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Professorship Predictive Analytics
M. Sc. Daniel Brand
Professorship Predictive Analytics 

M.Sc. Daniel Brand

Portrait: M.Sc. Daniel Brand
M.Sc. Daniel Brand
  • Phone:
    +49 371 531-38957
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  • Office Hours:
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I am a Research Assistant at the Professorship Predictive Analytics, where I work on the advancing the understanding of human thought processes using cognitive modeling and techniques from artificial intelligence and machine learning. The focus here is on human reasoning and problem solving.
My research revolves around the exploration and modeling of human thought processes, especially with respect to inference processes and problem solving. My research is methodologically versatile and lies between cognitive science and cognitive modeling on the one hand, and data science, information systems and artificial intelligence on the other. Regardless of the respective method, the aim is to gain insight into human thought processes and to make findings accessible and applicable by means of predictive computational models.
The focus thereby lies on:
  • Cognitive Modeling
  • Predictive Modelling of Human Reasoning
  • Syllogistic Reasoning
  • Information Systems

Professional Experience

  • since 02/2022: Research Assistant, TU Chemnitz, Professorship of Predictive Analytics
  • 02/2021 - 07/2021: Research Assistant, University of Southern Denmark, Department of Design and Communication
  • 07/2020 - 02/2022: Research Assistant, University of Freiburg, Cognitive Computation Lab
  • 05/2017 - 06/2020: Research Assistant, University of Freiburg, Center for Cognitive Science

Education and Qualifications

  • 2016: MSc. Computer Science, University of Freiburg
  • 2012: BSc. Computer Science, University of Freiburg
  • SS 2022: Lecturer, Seminar: Cognitive Ergonomics, TU Chemnitz
  • SS 2021: Assistant, Seminar: Cognitive Modeling, Cognitive Computation Lab, University of Freiburg
  • SS 2020: Assistant, Seminar: Cognitive Modeling, Cognitive Computation Lab, University of Freiburg
  • WS 2019/20: Assistant, Seminar: Cognitive Reasoning: Methods, Algorithms, and Statistics to Discern Human from Artificially Generated Data, Cognitive Computation Lab, University of Freiburg
  • SS 2019: Assistant, Seminar: Cross-Domain Modeling of Human Cognition, Cognitive Computation Lab, University of Freiburg
  • SS 2014: Tutor, Cloud Computing, Department for Databases and Information Systems, University of Freiburg
  • SS 2012: Tutor, Software Engineering, Department for Software Engineering, University of Freiburg

Current Projects

  • Automatische Prozessmodellgenerierung für Kognitive Modellierung [Automatic process model generation for cognitive modeling]

