Aaron Zhong
Data Science & Biostatistics
University of Washington, Seattle
Aaron Zhong

About Me

I am currently a graduate student in Biostatistics at the University of Washington. I earned my B.S. in Computer Science from Duke University and Duke Kunshan University. My academic interests lie at the intersection of data science and public health, with a focus on applying statistical methods to real-world health problems.

I am currently serving as a teaching assistant for BIOST 310: Biostatistics for the Health Sciences, supervised by Prof. Robin Mejia, where I lead discussion sections and support students in understanding core statistical concepts.

Experiences

Current
Seattle, WA

Teaching Assistant — BIOST 310, University of Washington

  • Lead discussion sections for Biostatistics for the Health Sciences, supervised by Prof. Robin Mejia.
  • Support students in understanding core statistical concepts including hypothesis testing, regression, and data interpretation.

June 2025 – Aug 2025
Shenzhen, China

Data Scientist Intern — Haplox Biotechnology

  • Architected an end-to-end genomic pipeline via SQL/Python for early lung cancer diagnostics, multiprocessing 1K+ samples and 100K+ features, reducing preprocessing time by 40%.
  • Streamlined high-dimensional biological datasets from 100K+ down to ~300 prognostic features using variance thresholds and mutual information SelectKBest algorithms.
  • Deployed a Random Forest diagnostic model with rigorous cross-validation via scikit-learn, achieving AUC of 0.98 to identify top genomic predictors from fragmented sequence data.
  • Designed Tableau dashboards to monitor prediction distributions across healthy and cancerous cohorts, guiding iterative feature refinement.

Aug 2024 – Nov 2024
Shanghai, China

Data Analyst Intern — Lilly Asia Ventures

  • Evaluated early-stage investment viability for medical device portfolios via EDA on 50+ variables, assessing funding history and valuation trends to dictate capital allocation strategies.
  • Implemented logistic regression models using multi-dimensional company growth and market indicators to quantify product commercialization probability and mitigate financial risk.
  • Designed Tableau visualizations to track competitive market share and long-term financial projections, streamlining scenario analysis for executive-level due diligence.