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Professorship Predictive Analytics
Prädiktive Verhaltensanalyse

Daniel Brand

Portrait: M.Sc. Daniel Brand
M.Sc. Daniel Brand
  • Phone:
    +49 371 531-38957
  • Email:
  • Office Hours:
    Please make an appointment via e-mail first.

Research Interests

  • Cognitive Modeling
  • Predictive Modelling of Human Reasoning
  • Syllogistic Reasoning
  • Information Systems

CV

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

Teaching

  • 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

Projects

  • FADEp. Intentionales Vergessen und Änderungen in Arbeitsprozessen: Ein prozesskonditional-orientierter Ansatz im Verwaltungs- und IT Kontext. [Website]
  • CCOBRA (Cognitive COmputation for Behavioral Reasoning Analysis) Framework: Online predictive modelling of human reasoning. [Website] [GitHub]
  • Freiraum 2022: MeMo: Stärkung der Metakognition und Motivation Studierender durch individualisierte Smart Personal Assistants [Website]

Publications

  • Riesterer, N., Brand, D., & Ragni, M. (2020). Do Models Capture Individuals? Evaluating Parameterized Models for Syllogistic Reasoning. In S. Denison, M. Mack, Y. Xu, & B. C. Armstrong (Eds.), Proceedings of the 42nd Annual Conference of the Cognitive Science Society (pp. 3377-3383). Cognitive Science Society. [PDF] [GitHub]
  • Brand, D., Riesterer, N., Dames, H., & Ragni, M. (2020). Analyzing the Differences in Human Reasoning via Joint Nonnegative Matrix Factorization. In S. Denison, M. Mack, Y. Xu, & B. C. Armstrong (Eds.), Proceedings of the 42nd Annual Conference of the Cognitive Science Society (pp. 3254-3260). Cognitive Science Society. [PDF] [GitHub]
  • Riesterer, N., Brand, D., & Ragni, M. (2020). Predictive Modeling of Individual Human Cognition: Upper Bounds and a New Perspective on Performance. Topics in Cognitive Science. doi: 10.1111/tops.12501. [GitHub]
  • Riesterer, N., Brand, D., Dames, H., & Ragni, M. (2020). Modeling Human Syllogistic Reasoning: The Role of "No Valid Conclusion". Topics in Cognitive Science, 12(1), 446-459. doi: 10.1111/tops.12487. [GitHub]
  • von Stülpnagel, R., Brand, D., & Seemann, A. K. (2019). Your neighbourhood is not a circle, and you are not its centre. Journal of Environmental Psychology, 66, 101349. doi: 10.1016/j.jenvp.2019.101349.
  • Brand, D., Riesterer, N., & Ragni, M. (2019). On the Matter of Aggregate Models for Syllogistic Reasoning: A Transitive Set-Based Account for Predicting the Population. In Stewart T. (Ed.), Proceedings of the 17th International Conference on Cognitive Modeling. [PDF] [GitHub]
  • Riesterer, N., Brand, D., & Ragni, M. (2019). Predictive Modeling of Individual Human Cognition: Upper Bounds and a New Perspective on Performance. In Stewart T. (Ed.), Proceedings of the 17th International Conference on Cognitive Modeling. [PDF] [GitHub]
  • Riesterer, N., Brand, D., Dames, H., & Ragni, M. (2019). Modeling Human Syllogistic Reasoning: The Role of "No Valid Conclusion", In Goel, A., Seifert, C., & Freska, C. (Eds.), Proceedings of the 41st Annual Conference of the Cognitive Science Society. [PDF] [GitHub]
  • Ragni, M., Dames, H., Brand, D., & Riesterer, N. (2019). When Does a Reasoner Respond: Nothing Follows?, In Goel, A., Seifert, C., & Freska, C. (Eds.), Proceedings of the 41st Annual Conference of the Cognitive Science Society.

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Talks and Poster Presentations

  • "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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