Previous Projects

  • FADEp. Intentionales Vergessen und Änderungen in Arbeitsprozessen: Ein prozesskonditional-orientierter Ansatz im Verwaltungs- und IT Kontext. [Website]
  • Freiraum 2022: MeMo: Stärkung der Metakognition und Motivation Studierender durch individualisierte Smart Personal Assistants [Website]
  • CCOBRA (Cognitive COmputation for Behavioral Reasoning Analysis) Framework: Online predictive modelling of human reasoning. [Website] [GitHub]
  • PVA Webexperiment Tools: Collection of existing tasks and templates aiming to make the development of psychological web-experiments easier. [GitHub]
  • Syllogistic Task Predictor: Online interactive prediction environment for syllogistic reasoning [Website]
  • Spatial Demonstrator: Interactive environment for spatial reasoning tasks [Website]
  • pyTailorshop: Python-based implementation of the Tailorshop simulation[GitHub]
  • Dames, H., Brand, D., & Ragni, M. (2022). Evidence for Multiple Mechanisms Underlying List-Method Directed Forgetting. In J. Culbertson, A. Perfors, H. Rabagliati, & V. Ramenzoni (Eds.), Proceedings of the 44th Annual Meeting of the Cognitive Science Society (pp. 519–525).
  • Brand, D., Riesterer, N., & Ragni, M. (2022). Model-Based Explanation of Feedback Effects in Syllogistic Reasoning. Topics in Cognitive Science, 14(4), 828-844. doi: 10.1111/tops.12624. [GitHub]
  • Mittenbühler, M., Brand, D., & Ragni, M. (2022). Do Models of Syllogistic Reasoning extend to Generalized Quantifiers?. In T. C. Stewart (Ed.), Proceedings of the 20th International Conference on Cognitive Modeling (pp. 189–195). Applied Cognitive Science Lab, Penn State: University Park, PA. [PDF] [GitHub]
  • Todorovikj, S., Brand, D., & Ragni, M. (2022). Predicting Algorithmic Complexity for Individuals. In T. C. Stewart (Ed.), Proceedings of the 20th International Conference on Cognitive Modeling (pp. 240–246). Applied Cognitive Science Lab, Penn State: University Park, PA. [PDF]
  • Kettner, F., Heinrich, E., Brand, D., & Ragni, M. (2022). Reverse-Engineering of Boolean Concepts: A Benchmark Analysis. In T. C. Stewart (Ed.), Proceedings of the 20th International Conference on Cognitive Modeling (pp. 164–169). Applied Cognitive Science Lab, Penn State: University Park, PA. [PDF]
  • Brand, D., Dames, H., Puricelli, L., & Ragni, M. (2022). Rule-Based Categorization: Measuring the Cognitive Costs of Intentional Rule Updating. In J. Culbertson, A. Perfors, H. Rabagliati, & V. Ramenzoni (Eds.), Proceedings of the 44th Annual Meeting of the Cognitive Science Society (pp. 2810–2817). [PDF] [GitHub]
  • Brand, D., Mittenbühler, M., & Ragni, M. (2022). Generalizing Syllogistic Reasoning: Extending Syllogisms to General Quantifiers. In J. Culbertson, A. Perfors, H. Rabagliati, & V. Ramenzoni (Eds.), Proceedings of the 44th Annual Meeting of the Cognitive Science Society (pp. 722–728). [PDF] [GitHub]
  • Todorovikj, S., Kettner, F., Brand, D., Beggiato, M., & Ragni, M. (2022). Predicting Individual Discomfort in Autonomous Driving. In J. Culbertson, A. Perfors, H. Rabagliati, & V. Ramenzoni (Eds.), Proceedings of the 44th Annual Meeting of the Cognitive Science Society (pp. 3103–3109).
  • von Stülpnagel, R., Findler, F., & Brand, D. (2022). Census-Based Variables Are Informative about Subjective Neighborhood Relations, but Only When Adjusted for Residents’ Neighborhood Conceptions. Sustainability, 14(8), 4434. doi: 10.3390/su14084434.

Show all

  • "Effect of Response Format on Syllogistic Reasoning" @ CogSci 2023. Online, July 2023. [poster]
  • "Uncovering iconic patterns of syllogistic reasoning: A clustering analysis" @ 21th International Conference on Cognitive Modeling. Online, July 2023. [slides]
  • "Do models of syllogistic reasoning extend to generalized quantifiers?" @ 20th International Conference on Cognitive Modeling. Online, July 2022. [slides]
  • "Model-based explanation of feedback effects in syllogistic reasoning" @ 19th International Conference on Cognitive Modeling. Online, July 2021. [talk]
  • "Unifying models for belief and syllogistic reasoning" @ 43th Annual Meeting of the Cognitive Science Society. Online, July 2021. [slides] [poster]
  • "How usable is Galaxy? A usability evaluation of Galaxy" @ 2019 Galaxy Community Conference (GCC2019). Freiburg, Germany, July 2019. [poster]
  • "Extending TransSet: An Individualized Model for Human Syllogistic Reasoning" @ 18th International Conference on Cognitive Modeling. Online, July 2020. [short slides] [talk]

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