Projects & Research Highlights

Structural Racism and Cervical Cancer Outcomes

Llanos Lab, Columbia University | 2025 – Present

This project examines structural racism and disparities in cervical cancer incidence, survival, and screening through a large-scale systematic review.

Key Contributions

  • Conducting comprehensive systematic review of structural racism and cervical cancer outcomes.
  • Leading data extraction in Covidence across >100 peer-reviewed studies.
  • Mapping exposure–outcome pathways involving healthcare access, socioeconomic status, and neighborhood-level inequities.
  • Synthesizing findings for manuscript submission and national presentation.
  • Collaborating on NIH-funded research integrating epidemiologic frameworks and equity metrics.

📄 View Research Poster

Stanford Medicine — Center for Asian Health Research and Education (CARE)

Research Scholar | 2023 – 2025

Quantitative research focused on health disparities in disaggregated Asian-American populations.

Key Contributions

  • Led statistical analyses using NHIS to examine relationships between sleep duration, depressive symptoms, and mortality risk.
  • Built and visualized multivariable regression models to highlight intra-Asian heterogeneity.
  • Conducted subgroup analyses using SEER to assess glioma grading and mortality across East, South, and Southeast Asian populations.
  • Contributed to modeling and interpretation included in a published abstract in Neurology (2024).

📄 View Published Abstract

Sports Betting in the United States: Data Analysis and Predictive Modeling

P8105 Data Science 1 | Final Project

End-to-end data analysis project examining state-level sports betting adoption, revenue generation, and policy environments.

Key Contributions

  • Collected, cleaned, and integrated United States Census data used throughout the analysis.
  • Built and evaluated predictive models, including least absolute shrinkage and selection operator regression.
  • Generated prediction and model performance figures used across the public-facing website.
  • Contributed to interpretation and communication of results.

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Dynamic Games and Predator–Prey Systems Using Markov Decision Processes

MATH-UN2015: Linear Algebra and Probability | Final Project (Fall 2025)

Modeled predator–prey interactions as stochastic dynamic games using Markov Decision Processes, transition matrices, and linear algebraic value iteration.

Key Contributions

  • Formulated predator–prey dynamics as finite-state Markov processes with absorbing states.
  • Encoded transitions and rewards using matrix and vector representations.
  • Solved Bellman equations via matrix inversion to compute long-run value functions.
  • Extended the model to a two-player stochastic game and analyzed Markov Perfect Equilibria.
  • Co-developed state-space design and dynamic game structure.

📄 View Final Paper