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