Welcome! I am a Postdoctoral Scholar at the Stanford University Graduate School of Education, where I work on the LEVANTE Project with Ben Domingue, Mike Frank, and Nilam Ram. I develop statistical methods that make educational and psychological measurement more reliable, valid, and fair — particularly as AI enters the assessment pipeline.
My research bridges methodological innovation with practical assessment design and large-scale data analysis. I specialize in:
- Statistical Psychometrics — multidimensional IRT (mIRT) and Many-Facet Rasch Models (MFRM)
- Bayesian Modeling — longitudinal and latent variable models, including Growth Mixture Modeling (GMM)
- AI-Integrated Measurement — evaluating ML-based scoring and the integration of LLMs into educational assessment
Recent Highlights
- Preprint (June 2026) — Good Kitty, Bad Bank? Rescoring Miscalibrated CATs Improves Accuracy (with Domingue, Ram, & Frank) · PsyArXiv
- Preprint (May 2026) — The Safety Valve: A Mixture IRT Approach to Modeling Guessing Behavior (with Ulitzsch, Zhang, Frank, & Domingue) · PsyArXiv · R package mixirt
- Preprint (2026) — A Parameterization-Invariant DIC (with Rabe-Hesketh) · arXiv:2605.27844
- Publication (2026) — What Do I Know about AI beyond Everyday Knowledge? in ACM Transactions on Computing Education
- Editorial Service — Editorial Board Member, Measurement: Interdisciplinary Research and Perspectives
Recent Posts
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