I am a Ph.D. student in the Human–Computer Interaction Institute (HCII) within the School of Computer Science at Carnegie Mellon University. I am fortunate to be advised by Ken Holstein and Steven Wu.
I develop tools for measuring the capabilities, risks, and limitations of AI systems. I study statistical approaches for evaluating AI systems themselves, as well as frameworks for understanding the broader sociotechnical context in which humans operate and interact with AI systems. My work bridges ideas from ML, Statistics, Human–Computer Interaction, and the Quantitative Social Sciences to advance an emerging interdisciplinary science of AI evaluation.
My work is generously supported by an NSF Graduate Research Fellowship, the Center for Advancing Safety of Machine Intelligence, and the National Institute for Standards and Technology (NIST).
Selected Work
(*) Co-first Author; (**) Co-senior Author- Doubly-Robust LLM-as-a-Judge: Externally Valid Estimation with Imperfect Personas Under Review, 2025 [arXiv]
- Measurement as Bricolage: How Data Scientists Construct Target Variables for Predictive Modeling Tasks Conference on Computer-Supported Cooperative Work and Social Computing (CSCW), 2025 [arXiv]
- Counterfactual Prediction Under Outcome Measurement Error Conference on Fairness, Accountability, and Transparency (FAccT), 2023 [PDF] [Video] [Code] Best Paper Award