Tianjun Sun, Ph. D.
Contact Information
Office: BH 422
E-mail: tianjunsun@ksu.edu
Summary
Dr. Tianjun Sun joined K-State in 2021 as an assistant professor of psychological sciences after receiving her PhD in Psychology from University of Illinois Urbana-Champaign. Dr. Sun’s research primarily focuses on personnel selection, individual differences, psychometrics, and using advanced technology and quantitative methods to enhance staffing decisions, improve candidate/employee experiences, and solve organizational problems. Dr. Sun is actively publishing in reputable outlets and has received a series of awards from American Psychological Association (APA), Association for Psychological Science (APS), Society for Industrial and Organizational Psychology (SIOP), and Academy of Management (AOM). Her ongoing research projects are being funded by the National Institutes of Health (NIH), the National Science Foundation (NSF), and the SIOP Foundation. Currently, Dr. Sun serves as an Editorial Fellow at Journal of Applied Psychology and is on the Editorial Boards of Organizational Research Methods, Journal of Business and Psychology, and Human Performance. On the applied side, Dr. Sun has had broad experience working in consulting, testing, and tech industries, and in areas of people analytics, learning and testing, and talent assessment.
Research Interests
- Personnel selection (e.g., faking, bias, machine learning applications, responsible artificial intelligence systems)
- Individual differences (e.g., bright/dark personality, vocational/leisure interest, social/interaction behavior)
- Research methods (e.g., structural equation modeling, multilevel/longitudinal design/analysis, big data approaches)
- Applied psychometrics (e.g., item response theory, computational measurement, adaptive learning/testing)
- Cross-cultural psychology (e.g., multi-group variability/invariance, tech-based/large-scale assessment)
Selected Recent Publications
(Underline denotes student co-authors. Please see CV for details and updates.)
- Li, M., Zhang, B., Li, L., Sun, T., & Brown, A. (2024). Mix-keying or desirability-matching in the construction of forced-choice scales: An empirical investigation. Organizational Research Methods.
- Zhang, B., Luo, J., Zhang, S., Sun, T., Zhang, D. (2023). Improving the statistical performance of oblique bifactor measurement and predictive models: An augmentation approach. Structural Equation Modeling: A Multidisciplinary Journal.
- Fan, J.*, Sun, T.*, Liu, J., Zhao, T., Glorioso, M., Chen, Z., Zhang, B., & Hack, E. (2023). How well can an AI chatbot infer personality? Examining psychometric properties of machine-inferred personality scores. Journal of Applied Psychology. *Equal contribution
- Sun, T., Guo, F., Min, H., & Zhang, B. (2023). Practical machine learning algorithms for selection assessment scoring: A use case report on multi-outcome prediction. Personnel Psychology.
- Sun, T., Schilpzand, P., & Liu, Y. (2023). Workplace gossip: An integrative review of its antecedents, functions, and consequences. Journal of Organizational Behavior.
Courses Taught
- PSYCH 560: Personnel/Industrial Psychology
- PSYCH 804: Industrial and Organizational Psychology
- PSYCH 806: Psychological Measurement
- PSYCH 820: Personality Theory and Research
- PSYCH 880: Performance Appraisal
Education
- Ph.D. in Industrial-Organizational/Personality Psychology (minor in Quantitative Psychology), University of Illinois Urbana-Champaign, 2021
- M.S. in Applied Statistics, University of Illinois Urbana-Champaign, 2019
- M.S. in Industrial-Organizational Psychology, University of Illinois Urbana-Champaign, 2017
- M.S. in Psychology and Statistics (Cum Laude, with Highest Distinctions), 2015
