Research Sketches
Workflow experiments, analysis techniques, and methodological notes: ways AI has proven useful, uneven, or surprisingly limited in actual scholarship.
How to read these
Treat each research sketch as a field note from an experiment. The point is not that a tool solved the problem, but what it made possible, what it got wrong, and what expertise was still needed around archives, metadata, data ethics, accessibility, privacy, method, or research computing.
Pipelines for Medieval Handwriting Recognition
ExperimentTo create an AI agent to work with Gemini and Claude to bulk process 300 images of archival documents and enable full-text search of medieval handwriting.
Results- built an agentic pipeline for bulk document processing
- combined multiple LLMs to improve transcription accuracy
- enabled full-text search of handwritten archival sources
Photos to Map Pins
ExperimentCreate an interactive map with pins for hundreds of photos, using GPS metadata already embedded in your phone's images — in under an hour.
Results- extracted GPS metadata from image files
- built a map visualization with AI-assisted coding
- presented geolocated data in a public-facing format
Generate 3D Prints from 2D Drawings
ExperimentAI can transform a historical line drawing into a 3D-printable file, adding a tactile dimension to research that images alone can't provide.
Results- generated 3D-printable files from 2D historical images
- reconstructed material culture objects for research
- incorporated tactile elements into research presentations