossed random and fixed factors [R package]. URL
Rabe, M. M. , Schad, D. J. , Vasishth, S. , & Kliegl, R. (2019). hypr: Hypothesis matrix translation [R package]. URL
Rabe, M. M. (November 2019). Eye-movement control during reading: Bayesian parameter inference of the dynamical SWIFT model. Invited talk presented at University of Victoria, BC, Canada.
Seelig, S. A. , Rabe, M. M. , Malem-Shinitski, N. , Reich, S. , & Engbert, R. (September 2019). Bayesian parameter estimation for the SWIFT model of eye-movement control during reading. Poster presented at Cognitive Computational Neuroscience (CCN) 2019, Berlin, Germany. DOI
Rabe, M. M. , Seelig, S. A. , Chandra, J. , Vasishth, S. , Reich, S. , & Engbert, R. (March 2019). Parameter inference and model comparison in dynamical cognitive models: SWIFT. Poster presented at 2nd SFB 1294 Data Assimilation Spring School, Dierhagen, Germany. PDF
Rabe, M. M. (2018). Generalized linear mixed modeling of Signal Detection Theory (Master of Science). Supervisors: D. S. Lindsay , M. E. J. Masson , and A. Krawitz. University of Victoria, BC, Canada. HDL OCLC PDF
Masson, M. E. J. , Rabe, M. M. , & Kliegl, R. (2017). Modulation of additive and interactive effects by trial history revisited. Memory & Cognition, 45(3), 480–492. DOI PDF
Rabe, M. M. , Kliegl, R. , & Lindsay, D. S. (November 2017). A Generalized linear mixed model approach to signal detection theory in recognition memory experiments. Poster presented at Psychonomic Society 58th Annual Meeting, Vancouver, BC, Canada.
Rabe, M. M. , Kliegl, R. , & Lindsay, D. S. (May 2017). Generalized linear mixed model of signal detection theory. Poster presented at NOWCAM, Burnaby, BC, Canada.
Fallow, K. M. , Rabe, M. M. , & Lindsay, D. S. (November 2015). Recognition memory response bias for paintings, words, and faces. Poster presented at Psychonomic Society 56th Annual Meeting, Chicago, IL, USA.
Rabe, M. M. (2015). Mixed model analysis of trial history in naming experiments (Bachelor of Science). Supervisors: R. Kliegl and M. E. J. Masson . Universität Potsdam, Germany. URN DNB OCLC PDF