I'm a Computational Biomathematician and Data Scientist. I have a passion for Mathematics and Genomics research. So, I use Machine Learning and Visual Analytics to help along the way.
Originally from Lenoir, North Carolina, I studied Applied Mathematics, Data Science, and Computational Biology at the University of North Carolina at Charlotte.
I currently work as a researcher in the Department of Bioinformatics an Genomics at UNCC as well as a Data Scientist for BlueGranite, a Microsoft partner consulting firm focused on delivering Data and AI solutions. I am currently located in Charlotte, North Carolina.
I have a wide range of interests when it comes to research. I often work on the computational side of things in order to enhance some other field of study such as genomics, mathematics, or even linguistics and beyond.
Using phylogenetic analysis, dimensionality reduction, and machine learning, a combined migratory model of the Bantu migration was formed with heterogeneous data.
Parallel Implementations of the Empirical Bayesian Elastic Net Cross-Validation in R.
Using unsupervised learning for dimensionality reduction and visualization.
Analysis and visualzation of the WHO reports of MERS infections versus genomic data.
Using R Shiny to create an analysis tool for pre-clinical trial data of a drug candidate.
Using Python Django to create a SNP analysis tool for TCGA cancer datasets.
Neural Network prediction of the effects of genetic mutations on mucopolysaccharidosis IIIB.
Sample data warehouse architecture for housing diverse medical data.
D3.js visualizations of UFO sighting data.
D3.js visualization of genetic sequence data of primates.
Using text analytics of a corpus of car reviews, we created a thorough recommendation for the next design of the Toyota Camry.
Using machine learning, we predicted the best time for each QVC product to be aired.
Novel method for the imputation of missing data. Used for the quantification of revenue loss due to out of stock product.
Using outlier prediction and changepoint analysis, predict when a customer's utility usage is out of the norm.
An overview of the first generation Azure Machine Learning online prediciton tool.
Using machine learning (demand forecasting), better predict the number of items to manufacture to keep your retailers' shelves full without over-producing.
Listed below are some of my interests and relevant skills. I definitely have dabbled in many things.
I'm always looking to learn and grow this list.