Moran Guo 郭沫然

Biostatistician I at Quantive Intelligence

I turn clinical and biomedical data into reproducible analyses and clear results. At Quantive Intelligence (formerly LLX Solutions), I support statistical analysis, SAS programming, and quality control for clinical studies.

Download CV (PDF) Email me GitHub

Core skills: SAS (Base Certified), R, Python, SQL · CDISC SDTM/ADaM · Tables, listings, and figures · Simulation and power analysis

Contact: guomoran203@gmail.com

Moran Guo

PlanMCI

Study design under budget constraints

ANCOVA-based power and minimum detectable effect calculations for mild cognitive impairment trials.

Explore project contributions and tools

Selected publications

  1. Efficient Inference for Noisy LLM-as-a-Judge Evaluation
    Yiqun T Chen, Sizhu Lu, Sijia Li, Moran Guo, and Shengyi Li
    In International Conference on Machine Learning (ICML), 2026
    Accepted at ICML 2026
    arXiv Code Documentation Poster
  2. Power Analysis for Prediction-Powered Inference
    Yiqun T. Chen, Moran Guo, and Shengyi Li
    2026
    Preprint; manuscript under review
    arXiv Code Documentation

News

Mar 23, 2026 Preprint out!
Jan 30, 2026 Preprint out!

Background

I completed my ScM in Biostatistics at Johns Hopkins Bloomberg School of Public Health in May 2026. I hold a B.S. in Biological Sciences: Computational Biology from the University of Rochester, graduating Magna Cum Laude with Honors in Research and minors in Mathematics and Japanese.

My graduate work with Yiqun T. Chen focused on prediction-powered inference, Monte Carlo simulation, and power and sample size planning. I also contributed statistical analysis and data quality control to a neuroimmunology study using paired cerebrospinal fluid and serum samples at Johns Hopkins School of Medicine.

View experience and education

Outside of work, I enjoy rock climbing, fitness, Japanese pop culture, electronic music, and watching tennis.