Daniel Brand

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

• 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

• 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

• 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]

• Riesterer N., Brand D., Ragni M. (2018) The Predictive Power of Heuristic Portfolios in Human Syllogistic Reasoning. In: Trollmann F., Turhan AY. (Eds.) KI 2018: Advances in Artificial Intelligence. KI 2018. Lecture Notes in Computer Science, vol 11117. Springer, Cham. [Poster] [GitHub]
• Riesterer, N., Brand, D., & Ragni, M. (2018) A Machine Learning Approach for Syllogistic Reasoning. In C. Rothkopf et al. (Eds.), Proceedings of the 14th Biannual Conference of the German Society for Cognitive Science (p. 54). [Poster]

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• "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]

• Research Gate
• ORCID