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