Projects
Most code is available on GitHub. Use the filter and sort controls to browse — or follow the Case Study link on any card for a full write-up.
A production PyQt6 desktop application for processing, visualizing, and analyzing 100+ GB multi-channel electrophysiological datasets — reducing lab analysis time by ~80%.
- Custom filtering, peak detection & baseline correction algorithms
- Statistical analysis suite with automated report generation
- Reduced analysis time by ~80% vs. prior manual workflows
A normalized SQLite database built on PubMed open data, with a Python ETL pipeline and five analytical SQL queries mapping publication trends in spinal neuroscience.
- 6-table normalized SQLite schema from 200k+ PubMed records
- 5 SQL analyses: window functions, self-joins, recursive CTEs
- Python ETL pipeline: Entrez API ingestion + NIH iCite enrichment
A companion PyQt6 application for automated, reproducible generation of publication-quality EMG trace figures — turning a half-day manual task into a 10-minute batch job.
- Configurable styling templates; export to PNG, SVG, and PDF
- Flexible, modular YAML configuration system
- Clean separation of data processing and rendering logic
Adapting and publishing a MATLAB spatial interpolation toolkit as the open-source, reproducible analysis pipeline for a peer-reviewed eLife study on spinal interneuron distributions.
- Spatial interpolation algorithms for cell-population density mapping
- Automated figure generation from raw anatomical cell-count data
- Featured as reproducible analysis pipeline in eLife (2024)
Interests & Future Directions
I’m actively building toward data science and ML applications in neuroscience, healthcare, and business. Areas I’m excited about: