Geoscientist & Scientific Data Engineer
I build deployed AI/ML systems and production-ready data pipelines optimized for massive scientific and biodiversity databases. Backed by a PhD in geological sciences (micropaleontology) and two decades of hands-on domain experience with deep-time geological, paleontological, and spatial data, I bridge the gap between highly complex natural-science datasets and robust computational engineering.
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Global Geology PostGIS Analysis — A PostgreSQL/PostGIS spatial database integrating USGS World Geology and State Geologic Map Compilation datasets (148.3M km² of mapped geology), using spatial SQL to compute continental-scale geologic surface analysis. 👉 View Project
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Spatial Biodiversity Gap Audit Platform — An automated extract, transform, load (ETL) pipeline and live analytical dashboard cross-auditing global IUCN Red List conservation data against a 26-million-record GBIF occurrence dataset using Python and SQLite. 👉 Launch Deployed App
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Semantic Socratic Tutor — A retrieval-augmented generation (RAG) system grounded in a specialized historical and philosophical scientific corpus. Built with Python, utilizing all-MiniLM-L6-v2 sentence-transformer embeddings, NumPy cosine-similarity retrieval, and an integrated Anthropic Claude API pipeline. 👉 Launch Deployed App
- Languages & Databases: Python, SQL, PostgreSQL, PostGIS, SQLite
- Geospatial Engineering: Spatial SQL, PostGIS, GeoPandas, spatial indexing, equal-area projection, continental-scale spatial queries
- Data Engineering: High-throughput ETL pipelines, database normalization, structural data migration, large-scale dataset ingestion
- AI/ML & Natural Language Processing: Retrieval-Augmented Generation (RAG), vector embeddings, semantic search, LLM API integration (Anthropic Claude)
- Deployment & UI: Streamlit, Streamlit Cloud, interactive dashboard architecture
Professor of Biology, Bryan College · PhD Geoscientist building the tools that turn complex scientific data into rigorous, queryable systems.