M.Sc. Ole Hätscher

Ole Haetscher
Doctoral Research Associate
Room: P 1a (Pavilion 1)
Consultation-hour: By arrangement via E-Mail
Phone: +49 (2 51) 83 - 3 41 15
E-Mail: o_haet01 [at] uni-muenster.de
 

 

  • Curiculum Vitae

    Professional Positions

    Since 10 / 2022
    Doctoral Research Associate, Department of Psychological Assessment and Personality Psychology, University of Münster
    Interdisciplinary collaborative project: “Medical tr.AI.ning – intelligent virtual agents for medical Education”

    04 / 2021 – 01 / 2022
    Research Assistant, Department of Statistics and Psychological Methods, University of Münster

    11 / 2016 – 03 / 2019
    Student Research Assistant, German Primate Center, University of Göttingen

    Education

    10 / 2019 – 09 / 2022
    M.Sc. Psychology, University of Münster. Master Thesis: “Machine learning-based classification of depressive symptoms using structural and functional MRI data”

    10 / 2015 – 03 / 2019
    B.Sc. Psychology, University of Göttingen. Bachelor Thesis: “Objektive Rationalität, subjektive Rationalität und Irrationalität bei eskalierendem Commitment”

    Practical & International Experience

    06 / 2022 – 09 / 2022
    Data Science working student; Westphalia DataLab GmbH, Münster, Germany

    03 / 2022 – 05 / 2022
    Data Science internship; Westphalia DataLab GmbH, Münster, Germany

    09 / 2020 – 02 / 2021
    Data Science internship; AXA Data Innovation Lab, Cologne, Germany

    05 / 2019 – 09 / 2019
    Music and education volunteer; Santa Cruz, Galapagos, Ecuador

    03 / 2018 – 05 / 2018
    Marketing internship; STU GmbH, Cologne, Germany

  • Research interest

    In my research, I am primarily interested in the potential of machine learning to predict differences in how individuals react to environmental conditions (reactivities). Specifically, my dissertation investigates whether differences in reactivities can be reliably predicted, and which person-level variables have the strongest influence on this prediction. I am investigating this in different contexts (e.g., social situations, education) for different types of reactivities (e.g., well-being, abilities) using different data sources (e.g., experience sampling, learning history data).

    In my approach, I combine data-driven bottom-up approaches with theoretically informed top-down approaches, especially for the derivation of the considered reactivities. Furthermore, I use modern methods from explainable artificial intelligence, which allow to identify important robust predictors and predictor combinations for the prediction, thus providing important suggestions for further theory building. Moreover, I aim to highlight the limitations of current statistical methods and strive to develop them further for adequate prediction of individual differences in reactivities.

    In addition to my dissertation topic, I am interested in several other innovative topics in the field of psychological diagnostics and personality psychology. In particular, I am interested in the influence of personality on the perception of and interaction with new technologies and the possibilities these technologies offer for personality research. This includes interpersonal simulations, VR-based scenarios, and Large Language Model-based interactions.

  • Publications

    Junga, A., Schmidle, P., Pielage, L., Schulze, H., Hätscher, O., Ständer, S., Marschall, B., Braun, S. A., & the medical tr.AI.ning consortium (in press). New horizons in dermatological education: Skin cancer screening with virtual reality. Journal of the European Academy of Dermatology & Venerology. https://doi.org/10.1111/jdv.19960 pdf

  • Presentations

    Hätscher, O., Klinz, J. L., Kuper, N., Scharbert, J., Kroencke, L., Grunenberg, E., & Back, M. D. (2024, April 05). A Machine Learning Approach to the Prediction of Individual Differences in Contingencies. [Conference presentation]. 4th World Conference on Personality, Willemstad, Curacao.

    Hätscher, O., Klinz, J. L., Kuper, N., Scharbert, J., Kroencke, L., Grunenberg, E., & Back, M. D. (2023, November 07). A Machine Learning Approach to the Prediction of Individual Differences in Psychological Reactivities. [Conference presentation]. 2nd TRR 318 Conference Measuring Understanding, Paderborn, Germany.

    Hätscher, O., Klinz, J. L., Scharbert, J., Grunenberg, E., & Back, M. D. (2023, September 25). A Machine Learning Approach to the Prediction of Individual Differences in Psychological Reactivities. [Conference presentation]. 17th Conference of the German Psychological Society – Personality Psychology and Psychological Diagnostics (DPPD) Section, Salzburg, Austria.

    Hätscher, O., Junga, A., Schulze, H., Kockwelp, P., Risse, B., Back, M. D., & Marschall, B. (2023, September 16). Zusammenhang von Persönlichkeitsvariablen und Leistung in der virtuellen medizinischen Ausbildung. [Poster presentation]. Jahrestagung der Gesellschaft für Medizinische Ausbildung, Osnabrück, Germany.

    Hätscher, O., Liethmann, L., Klinksieck, J. L., Breil, S. M., Ahrens, H., Geldmacher, T., Sensmeier, J., Marschall, B., & Back, M. D. (2023, July 22). Investigating the Relationship Between Self-Reported Social Skills and Actual Behavior. [Poster presentation]. 8th biennial conference of the Association for Research in Personality, Evanston, USA.

    Hätscher, O., Junga, A., Schulze, H., Kockwelp, P., Risse, B., Back, M. D., Marschall, B. (2023, April 13). Integration of VR into Medical Education. [Conference presentation]. Würtual Reality XR Meeting, Würzburg, Germany.

  • Memberships

    • German Psychological Society (DGPs; associated member)
    • Section of Personality Psychology and Psychological Assessment (DPPD)
    • Section of Methods and Evaluation