Sara Todorovikj
Research Interests
- Cognitive Modeling
- Predictive Modeling
- Knowledge Representation and Reasoning
- Conditional and Syllogistic Reasoning
CV
Professional Experience
- Since 10/2021: Research Assistant, TU Chemnitz, Professorship of Predictive Analytics
- 04/2021 - 10/2021: Student Research Assistant, University of Freiburg, Foundations of Artificial Intelligence
- 02/2021 - 10/2021: Research Assistant, University of Southern Denmark, Department of Design and Communication
- 05/2018 - 10/2021: Student Research Assistant, University of Freiburg, Cognitive Computation Lab
- 06/2015 - 08/2016: Student Research Assistant, German Research Center for Artificial Intelligence, Robotics Innovation Center Bremen
Education and Qualifications
- 10/2016 - 10/2020: MSc. Computer Science, University of Freiburg
- 09/2013 - 09/2016: BSc. Computer Science, Jacobs University Bremen
Teaching
- SS 2024: Partial assistant, Cognitive Modeling, TU Chemnitz
- WS 2023/24: Assistant, Predictive Analytics, TU Chemnitz
- SS 2023: Lecturer, Applied Machine Learning Seminar, TU Chemnitz
- SS 2023: Assistant, Cognitive Modeling, TU Chmenitz
- WS 2022/23: Lecturer, Thinking Seminar, TU Chemnitz
- WS 2022/23: Assistant, Predictive Analytics, TU Chemnitz
- SS 2022: Lecturer, Applied Machine Learning Seminar, TU Chemnitz
- SS 2022: Assistant, Predictive Analytics 2, TU Chemnitz
- WS 2021/22: Assistant, Predictive Analytics, TU Chemnitz
- WS 2018/19: Tutor, Image Processing and Computer Graphics, University of Freiburg
Publications
- Todorovikj, S., Brand, D., & Ragni, M. (2024). Model Verification and Preferred Mental Models in Syllogistic Reasoning. In Proceedings of the 22nd International Conference on Cognitive Modeling.
- Brand, D., Todorovikj, S., & Ragni, M. (2024). Predicting Complex Problem Solving Performance in the Tailorshop Scenario. In Proceedings of the 22nd International Conference on Cognitive Modeling.
- Brand, D., Todorovikj, S., & Ragni, M. (2024). Necessity, Possibility and Likelihood in Syllogistic Reasoning. In L. K. Samuelson, S. L. Frank, M. Toneva, A. Mackey, & E. Hazeltine (Eds.),Proceedings of the 46th Annual Conference of the CognitiveScience Society. 2776-2782 [PDF]
- Blickle, J., Todorovikj, S., & Ragni, M. (2024). Evaluating the Predictive Power of Tasks and Items in IQ Tests. In L. K. Samuelson, S. L. Frank, M. Toneva, A. Mackey, & E. Hazeltine (Eds.),Proceedings of the 46th Annual Conference of the CognitiveScience Society. 4833-4840 [PDF]
- Todorovikj, S., Brand, D., & Ragni, M. (2023). Preferred Mental Models in Syllogistic Reasoning. In Proceedings of the 21st International Conference on Cognitive Modeling. [PDF]
- Todorovikj, S., Brand, D., & Ragni, M. (2022). Predicting Algorithmic Complexity for Individuals. In Proceedings of the 20th International Conference on Cognitive Modeling. [PDF]
- 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. [PDF]
- Todorovikj, S. & Ragni, M. (2021). How good can an individual's conclusion endorsement be predicted?. In Proceedings of the 19th International Conference on Cognitive Modeling. [PDF]
- Todorovikj, S. & Ragni, M. (2021). Deductive vs. Inductive Instructions: Evaluating the Predictive Powers of Cognitive Models for Conditional Reasoning. In Proceedings of 7th Workshop on Formal and Cognitive Reasoning. [PDF]
- Todorovikj, S., Kern-Isberner, G., & Ragni, M. (2021). On the Cognitive Adequacy of Non-monotonic Logics. In Proceedings of the 19th International Workshop on Non-Monotonic Reasoning. [PDF]
- Ragni, M., Wagner, F., & Todorovikj, S. (2020). The Power of Nonmonotonic Logics to Predict the Individual Reasoner. In Proceedings of the 18th International Conference on Cognitive Modeling. [PDF]
- Todorovikj, S., Friemann, P., & Ragni, M. (2019). A Cross-Domain Theory of Mental Models. In Pacific Rim Knowledge Acquisition Workshop. [PDF]
- Todorovikj, S., Friemann, P., & Ragni, M. (2019). Combining Mental Models and Probabilities: A new Computational Cognitive Approach for Conditional Reasoning. In Proceedings of the 17th International Conference on Cognitive Modeling. [PDF]
Talks and Poster Presentations
- "Model Verification and Preferred Mental Models in Syllogistic Reasoning" @ 22nd International Conference on Cognitive Modeling. Tilburg, Netherlands, July 2024. [slides]
- "Predicting Complex Problem Solving Performance in the Tailorshop Scenario" @ 22nd International Conference on Cognitive Modeling. Tilburg, Netherlands, July 2024. [slides]
- "Necessity, Possibility and Likelihood in Syllogistic Reasoning" @ 46th Annual Meeting of the Cognitive Science Society. Rotterdam, Netherlands, July 2024. [poster]
- "Evaluating the Predictive Power of Tasks and Items in IQ Tests" @ 46th Annual Meeting of the Cognitive Science Society. Rotterdam, Netherlands, July 2024. [poster]
- "Towards Bridging the Gap Between Conditional and Syllogistic Reasoning" @ 45th Annual Meeting of the Cognitive Science Society. Sydney, Australia (Online), July 2023. [slides]
- "Preferred Mental Models in Syllogistic Reasoning" @ 21st International Conference on Cognitive Modeling. Online, June 2023. [slides] [video]
- "Predicting Individual Discomfort in Autonomous Driving" @ 44th Annual Meeting of the Cognitive Science Society. Toronto, Canada (Online), July 2022. [slides]
- "Predicting Algorithmic Complexity for Individuals" @ 20th International Conference on Cognitive Modeling. Online, July 2022. [slides] [video]
- "On the Cognitive Adequacy of Non-monotonic Logics" @ 19th International Workshop on Non-Monotonic Reasoning. Hanoi, Vietnam (Online), November 2021.
- "Deductive vs. Inductive Instructions: Evaluating the Predictive Powers of Cognitive Models for Conditional Reasoning" @ 7th Workshop on Formal and Cognitive Reasoning. Berlin, Germany (Online), September 2021.
- "How good can an individual's conclusion endorsement be predicted?" @ 19th International Conference on Cognitive Modeling. Online, July 2021. [video]
Supervised Theses
- "Empirical Reanalysis of the BIS-HB using Machine Learning for the Purpose of Intelligence Test Optimisation"
Joshua Blickle (Master Thesis in Psychology, 2023)