I regularly take PhD students. If you are interested in doing a PhD with me at LSE, please feel free to send me an email. In particular, I have recently become very interested in developing psychometric methods for evaluating AI systems (see here for more information) and are therefore seeking for PhD students who'd love to work in this direction.

Contact Information

• Office:
  Columbia House, Room 5.16
  Houghton Street, London, WC2A 2AE
  
  

• Faculty webpage: Link

• Research lab website: Link

• Google scholar page: Link
  

• Email: y.chen186@lse.ac.uk
  
  

CURRICULUM VITAE

• Link
  
  

Educational Background

• PhD, Statistics, Columbia University in the city of New York, 2016
  (My Node on Math Genealogy Tree: Click Link)
  
  

Research

My research sits at the intersection of psychometric principles, advanced statistical modeling—predominantly latent variable frameworks—and machine learning techniques to solve complex data challenges in the social and behavioral sciences. More recently, my work has expanded to address the profound sociological and psychological shifts brought about by the rapid advancement of artificial intelligence. Specifically, I am developing new psychometric methodologies for AI evaluation, as well as adapted frameworks for human assessment in environments where AI agents are actively involved. As AI continues to introduce novel behavioral and social dynamics, I believe that measurement science will play an essential role in decoding these systems, ensuring that both human and artificial capabilities are evaluated with genuine statistical rigor, validity, and depth. I run a psychometric lab with Professor Irini Moustaki at LSE. Many of my recent works on psychometrics are with members of this lab. I also work with other colleagues at LSE as well as external collaborators on statistical and machine learning theory and methods.

Some recent publications that reflect my recent research interests:

• Book

  • Moustaki, I., Steele, F., Chen, Y., and Bartholomew, D. (2026) Analysis of Multivariate Social Science Data: Statistical Machine Learning Methods (3rd ed.). Oxfordshire, UK: Taylor & Francis.

• Journal publications

  • Lee, S.M. and Chen, Y. (2026+) Pairwise Comparisons without Stochastic Transitivity: Model, Theory and Applications. Journal of Machine Learning Research. To appear.

  • Cen, Z., Gu, C., Zhu, J., Li, T., Chen, Y., Shi, C. (2026+). Learning Perturbations to Extrapolate Your LLM. STAI-X 2026 Conference (The First Conference on Statistics and Trustworthy AI for Cross (X)-Domain Acceleration). Accepted (with paper honorable mention).

  • Ouyang, J., Chen, Y., Li, C., Xu, G. (2026+) Accounting for Measurement Bias: A New Framework for Reliable Country Ranking in Large-Scale Educational Assessments. Journal of American Statistical Association. To appear.

  • Lee, S. Chen, Y. and Li. X. (2026+) Sequential Change Point Detection with FDR Control in Reconfigurable Sensor Networks. IEEE Transactions on Information Theory. To appear.

  • Lee, S.M., Chen, Y. and Sit, T. (2026+) A Latent Variable Approach to Learning Highdimensional Multivariate Longitudinal Data. Journal of the American Statistical Association. To appear.

  • Ma, T., Zhu, J. Cai, H., Qi, Z., Chen, Y., Shi, C. and Laber, E. (2026+) Sequential Knockoffs for Variable Selection in Reinforcement Learning. Journal of American Statistical Association. To appear.

  • Alfonzetti, G., Bellio, R., Chen, Y. and Moustaki, I. (2026). When Composite Likelihood meets Stochastic Approximation. Journal of American Statistical Association. 120(551), 1906-1918.

  • Chen, F., Chen, Y., Ying, Z. and Zhou, F. (2025). Dynamic Factor Analysis of Highdimensional Recurrent Events. Biometrika. 112, asaf028.

  • Wallin, G., Chen, Y., Lee, Y-H, and Li, X., (2025) A Latent Variable Model with Change Points and Its Application to Time Pressure Effects in Educational Assessment. Annals of Applied Statistics. 19, 2490-2516

  • Qiao, J., Chen, Y. and Ying, Z. (2025) Exact Exploratory Bi-factor Analysis: A Constraintbased Optimisation Approach. Psychometrika. 90, 998 - 1013

  • Cardenas-Hurtado, C.A., Moustaki, I., Chen, Y. and Marra, G. (2025). Generalized Latent Variable Models for Location, Scale, and Shape parameters. Psychometrika. 90, 932 - 956.

  • Chen, Y., Li, X., Liu, J. and Ying, Z. (2025). Item Response Theory – A Statistical Framework for Psychological Measurement (with discussions). Statistical Science. 40, 167–194.

  • Chen, Y. and Li, X. (2024). A Note on Entrywise Consistency for Mixed-data Matrix Completion. Journal of Machine Learning Research. 25(343): 1-66.

  • Wallin, G., Chen, Y. and Moustaki, I. (2024). DIF Analysis with Unknown Groups and Anchor Items. Psychometrik. 89, 267–295.
    
    

Publications

See my CV (link) or google scholar page (link).

Professional and Editorial Work

• Member of the editorial council of the Psychometric Society, 2024 - 2030

• Associate editor of British Journal of Mathematical and Statistical Psychology, 2022 -

• Associate editor of Psychometrika, 2019 -

• Associate editor of Psychological Methods, 2025 -

• Associate editor of Journal of Educational and Behavioural Statistics, 2025 -

• Associate editor of Journal of American Statistical Association, 2026 -

• Associate editor of the American Statistician, 2026 -

• Editorial board member of Journal of Educational and Behavioural Statistics, 2021 - 2025

• Editorial board member of Applied Psychological Measurement, 2017 -
  
  

Honors

• 2024 Psychometrics Society Best Reviewer Award
  

• 2022 Psychometrics Society Early Career Award
  

• 2020 AERA Outstanding Reviewer Award
  

• 2018 NCME Brenda H. Loyd Outstanding Dissertation Award (Photo)
  

• 2018 National Academy of Education/Spencer Postdoctoral Fellow (link)
  
  

Funding

• LSE-NYU Seed Research Fund (2025-2026)

• IEA (International Association for the Evaluation of Educational Achievement) Research and Development Funds, 2022-2023

• National Academy of Education/Spencer Postdoctoral Fellowship, 2018-2020
  
  

Experience

• Intern at Educational Testing Service, supervised by Dr. Matthias von Davier, June to July 2014
  

• Visiting Scholar at Shanghai Center for Mathematical Sciences, May to July 2016
  

• Assistant Professor in Department of Psychology and Institute for Quantitative Theory and Methods, Emory University, August 2016 - August 2018