• MD, Duke University School of Medicine, 2020
  • PhD, Duke University, Computational Biology and Bioinformatics, 2019
  • BS, Johns Hopkins University, 2011, Physics and Biophysics

Current Employment

Areas of Focus

If it involves cool math and is impactful, I am interested. Lately my research has focused on uncertainty quantification in the setting of partial identifiability with a particular application to the analysis of multivariate sequence count data (e.g., Microbiome and Gene Expression studies). I also have particular interest in multivariate time-series analysis which I have applied to a wide variety of problems in finance, epidemiology, and personalized medicine.


  • Analysis of Bio-molecular Assays
    • Microbiome Amplicon and Shotgun Sequencing
    • Bulk and Single-Cell RNA-Seq
    • Phosphoproteomics
  • Inference and Prediction from Financial Time-Series and Alternative Data
  • Personalized Medicine
    • Medical Decision Making Under Uncertainty
    • Personalized Risk Prediction
  • Non-Specific Surveillance in Epidemiology
    • Waste-Water Based Viral Surveillance for COVID-19
    • Use of Syndromic Markers for Assessing Disease Burden
  • Agriculture
    • Microbial determinants of feed conversion and disease prevention in livestock


  • Partial Identified Models
  • Bayesian Statistics
  • Bayesian Decision Theory
  • Compositional Data
  • Multivariate Analysis
  • Uncertainty Quantification in Time-Series Analysis

More Details

More detail on my research interests can be obtained from the Silverman lab’s website and from the list of my recent publications.


In my free time I enjoy exploring the outdoors (backpacking, canoing, rock climbing), creating puzzles, and farming.