 | Clemens Stachl, Ph.D.Director Clemens Stachl is Associate Professor of Behavioral Science at the University of St. Gallen and Director of the IBT. He holds a PhD in Psychology and has worked as a postdoctoral scholar at Stanford University and Ludwig-Maximilians-Universität München. His work lies at the intersection of the behavioral- and computational sciences. He uses computational technologies to objectively quantify and study everyday human behavior, situational characteristics, and psychological processes. In particular he investigates (1) how technology can be used to better understand human behavior, experiences, and preferences, (2) how AI/machine learning can be used to statistically recognize individual differences (e.g., personality traits) from digital footprints, and how (3) stable user traits and momentary states can be considered in the design of intelligent systems and services to support people in their everyday lives. Additionally, he studies and thematizes the consequences and implications that can arise from the widespread and unreflected use of digital behavioral data in algorithmic decision making, for individuals and our societies as a whole. Clemens Stachl has published numerous papers in leading journals and conferences in the fields of Personality Psychology (e.g., European Journal of Personality, Journal of Personality and Social Psychology), Behavioral Science (e.g., Behavioral and Brain Sciences, PNAS), and Human-Computer Interaction (CHI). For his work he received the prize for digital assessment (German Psychological Society) and the best paper award from German Society for Online-Research. His research has also been featured in worldwide media outlets (e.g., “Forbes”, “Harvard Business Review”, “Fast Company” and “Die Zeit”). He currently teaches courses on Mobile Sensing and Behavioral Metrics Marketing Communication, and Consumer Behaviour at the School of Management at St. Gallen. Selected Publications- Stachl, C., Au, Q., Schoedel, R., Gosling, S. D., Harari, G. M., Buschek, D., Völkel, S. T., Schuwerk, T., Oldemeier, M., Ullmann, T., Hussmann, H., Bischl, B., & Bühner, M. (2020). Predicting personality from patterns of behavior collected with smartphones. Proceedings of the National Academy of Sciences of the United States of America, 117(30), 17680–17687. doi.org/10.1073/pnas.1920484117
- Stachl, C., Pargent, F., Hilbert, S., Harari, G. M., Schoedel, R., Vaid, S., Gosling, S. D., & Bühner, M. (2020). Personality Research and Assessment in the Era of Machine Learning. European Journal of Personality, 34(5), 613–631. https://doi.org/10.1002/per.2257
- Grunenberg, E., Stachl, C., Breil, S. M., Schäpers, P., & Back, M. D. (2025). Predicting and Explaining Assessment Center Judgments: A Cross-Validated Behavioral Approach to Performance Judgments in Interpersonal Assessment Center Exercises. Human Resource Management, 64(2), 423–445. https://doi.org/10.1002/hrm.22252
- Harari, G. M., Müller, S. R., Stachl, C., Wang, R., Wang, W., Bühner, M., Rentfrow, P. J., Campbell, A. T., & Gosling, S. D. (2019). Sensing Sociability: Individual Differences in Young Adults’ Conversation, Calling, Texting, and App Use Behaviors in Daily Life. Journal of Personality and Social Psychology. doi.org/10.1037/pspp0000245
- Matz, S. C., Bukow, C. S., Peters, H., Deacons, C., Dinu, A., & Stachl, C. (2023). Using machine learning to predict student retention from socio-demographic characteristics and app-based engagement metrics. Scientific Reports, 13(1), https://doi.org/10.1038/s41598-023-32484-w
- Ilievski, F., Hammer, B., van Harmelen, F., Paassen, B., Saralajew, S., Schmid, U., Biehl, M., Bolognesi, M., Dong, X. L., Gashteovski, K., Hitzler, P., Marra, G., Minervini, P., Mundt, M., Ngomo, A.-C. N., Oltramari, A., Pasi, G., Saribatur, Z. G., Serafini, L., … Villmann, T. (2025). Aligning generalization between humans and machines. Nature Machine Intelligence, 1–12. https://doi.org/10.1038/s42256-025-01109-4
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