Bioinformatics / Scientific Computing
I build research computing systems for genomic data, reproducible modeling, and practical AI in scientific environments.
Researcher at The University of Arizona in the Bernardo Lemos Lab, where I focus on HPC pipeline development, methylation-focused modeling workflows, and scientific data systems that can support downstream analysis and machine learning.
Where I’m focused now
Research Computing
RRBS/WGBS HPC Genomic ETL Pipelines
End-to-end genomic processing workflows on HPC infrastructure, built for scale, reproducibility, and downstream-ready biological analysis.
- Python, Bash, SLURM
- Parallelized HPC execution
- Thousands of samples processed
Research ML Engineering
DNA Methylation Age Clock Modeling
A more configurable and reproducible engineering layer around methylation-based age prediction workflows for repeatable experimentation.
- Elastic-net modeling
- Cross-validation workflows
- Structured outputs and logging
Applied AI for Research
Self-Hosted Bioinformatics AI / Internal RAG System
A local retrieval-oriented assistant built for curated scientific content, internal research use, and controlled lab-facing querying.
- Sentence-transformers + FAISS
- Document ingestion and chunking
- Streamlit interface
Explore
Semantic Project Explorer
Click a concept card to see how the featured work on this site maps to it. This is a lightweight retrieval-style layer over the projects and themes I am building around right now.
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Links
Direct access
Current role
Data Analyst / Computing Sciences Researcher
Dr. Bernardo Lemos Lab, Pharmacology & Toxicology
Degrees
Master of Science in Data Science
The University of Arizona, 2025
Bachelor of Science in Business Administration
The University of Arizona, 2016