Hi! I’m He Ren, pronounced like heron 🪶 (yes, like the bird). I’m a Ph.D. candidate in Measurement & Statistics at the University of Washington.

I build quantitative methods that make sense of messy social data, fairly, interpretably, and with impact. My work blends psychometrics, statistics, and computer science to better understand human behavior and emerging technologies. Lately, I’ve been working on bridging psychometrics and AI, that is, using psychometric principles to evaluate large language models, and using AI to improve measurement and assessment.

My research interests include machine learning, item response theory (IRT), diagnostic classification models (DCMs), computerized adaptive testing (CAT), natural language processing (NLP), and large language models (LLMs).

I’m always open to collaboration, whether you're into quantitative methodology or applied research. Feel free to reach out, and let’s build something interesting (and maybe even fun).

Beyond research, I love hiking, photography, and any excuse to be on or near water, snorkeling, kayaking, or just soaking in the ocean breeze.