Neal A. Doran, Ph.D.
Scientific Data Engineer & Professor of Biology
I build deployed AI/ML systems and production-ready data pipelines optimized for massive scientific databases. I bridge the gap between highly complex natural science datasets and robust computational engineering.
Publications & Projects
My upcoming book on dinosaur morphospatial patterns and contingent emergence is currently in the typesetting phase with Cambridge Scholars Publishing (expected 2026).
Spatial Biodiversity Gap Audit Platform
An automated ETL pipeline and live analytical dashboard cross-auditing global IUCN Red List conservation data against a 26-million-record GBIF spatial occurrence dataset.
- Stack: Python, SQLite, Streamlit, Plotly, Pandas
Semantic Socratic Tutor
A retrieval-augmented generation (RAG) system grounded in a specialized historical and philosophical scientific corpus. The system enforces strict Socratic pedagogical constraints, utilizing vector search to anchor LLM responses entirely to verified source texts.
- Stack: Python, Anthropic Claude API, ChromaDB, Sentence-Transformers, NumPy, Streamlit
Technical Capabilities
- Data Engineering & Infrastructure: High-throughput ETL pipelines, database normalization, large-scale dataset ingestion (SQL, SQLite). Currently migrating core datasets to spatial SQL environments utilizing PostGIS and GeoPandas.
- AI & Natural Language Processing: RAG architecture, vector embeddings, semantic search optimization, LLM API integration.
- Domain Expertise: Two decades of hands-on experience with deep-time geological, paleontological, and spatial biodiversity data.
Contact & Writing
Alongside my computational work, I maintain a platform exploring the intersection of the historical sciences, philosophy, and faith. You can find my broader writing at Faith and Reason-25.