Pengda Wang

Pengda Wang

Rice University

I am a second-year Industrial-Organizational Psychology Ph.D. student in the OWL Lab at Rice University, advised by Prof. Fred Oswald and Tianjun Sun (Co-Advised). Prior to this, I received my B.S. in Psychology and B.A. in Computer Science, both with high distinction, from the University of Minnesota-Twin Cities, where I had the privilege of working with Prof. Richard Landers, Prof. Deniz Ones, and Prof. Gail Ferguson.

My primary research interests are centered around leveraging innovative technologies to enhance psychometric assessments and employee selection. I am also interested in advancing open science through the adoption of novel methodologies. My aim is to become an I-O psychologist who is an expert in quantitative analysis, with a keen focus on harnessing machine learning to elevate the accuracy and fairness of psychological measurement and personnel selection systems.

I am always excited to collaborate with other researchers and explore new fields. Do not hesitate to contact me if you are interested!

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🔥 News

  • 2025.04 - Our submission entitled Differential embedding dimension functioning in natural language processing for psychological assessment, has been accepted for Oral presentation at the IMPS 2025.
  • 2025.01 - Our article, Advancing organizational science through synthetic data: A path to enhanced data sharing and collaboration, selected as Editor Commendation (22/over 1600) at Journal of Business and Psychology.
  • 2024.12 - Our symposium, Innovations in AI assessment of individual differences: Improving validity and equity, has been accepted at SIOP 2025.
  • 2024.12 - Our symposium, Machine learning for I-O 7.0: Large language models for assessments, has been accepted at SIOP 2025.
  • 2024.12 - Our alternative session presentation, Bridging disciplines: How Computer Science and I-O Psychology benefit each other, has been accepted at SIOP 2025.
  • 2024.11 - Our article, Advancing organizational science through synthetic data: A path to enhanced data sharing and collaboration, has now been accepted at Journal of Business and Psychology.
  • 2024.10 - Serve as a reviewer for SIOP 2025.
  • 2024.09 - Serve as a reviewer for CHI 2025.
  • 2024.09 - Our article, Will the real Linda please stand up... To large language models? Examining the representativeness heuristic in LLMs, selected as an Oral Spotlight Presentation (top 2%) at COLM 2024.
  • 2024.08 - Also joined the Chili Lab at Rice University.
  • 2024.08 - Also joined the SMART Lab at Rice University.
  • 2024.08 - Our article, On putting the horse (raters and criteria) before the cart (variance components in ratings), has now been published in Industrial and Organizational Psychology.
  • 2024.07 - Our article, Will the real Linda please stand up... To large language models? Examining the representativeness heuristic in LLMs, has now been accepted at COLM 2024.
  • 2024.03 - Our article, The weight of beauty in psychological research, has now been published in Industrial and Organizational Psychology.
  • 2023.12 - Our symposium, To RIASEC and beyond: Advances in vocational interest research, has been accepted at SIOP 2024.
  • 2023.12 - Our symposium, Future of performance prediction and evaluation: Artificial intelligence and big data, has been accepted at SIOP 2024.
  • 2023.08 - I joined OWL Lab at Rice University as a first-year PhD student.

đź“ť Publications

Personality structured interview for large language model simulation in personality research.

Personality structured interview for large language model simulation in personality research.
[PDF] [DOI] [Code] [BibTeX]
[Cite]: Wang, P., Zou, H., Chen, H., Sun, T., Xiao, Z., & Oswald, F. L. (2025). Personality structured interview for large language model simulation in personality research. arXiv (Cornell University). https://doi.org/10.48550/arXiv.2502.12109

[pre-print]

Automating personality-based employment interviews: Development and validation of an artificial intelligence chatbot.

Automating personality-based employment interviews: Development and validation of an artificial intelligence chatbot.
[PDF] [DOI] [BibTeX]
[Cite]: Sylvara, A., Wang, P., Sun, T., Heimann, A. L., & Ingold, P. V. (2025). Automating personality-based employment interviews: Development and validation of an artificial intelligence chatbot. OSF. https://doi.org/10.31234/osf.io/9ktmf_v3

[pre-print]

Advancing organizational science through synthetic data: A path to enhanced data sharing and collaboration.

Advancing organizational science through synthetic data: A path to enhanced data sharing and collaboration. 🏅Editor Commendation (22/over 1600)
[PDF] [DOI] [Code] [BibTeX]
[Cite]: Wang, P., Loignon, A. C., Shrestha, S., Banks, G. C., & Oswald, F. L. (2024). Advancing organizational science through synthetic data: A path to enhanced data sharing and collaboration. Journal of Business and Psychology. https://doi.org/10.31234/osf.io/4qbjz

Can LLM 'self-report'?: Evaluating the validity of self-report scales in measuring personality design in LLM-based chatbots.

Can LLM “self-report”?: Evaluating the validity of self-report scales in measuring personality design in LLM-based chatbots.
[PDF] [DOI] [Code] [BibTeX]
[Cite]: Zou, H., Wang, P., Yan, Z., Sun, T., & Xiao, Z. (2024). Can LLM “self-report”?: Evaluating the validity of self-report scales in measuring personality design in LLM-based chatbots. arXiv (Cornell University). https://doi.org/10.48550/arXiv.2412.00207

[pre-print]

From babbling to fluency: Evaluating the evolution of language models in terms of human language acquisition.

From babbling to fluency: Evaluating the evolution of language models in terms of human language acquisition.
[PDF] [DOI] [Code] [BibTeX]
[Cite]: Yang, Y.*, Wang, P.*, Plonsky, L. D., Oswald, F. L., & Chen, H. (2024). From babbling to fluency: Evaluating the evolution of language models in terms of human language acquisition. arXiv (Cornell University). https://doi.org/10.48550/arXiv.2410.13259

[pre-print]

Not yet: Large language models cannot replace human respondents for psychometric research.

