My research is focused on the development of computational methods to solve biologic problems. Currently, I am using machine learning methods (Random Forests, SVMs, Deep Neural Networks) to explore the epigenome.

I developed a machine learning model to predict chromatin state. Additionally, I developed a deep neural network to predict H3K27ac activity from whole genome bisulfite sequencing (WGBS). The predicted H3K27ac activity was used to identify putative Enhancer/Super-Enhancer regions across the human genome.

I worked in the Computational Chemical and Structural Biology Laboratory under the direction of Jens Meiler. Durning my graduate studies I developed methods to simulate small angle X-ray and neutron scattering (SAXS/SANS) profiles from rigid bodies in 3D Euclidean space. I then applied this method to filter in silico protein models during protein folding simulations using BCL::Fold.

•Six Sigma Green Belt: Over 100K reduction in Operating costs through Liquid Handling Robot Optimization•Mitochondrial DNA Sequencing/STR Genotyping•Analyze and troubleshoot problems through Electropherogram Data from ABI 3730 Genetic Analyzer•Program Biomek Fx Methods•Created Biomek Fx Calibration System to satisfy ISO accreditation requirements•Wrote Excel program with Visual Basic tool to analyze data from spectrophotometer•Certified Biomek Fx Methods and Technique programmer through Beckman Coulter•Wrote SOPs and Standard Worksheets for STR Laboratory processes

• Managed programming phases of the projects: timelines, programming budget requirements, project programming planning, programming survey instruments, data analysis, reports, and sending final data to client.• Programmed market research studies in CfMC and HTML on a linux platform using Survent, WebSurvent, and PhP. • Hired and trained programming staff, and solved major programming challenges.