people

Ruiting Shen is a master’s student in the A3SR program at NYU. Her research interests, in general, focus on applying statistical and machine learning models to psychological and educational latent variable modeling. This includes, but is not limited to, incorporating behavioral data—such as test process and user clickstream data—into traditional IRT models to improve the accuracy of ability and item parameter estimations and interpretations; statistical applications of large language models (LLMs); and model evaluation tool development. In practice, she also enjoys learning programming languages and working on data processing, management, and statistical consulting. Outside of research, she loves trying good food and coffee, swimming, researching fashion trends, and playing chess.

Ruiting will be applying to Ph.D. programs for Fall 2026 admission!

Jillian Pizza is a Master’s student in the A3SR program at NYU. Her research interests include applying statistical techniques to measure political ideology and effective political messaging, with a focus on U.S. Politics. Outside of research, Jillian loves live music, painting, reading, and spending time with her friends and cat, Olive!

Sophia Deng completed her Master’s degree in Applied Statistics for Social Research A3SR in Spring 2025. Her research spans venture capital networks in the education sector and the modeling of item selection algorithms for computer adaptive testing (CAT). She is also an active contributor to meow, a package for conducting simulations to compare CAT algorithms. Sophia is broadly interested in the intersection of statistical learning, network analysis, and optimization, with a particular focus on the governance and deployment of emerging technologies. Her work engages questions of algorithmic design, network analysis, and data privacy–especially as they relate to decision-making systems in both institutional and digital environments.

Yuan Huang graduated from A3SR in Spring 2025. She has worked on LLM Responses to Social Surveys and is currently a Data Manager at NYU School of Global Public Health, where she designs HIPAA-compliant data architectures for clinical research. Her research interests center on causal inference methodology, the intersection of large language models and causality, missing data techniques, and longitudinal data analysis. Yuan has extensive experience in AI-driven systems development, having led the deployment of investigation planning tools and automated fraud detection systems during her internship at the United Nations Development Programme. She is particularly interested in developing novel statistical frameworks that enhance the reliability of causal treatment effect estimates and exploring how LLMs can be leveraged for robust data augmentation in measurement contexts. Outside of research, Yuan enjoys running, swimming, and hiking.

Yining Lu recently completed her master’s degree in Applied Statistics for Social Science Research (A3SR) at NYU, where she focused on using large language models (LLMs) to analyze responses to social surveys. Beginning in Fall 2025, she will pursue a Ph.D. in Organizational Leadership and Information Analytics at the University of Colorado Boulder. Her research interests lie at the intersection of information systems, measurement theory, and behavioral analytics. She is particularly interested in developing and validating measurement models within nomological networks and applying computational methods to uncover latent constructs—such as trust, engagement, and decision-making—in digital contexts. Outside of research, Yining enjoys playing video games, hiking, listening to music, and baking.

Victoria Zhang graduated from A3SR in Spring 2025. She worked on MCMC Based Short Form Creation. Victoria was also a course assistant for both Statistical Computing and Modern Approaches in Measurement. Her research interests focus on using quantitative methods to explore identity, education, and institutional decision-making. She is particularly interested in applying survey and measurement methods to inform more inclusive, data-driven practices in education and social policy, with an emphasis on the experiences of immigrants and LGBTQI+ individuals. Outside of research, Victoria enjoys cooking, exploring new cuisines, attending concerts and shows, and learning new languages.