Not yet: Large language models cannot replace human respondents for psychometric research.
[PDF] [DOI] [Code] [BibTeX]
[Cite]: Wang, P., Zou, H., Yan, Z., Guo, F., Sun, T., Xiao, Z., & Zhang, B. (2024). Not yet: Large language models cannot replace human respondents for psychometric research. OSF. https://doi.org/10.31219/osf.io/rwy9b

[pre-print]

On putting the horse (raters and criteria) before the cart (variance components in ratings).

On putting the horse (raters and criteria) before the cart (variance components in ratings).
[PDF] [DOI] [BibTeX]
[Cite]: Wang, P., Myeong, H., & Oswald, F. L. (2024). On putting the horse (raters and criteria) before the cart (variance components in ratings). Industrial and Organizational Psychology, 1-5. https://doi.org/10.1017/iop.2024.16

Will the real Linda please stand up... To large language models?

Will the real Linda please stand up… To large language models? Examining the representativeness heuristic in LLMs. 🏅Oral Spotlight Presentation (top 2%)
[PDF] [DOI] [Code] [BibTeX]
[Cite]: Wang, P.*, Xiao, Z.*, Chen, H., & Oswald, F. L. (2024). Will the real Linda please stand up… To large language models? Examining the representativeness heuristic in LLMs. The Conference on Language Modeling (COLM 2024). https://doi.org/10.48550/arxiv.2404.01461

The weight of beauty in psychological research.

The weight of beauty in psychological research.
[PDF] [DOI] [BibTeX]
[Cite]: Myeong, H., Wang, P., & King, E. B. (2024). The weight of beauty in psychological research. Industrial and Organizational Psychology, 17(1), 111–114. https://doi.org/10.1017/iop.2023.87

đź’¬ Conference Presentations

  • Wang, P., Sylvara, A., Sun, T., Hebl, M. R., & Oswald, F. L. (2025). Differential embedding dimension functioning in natural language processing for psychological assessment. [Oral presentation]. International Meeting of the Psychometric Society (IMPS 2025), Minneapolis, MN, United States.

  • Wang, P., & Oswald, F. L. (Co-Chairs) (2025). Bridging Disciplines: How Computer Science and I-O Psychology Benefit Each Other [Alternative Session Type]. Society for Industrial and Organizational Psychology Annual Conference (SIOP 2025), Denver, CO, United States.

  • Wang, P., Zou, H., Yan, Z., Guo, F., Sun, T., Xiao, Z., & Zhang, B. (2025). Not yet: Large language models cannot replace human respondents for psychometric research. In Hickman, L., & Liu, M.(Co-Chairs) (2025). Machine learning for I-O 7.0: Large language models for assessments [Symposium]. Society for Industrial and Organizational Psychology Annual Conference (SIOP 2025), Denver, CO, United States.

  • Wang, P., Sylvara, A., Sun, T., Hebl, M. R., & Oswald, F. L. (2025). Differential embedding dimension functioning in natural language processing for psychological assessment. In Hou, D. X., & Sun, T. (Co-Chairs) (2025). Innovations in AI assessment of individual differences: Improving validity and equity [Symposium]. Society for Industrial and Organizational Psychology Annual Conference (SIOP 2025), Denver, CO, United States.

  • Wang, P.*, Xiao, Z.*, Chen, H., & Oswald, F. L. (2024). Will the real Linda please stand up… To large language models? Examining the representativeness heuristic in LLMs [Oral presentation]. The Conference on Language Modeling (COLLM 2024), Philadelphia, PA, United States. 🏅Oral spotlight presentation (top 2%)

  • Wu, F., Wang, P., & Oswald, F. O. (2024). The influence of disability and career challenges on vocational interests. In Hoff, K. A. (Chair) (2024). To RIASEC and beyond: Advances in vocational interest research [Symposium]. Society for Industrial and Organizational Psychology Annual Conference (SIOP 2024), Chicago, IL, United States.

  • Wang, P., & Oswald, F. L. (2024). Leveraging synthetic data for advancements in organizational research. In Liou, G., & Tay, L. (Co-Chairs) (2024). Future of performance prediction and evaluation: Artificial intelligence and big data [Symposium]. Society for Industrial and Organizational Psychology Annual Conference (SIOP 2024), Chicago, IL, United States.

🎖 Honors and Awards

  • 2025, Researcher Access Program, OpenAI. $5,000.
  • 2023, Mortensen Research Award & CLA Research Scholarship, University of Minnesota-Twin Cities. $1,500.

đź“– Education

  • 2023 - Present, Ph.D. in Industrial-Organizational Psychology, Rice University
  • 2019 - 2023, B.S. in Psychology and B.A. in Computer Science, University of Minnesota-Twin Cities

đź’» Internships and Research Experiences

  • 2024.08 - Present, Chili Lab Research Assistant, Houston, TX, USA
  • 2024.08 - Present, SMART Lab Research Assistant, Houston, TX, USA
  • 2023.08 - Present, OWL Lab Research Assistant, Houston, TX, USA
  • 2022.05 - 2023.06, CFL Lab Research Assistant, Minneapolis, MN, USA
  • 2021.04 - 2023.06, TNTLAB Research Assistant, Minneapolis, MN, USA
  • 2021.12 - 2022.07, 3D HoloGroup, Inc Human Resources Intern, Minneapolis, MN, USA
  • 2020.06 - 2022.07, Ones Green Lab Research Assistant, Minneapolis, MN, USA

🫶 Service

  • SIOP 2025, Reviewer
  • CHI 2025, Reviewer