CV

Education

• MS, Applied Statistics for Social Science Research (Computational Track), New York University, 2026 (expected)
• MA, Applied Psychology, New York University, 2023

Work experience

• PRIISM Fellowship Psychometrics Research Assistant @ Department of Applied Statistics, Social Science, and Humanities, New York University (2024–current)
  • Supervisor: Klint Kanopka, Ph.D.
  • Conducted analysis and modeling including clustering and sequence analysis for the NAEP computer adaptive test process and response data.
  • Developed and implemented a scalable data analysis pipeline to assess the fit of polytomous item response models across large-scale item response datasets.
• Data Processing Researcher @ Computational Social Policy Lab (2024–current)
  • Supervisor: Alex Chohlas-Wood, Ph.D.
  • Applied an OpenAI large language model (LLM) to extract structured information from lawsuit documents with the goal of building an automatic pipeline to create a new databas.
  • Cleaned and standardized manually coded case data from CSV files in the past 10 years to support model evaluation and accuracy benchmarking.
• Data Management Specialist @ Data Services, New York University (2025–current)
  • Supervisor: Vicky Rampin, M.S.
  • Respond to inquiries to data and code management from students, faculty, and staff via consultations, email or chat.
  • Lead classes on data management and version control tools like Git and GitHub.

Teaching experience

• TA, Intermediate Quantitative Methods: The General Linear Model (Graduate Level), New York University (2023Fall, 2024Fall)
  • Instructor: Ravi Shroff, Ph.D.
  • Duties: Hold recitation sessions to go over course materials, hold office hours for homework questions, code debugging, and other course relevant questions, homework grading
• TA, Basic Statistics (Graduate Level), New York University (2025Spring)
  • Instructor: Jaime Kahhat, Ph.D.
  • Duties: Hold office hours for homework questions, code debugging, and other course relevant questions, homework grading

Conference Presentation

• Shen, R. Tracking Behavioral Patterns in a Computerized Math Assessment: A Latent Class Approach. (2025). 2025 NYU Society for Statistics Conference, New York, NY. Chapter of the American Statistical Association. Paper presentation.

Honors and Awards

• PRIISM Opportunity Fellowship ($10,400)
• NYU Applied Psychology Department Graduation Spotlight Student

Skills

• Data Processing/Programming: R(baseR,tidyverse), SQL(SQLight),Shell/Terminal
• Data Management Tools: Git/Github, OSF
• Statistical& Machine Learning Models: General linear regression, GLM, Multilevel models, IRT models (Dichotomous: 1-3PL, Polytomous: GRM, NRM, PCM, GPCM), K-means, PCA, Exploratory factor analysis(EFA), Latent class analysis, Hierarchical clustering