Hi, everyone! My name is He Ren (pronunciation /xɤ̂ ʐən˧˥/ or "huh zhen"), and very welcome to my personal homepage! I am a Ph.D. candidate in the Measurement & Statistics program at University of Washington.

I am committed to the development and improvement of quantitative educational measurement methods, with a particular focus on promoting fairness and addressing ethical challenges through interpretable and valid measurements. I am also passionate about bridging AI and psychometrics, using psychometric principles to guide the development of transparent, fair, and socially responsible AI, while also leveraging AI to advance methods and applications of psychometrics. My work seeks to connect statistics, computer science, and social science in ways that enrich all three disciplines.

My research interests focus on Machine Learning (ML), Computational Methods, Item Response Theory (IRT), Diagnostic Classification Modeling (DCM), Computerized adaptive testing (CAT), Natural Language Processing (NLP), and Large Language Models (LLMs).

I look forward to any potential collaborations. If you are also interested in the methodology or application of quantitative measurement methods, feel free to contact me. Let’s have some fun!

When I’m not working, you’ll likely find me exploring nature on a hiking trail, capturing the world through my camera lens, or enjoying the thrill of water activities—whether snorkeling, kayaking, or simply being near the ocean.