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Professur Prädiktive Verhaltensanalyse
Daniel Brand

Daniel Brand

Portrait: M.Sc. Daniel Brand
M.Sc. Daniel Brand
  • Telefon:
    +49 371 531-38957
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Forschungsschwerpunkte

  • Kognitive Modellierung
  • Prädiktive Modellierung menschlichen Schlussfolgerns
  • Syllogistisches Schließen
  • Informationssysteme

Lebenslauf

Berufserfahrung

  • seit 02/2022: Wissenschaftlicher Mitarbeiter; TU Chemnitz; Professur Prädiktive Verhaltensanalyse
  • 02/2021 - 07/2021: Wissenschaftlicher Mitarbeiter; Syddansk Universitet (SDU); Abteilung für Design und Kommunikation
  • 07/2020 - 02/2022: Wissenschaftlicher Mitarbeiter; Albert-Ludwigs-Universität Freiburg; Cognitive Computation Lab
  • 05/2017 - 06/2020: Wissenschaftlicher Mitarbeiter; Albert-Ludwigs-Universität Freiburg; Center for Cognitive Science

Bildungsweg und Qualifikationen

  • 2016: MSc. Computer Science, Albert-Ludwigs-Universität Freiburg
  • 2012: BSc. Computer Science, Albert-Ludwigs-Universität Freiburg

Lehre

  • SS 2022: Dozent; Seminar: Kognitive Ergonomie; TU Chemnitz
  • SS 2021: Assistent; Seminar: Cognitive Modeling; Cognitive Computation Lab; Albert-Ludwigs-Universität Freiburg
  • SS 2020: Assistent; Seminar: Cognitive Modeling; Cognitive Computation Lab; Albert-Ludwigs-Universität Freiburg
  • WS 2019/20: Assistent; Seminar: Cognitive Reasoning: Methods, Algorithms, and Statistics to Discern Human from Artificially Generated Data; Cognitive Computation Lab; Albert-Ludwigs-Universität Freiburg
  • SS 2019: Assistent; Seminar: Cross-Domain Modeling of Human Cognition; Cognitive Computation Lab; Albert-Ludwigs-Universität Freiburg
  • SS 2014: Tutor; Cloud Computing; Department for Databases and Information Systems; Albert-Ludwigs-Universität Freiburg
  • SS 2012: Tutor; Software Engineering; Department for Software Engineering; Albert-Ludwigs-Universität Freiburg

Projekte

  • 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]

Publikationen

  • Brand, D., Mittenbühler, M., & Ragni, M. (2022). Generalizing Syllogistic Reasoning: Extending Syllogisms to General Quantifiers. In Proceedings of the 44th Annual Meeting of the Cognitive Science Society. [PDF] [GitHub]
  • Todorovikj, S., Kettner, F., Brand, D., Beggiato, M., & Ragni, M. (2022). Predicting Individual Discomfort in Autonomous Driving. In Proceedings of the 44th Annual Meeting of the Cognitive Science Society.
  • 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.
  • Ragni, M., Brand, D., & Riesterer, N. (2021). The Predictive Power of Spatial Relational Reasoning Models: A New Evaluation Approach. Frontiers in Psychology, 12. doi: 10.3389/fpsyg.2021.626292. [GitHub]
  • Brand, D., Riesterer, N., and Ragni, M. (2021). Unifying models for belief and syllogistic reasoning. In Proceedings of the 43th Annual Meeting of the Cognitive Science Society, eds. T. Fitch, C. Lamm, H. Leder, and K. T. mar Raible. [PDF] [GitHub]
  • Brand, D., Riesterer, N., & Ragni, M. (2021). Model-Based Explanation of Feedback Effects in Syllogistic Reasoning. In Proceedings of the 19th International Conference on Cognitive Modeling. [GitHub]
  • Mannhardt, J., Bucher, L., Brand, D., & Ragni, M. (2021). Predicting spatial belief reasoning: comparing cognitive and AI models. In Proceedings of the 19th International Conference on Cognitive Modeling. [PDF]
  • Riesterer, N., Brand, D., & Ragni, M. (2020). Feedback Influences Syllogistic Strategy: An Analysis based on Joint Nonnegative Matrix Factorization. In Proceedings of the 18th International Conference on Cognitive Modeling. [PDF] [GitHub]
  • Brand, D., Riesterer, N., & Ragni, M. (2020). Extending TransSet: An Individualized Model for Human Syllogistic Reasoning. In Proceedings of the 18th International Conference on Cognitive Modeling. [PDF] [GitHub]

alle anzeigen

Vorträge und Posterpräsentationen

  • "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]

Zusätzliches