Roles
Incoming Assistant Professor, College of Arts and Sciences
Biography
Dr. Mirea is an incoming Assistant Professor in the Department of Psychology, starting in summer 2027. His research investigates the socio-cognitive mechanisms underlying mental health and its treatment as they manifest in the real world, as well as how digital technologies like social media and AI interact with users’ mental health. He is especially interested in the psychological processes underlying social connection and how these shape our interactions with other humans, and increasingly with AI, in virtual and text-based settings. His approach leverages computational tools (cognitive modeling and large language models) to study behavior in both controlled experiments and digital environments.
Website: dan-mirea.com
E-Mail: danmirea@sas.upenn.edu
Dr. Mirea anticipates recruiting a PhD student to start in Fall 2027 through either the Psychological Sciences or Clinical Psychology program. Please get in touch if you are interested.
Education & Training
Education
- Princeton University - PhD, 2026
- University of Cambridge - MSci, 2019
- University of Cambridge - BA, 2018
Training
- MindCORE Postdoctoral Fellow - University of Pennsylvania, 2026-2027
Honors & Awards
- Research and Academia Award - Young Futures, 2026
- Psychology of Technology Dissertation Award - Psychology of Technology Institute, 2025
- Honorific Fellowship - Princeton University, 2025
- Diversity Award - Society for Affective Science, 2025
- Exemplar Mentor Award - Princeton University, 2024
Publications
Mirea, D.-M., Chen, S., Palacio-Soto, K., Ding, J., Mildner, J.N., Kelley, S.W., Gillan, C.M., Nook, E.C.*, Niv, Y.* (2026). Depression is associated with higher sensitivity to social media rewards. JAMA Psychiatry. 83(9), 930–938. https://doi.org/10.1001/jamapsychiatry.2026.1430
Mirea, D.-M., Holton, E., Chandrasekhar, D., Niv, Y. (2026). Stage 1 Registered Report: Testing the longitudinal and causal effect of social media rewards on mood and mental health in young adults. Lifecycle Journal, 2. https://doi.org/10.71240/lcyc.942738.
Barrie, C., Crockett, M.J., Globig, L., McLoughlin, K., Mirea, D.-M., … (2026). A reporting checklist for large language models in behavioural science. Nature Human Behaviour 10, 1182–1186. https://doi.org/10.1038/s41562-026-02492-7
Mirea, D.-M., Nook, E.C., Niv, Y. (2025). Cognitive modeling of real-world behavior for understanding mental health. Trends in Cognitive Sciences 30, 350-363. https://doi.org/10.1016/j.tics.2025.07.009
Coles, N.A., Perz, B., Behnke, M., Eichstaedt, J. C., …, Berwian, I. M., Chiu, J. C., Mirea, D.-M., Nook, E. C., Vartiainen, H. I., Whiting, C., et al. (2025). Big team science reveals promises and limitations of machine learning efforts to model the physiological basis of affective experience. Royal Society Open Science 12, 241778. https://royalsocietypublishing.org/doi/10.1098/rsos.241778
Chiu, J.C., Budny, N., Sameer, A., Baah, P.A., Mirea, D.-M., Berwian, I.M., Niv, Y. (2025). Emotions Shape Effort-Reward Choices: Positive Valence Decreases Effort, Except Under High Arousal. In Proceedings of the 2025 Symposium on Eye Tracking Research and Applications. https://dl.acm.org/doi/10.1145/3715669.3726794
Mirea, D.-M.*, Rathje, S.*, Sucholutsky, I., Marjieh, R., Robertson, C., Van Bavel, J.J. (2024). GPT is an effective tool for multilingual psychological text analysis. Proceedings of the National Academy of Sciences, 121 (34), e2308950121. https://www.pnas.org/doi/10.1073/pnas.2308950121
Mirea, D.-M.*, Shin, Y.S.*, Dubrow, S., Niv, Y. (2024). The ubiquity of time in latent-cause inference. Journal of Cognitive Neuroscience, 36 (11): 2442–2454. https://direct.mit.edu/jocn/article-abstract/36/11/2442/123970/The-Ubiquity-of-Time-in-Latent-cause-Inference
Mirea, D.-M., Martin-Key, N.A., Barton-Owen, G., Olmert, T. et al. (2021). The impact of an online psychiatric assessment on the mental health and wellbeing of participants presenting with depressive symptoms: longitudinal observational study. JMIR Mental Health, 8(2), e23813. https://mental.jmir.org/2021/2/e23813/
Martin-Key, N.A., Mirea, D.-M., Olmert, T., Cooper, J.D. et al. (2021). Towards an extended definition of major depressive disorder symptomatology: digital assessment and cross-validation study. JMIR Formative Research, 5(10):e27908. https://formative.jmir.org/2021/10/e27908/authors
Tomasik, J., Han, S.Y.S., Barton-Owen, G., Mirea, D.-M., Martin-Key, N.A., et al. (2021). A machine learning algorithm to differentiate bipolar disorder from major depressive disorder using an online mental health questionnaire and blood biomarker data. Translational Psychiatry, 11(1), 1-12. https://www.nature.com/articles/s41398-020-01181-x
