Biorepository Development
Development of Biorepository FFPE and Plasma Database and UI based on clinically relevant Oncomine variants
Current Work Projects
H&E Deep Image Classification
Inception V3 & ViT Model Training, Validation, and Testing for Deep Learning Classification of genetic variant predictions in H&E Images
AI Variant Calling Classification
Supervised and Neural Network Machine Learning Model development to classify SNV/INDEL Ion Torrent variations
BNFX App UI Development
Develop R&D Bioinformatics App UI to assist colleagues in analyzing data, connecting internal databases, and running approved 3rd-party software
Work Experience
Professional/Educational journey and key accomplishments
BS in Biology
Virginia Tech, Blacksburg, VA
2008
Attended Virginia Tech, Blacksburg, VA.
Research Publication
Journal of Computational Biology
March 2011
Published "Novel Machine Learning Approaches for FFPE Sample Analysis" detailing new computational methods for working with challenging sample types.
LIMS Business Analyst
Department of General Services, Richmond, VA
2012 - 2015
Tested LIMS software under Software Development Life Cycle (SDLC) practices at DCLS (Division of Consolidated Lab Services), as well as facilitated communication between users and developers of ideas in the development and training of LIMS software.
MS in Bioinformatics
Virginia Commonwealth University, Richmond, VA
2014 - 2016
Specialized in genomic data analysis and machine learning applications in healthcare. Thesis focused on novel algorithms for variant calling in cancer genomics.
Bioinformatics Scientist I
BASF, Raleigh, NC
2016 - 2019
Developed and validated custom data analysis pipelines and algorithms to analyze complex, poorly annotated, plant ge-nomes within a regulatory environment. Integrated multiple NGS platforms (Illumina and PacBio) to construct hybrid genome and transcriptome assemblies, enabling downstream variant discovery and gene expression analysis.
Bioinformatics Engineer
Eli Lilly and Company, San Diego, CA
2019 - 2020
Applied bioinformatics methods, antibody research, and statistical analysis to meet project objectives and deadlines. Developed in-house UI tools to streamline data processing and deliver clear, comprehensive data visualizations for molecular biology colleagues.
Sr. Scientist to Staff Scientist, Bioinformatics
Thermo Fisher Scientific: Carlsbad, CA
2020 - 2023 (Sr. Scientist)
2023 - Current (Staff Scientist)
Contribute to advancing oncology diagnostics and precision medicine through the development of automated pipelines and data science UI applications. Focus on integrating emerging NGS technologies and gene-targeted panels to support scalable analysis and interactive visualization for both internal and external stakeholders.
H&E Image Classification Project
Internal R&D Initiative
2023 - 2024
Spearheaded development of deep learning models for histopathology image analysis, achieving 92% accuracy in predicting genetic variants from H&E slides.
Journal Publication
The Journal of Molecular Diagnostics
Jan 2026
Analytical and Clinical Validation of the IVD-Compliant Oncomine Dx Express Test for Genomic Profiling of FFPE Tumor Samples
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Education
Work Experience
Publications
Major Projects
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Technical Skills
Programming Languages
Python
10 years
R
7 years
C++
3 years
Javascript
6 years
Bioinformatics Tools
Next-Gen Sequencing
8 years
GATK
6 years
Variant Calling
7 years
Machine Learning & Data Science
Scikit-learn
4 years
TensorFlow/Pytorch
3 years
NVIDIA CUDA & GPU Computing
3 years
CNN & Transformer Vision
3 years
DevOps & Workflow Tools
Git/GitHub
10 years
Docker
6 years
Nextflow
3 years
Full-Stack Development
React
6 years
Node.js
6 years
FastAPI
4 years
Django
3 years