Lillian Dillard

About Lillian Dillard

I am a Computational Systems Biologist currently leading microbiome-focused modeling efforts at the Gates Foundation. My work integrates agent-based simulation, multi-omic data analysis, and epidemiological modeling to optimize intervention strategies and forecast outcomes related to HIV risk, preterm birth, and maternal-infant health. I bring strong expertise in data analytics, machine learning, and in silico modeling, with a proven track record of translating complex biological data into actionable insights for strategic decision-making.

Experience

1. Research Scientist

   Gates Foundation

   Feb 2024 — Present

   Developing a dynamic agent-based model to simulate vaginal microbiome (VMB) dynamics, optimizing treatment strategies, dosing protocols, and intervention timing to enhance efficacy. Leveraging this model to predict intervention outcomes, quantifying their impact on HIV risk and preterm birth prevalence, and forecasting intervention efficacy and efficiency within demographically relevant populations. Collaborating with strategy teams and academic researchers to inform funding portfolios and drive innovation in women’s health.Integrating gut microbiome and enteropathogen data from multi-country maternal cohorts to model how microbial exposures influence preterm birth, fetal growth, and early infant outcomes—supporting evidence synthesis and intervention prioritization.

Education

• The University of North Carolina at Chapel Hill

  Bachelor of Science - BS, Biology, General

• University of Virginia

  Doctor of Philosophy - PhD, Biochemistry and Molecular Genetics

• University of Virginia

  Master of Science - MS, Biological and Physical Sciences

• The University of North Carolina at Chapel Hill

  Bachelor of Science - BS, Psychology