Experience
February 23’ to present
Senior Design Engineer I, Ginkgo Bioworks - Systems Biology Group
Within our team, I have been primarily responsible for machine learning pipeline construction, integrating and analyzing large-scale multi-omic data types with the goal of novel target discovery or microbial strain optimization. This required collaboration & coordination with scientists across numerous data collection & computational resourcing. More recently have been focusing on onboarding & innovating on existing deep learning (AI) frameworks. These efforts led to contributions in >10 projects in the last year, many with direct client presentations for large groups like Bayer & Sanofi.
June 22’ to February 23’
Bioinformatics Scientist II, Zymergen - Natural Products & Drug Discovery Group
My role was centered on pipeline development & analysis of large-scale microbial datasets across diverse synthetic biology projects ranging from drug discovery & materials science. This work required integration of numerous bioinformatic and statistical modeling into massively high-throughput reproducible workflows along with automated report generation.
August 17’ to June 22’
Postdoctoral Research Associate, Biomedical Engineering - University of Virginia, Papin Lab
In my last academic position I designed novel platforms for computational network modeling of bacterial metabolism to engineer bacterial species consortia for targeted bacteriotherapy against C. difficile infection to subsequently test in an animal model.
April 12’ to July 17’
PhD Candidate, Microbiology & Immunology - University of Michigan, Schloss Lab
My dissertation research combined metagenomics, metatranscriptomics, & untargeted metabolomic with statistical analyses to understand shifts in composition or function of the gut microbiome in response to infection. Achieved an additional certificate in Cellular Biotechnology with an internship at Janssen Pharmaceuticals.
June 12’ to August 12’
R&D Internship, Immunological Research Departmen - Janssen Pharmaceuticals
Used classical machine learning algorithms to predict Crohn’s disease patient response to drug therapy combining both microbiome and host epithelial microarray data.
Education
July 11’ to July 17’
Doctorate, Microbiology & Immunology - University of Michigan, Ann Arbor MI
My dissertation research combined metagenomics, metatranscriptomics, & untargeted metabolomic with statistical analyses to understand shifts in composition or function of the gut microbiome in response to infection. Achieved an additional certificate in Cellular Biotechnology with an internship at Janssen Pharmaceuticals.
August 07’ to May 11’
Bachelor of Arts (BA), Biology - Hiram College, Hiram OH
Graduated Cum Laude with an additional minor in Chemistry
Skills
Data Science & Programming
- Implementation of Deep Learning, AI, & Large Language Models plus related architecture; PyTorch, TensorFlow+Keras, and recent LLM frameworks including Hyena & Mamba
- Extensive work in classical machine learning & statistics; XGBoost, Random Forest, Multivariate Regression, & Unsupervised/Supervised Clustering
- Mastery in multiple languages: Python, R, Groovy, Bash, & SQL
- High-performance computing & parallelization: Nextflow Tower, Argo, GCP, AWS, Slurm, & Torque
- Containerization, version control, & POC testing: Docker, Git, & Jupyter
Computational Biology
- Integrative multi-omic analyses for metagenomics, metatranscriptomics, & mass spectrometry
- Metabolic network analysis & context-specific simulations of metabolism
- High-throughput assembly & annotation of microbial genomes from microbiome deep sequencing
- Between species interaction predictive modeling in the context of inflammation & infection
- Biosynthetic gene cluster discovery in large metagenomic datasets
Experimental Design & Execution
- Animal care & handling in models of cancer, infectious disease, & dietary intervention
- Anaerobic / Aerobic microbiology, mammalian cell culture, & fermentation modeling
- Clinical patient sample collection