GeezerVison

I investigate the cognitive and computational mechanisms that allow us to rapidly make sense of language in real time. To understand this process, I ask:

• How is each word that we hear or read combined with our understanding of the text so far?
  
• What sources of knowledge do we recruit?
  
• How are these sources integrated, especially when they are in conflict?
  

To answer these questions, I use experimental and computational methods ranging from eye-tracking to large-scale crowd-sourcing, corpus methods, Bayesian data analysis, and computational cognitive modeling including large language models.

I am a tenure-track professor at the Institute of Linguistics at the University of Stuttgart (positive interim evaluation in 2025, final evaluation underway). Previously, I held postdoctoral positions at the University of Potsdam, UC San Diego, and the University of Oxford. I earned my PhD in Cognitive Science at the University of Potsdam, where I also served as a visiting professor for two years. In addition to my academic work, I have worked as a software engineer, founded two companies, and collaborated with sound artists and composers at the intersection of science and art.

Research pillars:

• Mechanisms of Language Comprehension and Reading: Investigating cognitive processes across multiple levels, from sub-lexical single-word reading to sentence- and discourse-level phenomena like agreement attraction, expectation, and syntactic dependencies, and implicit biases. This includes analyzing reading strategies, scanpaths, and eye movement dynamics to understand processing difficulties and predict reading comprehension.
  
• Computational Cognitive Modeling: Evaluating computational models against behavioral data. This encompasses working memory-based parsing models (e.g., cue-based retrieval in ACT-R) as well as comparing human gaze and sentence processing behavior against representations in Large Language Models.
  
• Research Methods and Statistical Inference: Developing and evaluating rigorous experimental methods (e.g., eye-tracking, EEG co-registration), advancing statistical analysis procedures in psycholinguistics (e.g., scanpath methods), and building open-source software tools for the research community.
  

Teaching interests: Human sentence processing, eye-tracking, Bayesian data analysis, corpus methods, large language models, web-based experimental methods, scientific computing, foundations of math.

Media coverage:

• New York Times (25.01.2020): She’s the Next President. Wait, Did You Read That Right?
  
• WNYC Studios, The Takeaway: America's weekday conversation (podcast, 29.01.2020): Could "She" Be President? A Look at Pronoun Bias in Politics
  
• MIT News (08.01.2020): “She” goes missing from presidential language. Also reported by ScienceDaily, AAAS EurekaAlert!, and Phys.org.
  
• Kunstjahr 2013 – Die Zeitschrift, die Bilanz zieht, Lindinger + Schmid. Article about my science/art cross-over project with sound artist Christoph Illing.
  

My name is a bit unusual which may cause confusion. To clarify: My first name is “Titus” and my last name is “von der Malsburg”. Despite common misconceptions, my last name should not be written as “Von Der Malsburg”, just “Malsburg”, or “van der Malsburg” (with Dutch “van” instead of “von”). Nor should “von der” be treated as a middle name. For historical and practical reasons, it’s customary to list my name alphabetically under “M” not “v”. In BibTeX entries, it’s best to write {von der Malsburg}, Titus and to include the field sortname = {Malsburg} when I’m the first author of a publication.

Members of my group are: Candy Adusei, Ondřej Drobil, Mohammed Said and Qibi Wang. We’re also supported by a highly competent lab assistant, Rebecca Fiestas Cueto, who is in charge of preparing and conducting some of our eye-tracking experiments.

We are currently funded by a joint DFG project on the processing of resumptive pronouns, in collaboration with Aya Meltzer-Asscher at Tel Aviv University.

Candy Adusei

Ondřej Drobil

Mohammed Said

Qibi Wang

Together, we use a range of tools to conduct our research, including an EyeLink 1000 Plus eyetracker, a TRACKPixx3 eye-tracker (2 kHz, binocular, similar to the EyeLink) and three GazePoint trackers (two GP3 HD and one GP3). The latter are primarily but not just used for eye-tracking education.

Working with us

Better described as random technical notes, some of which are taken from our internal lab wiki.

• We use a plain GitHub repository for project and knowledge management (Feb 2025)
  
• How we do weekly updates (Feb 2024)
  
• A guide and template for self-hosted experiments (Nov 2023)
  
• Cohen’s d in simple linear regression models (Sept 2022)
  
• How to calculate worker compensation for Amazon Mechanical Turk (Dec 2016)
  
• Latin square designs in Ibex experiments (Feb 2016)
  
• Bayesian mixed-effects models using MCMCglmm (June 2015, horribly obsolete because we now have Stan-based packages such as brms, rstanarm, and rethinking)
  
• Predict vs simulate in lme4 (May 2015)
  

Science fundamentally relies on open source / libre software that prioritizes users’ needs over shareholders' interests. As such, we are committed to contributing to a robust academic software ecosystem developed and maintained by researchers for researchers.

For conducting experiments:

R packages:

Emacs packages:

Manuscripts (non-peer-reviewed)

Peer-reviewed journal articles

Peer-reviewed proceedings articles

Other publications