Current Research

My current primary research goal, at the University of Florida, is to develop and/or improve the accuracy of spatial public health databases in semi-developing and/or developed countries, through the integration of other large heterogeneous datasets. This will be done by creating health modeling programs and subroutines that will collect, compile and integrate useful health data to

  1. Determine and predict spread and distribution of vector-borne infectious diseases.
  2. Allow easier access to more accurate and realistic ecological data. I have 7+ years of experience of using GIS (Geographic Information Systems) and programming abilities (R, VB, C++, and Python) to develop my future research work.

Additionally, I’ve focused on developing tailored ‘Big data’ approaches that can facilitate the analysis of multi-dimensional heterogenous data such as metagenomic, expression and phylogenetic data combined with clinical metadata to explore system biology approaches investigating various comorbidities associated with zoonoses. While the emphasis of my research is on developing approaches to better mine the enormous amounts of heterogeneous data generated in large population-based studies, my secondary goal is to show the utility of the methods on a problem with significant public health relevance. I have considerable experience in bioinformatics, primarily the processing of RNA sequencing and methylation data, equipping me with an ability to parse large heterogeneous datasets. I currently work on implementing One-Health data-driven solutions on surveillance databases including incorporating spatial resolution within disease surveillance programs in Central Asia and with the United States Army’s Veterinary Service.