Website: https://lingbo-t.github.io
Lingbo Tong is an assistant professor in the Quantitative Methods area within the Department of Educational Psychology. Her research brings together psychometrics, natural language processing, and artificial intelligence, with a particular interest in improving how complex data such as text are integrated into psychological and educational measurement. She also studies how psychometric principles such as validity, reliability, and fairness can help us better understand, evaluate, and advance AI systems. Lingbo enjoys interdisciplinary collaboration and works with researchers across education, health and wellbeing, and digital culture.
Education
- Ph.D. Quantitative Psychology and Computer Science and Engineering, University of Notre Dame, 2025
- M.S. Computer Science and Engineering, University of Notre Dame, 2024
- B.Eng. Computer Science and Technology, Sichuan University, 2020
Selected Publications
- Gao, Z., Tong, L., & Zhang, Z. (2026). Detecting and Evaluating Bias in Large Language Models: Concepts, Methods, and Challenges. Journal of Behavioral Data Science, 6(1), 68–135.
- Tong, L., & Zhang, Z. (2026). Neural Network Analysis of Psychological Data: A Step-by-Step Guide. Multivariate Behavioral Research, 61(2), 399–419.
- Wan*, R., Tong*, L., Knearem, T., Li, T. J. J., Huang, T. H. K., & Wu, Q. (2025). Hashtag Re-Appropriation for Audience Control on Recommendation-Driven Social Media Xiaohongshu (rednote). In Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems (pp. 1–25).
- Tong, L., Qu, W., & Zhang, Z. (2025). Comparison of the K1 Rule, Parallel Analysis, and the Bass-Ackward Method on Identifying the Number of Factors in Factor Analysis. Fudan Journal of the Humanities and Social Sciences, 18(1), 17–44.
- Lu, Y., Tong, L., & Cheng, Y. (2024). Advanced Knowledge Tracing: Incorporating Process Data and Curricula Information via an Attention-Based Framework for Accuracy and Interpretability. Journal of Educational Data Mining, 16(2), 58–84.