Research & software

I build tools for coordinating AI systems and examining whether their outputs are supported by evidence.

Research interests

Agentic systems

Model orchestration, structured tool use, persistent state, agent memory, and knowledge representation.

Verification & evaluation

Evidence quality, provenance, uncertainty, calibration, and reproducible experimental workflows.

Applied perception

Biometric measurement, computer vision, sensor fusion, and GNSS-denied autonomous navigation.

Selected public software

Six projects from my current CV and resume.

Agent collaboration

circle

Go

Shared memory and review workflows for research teams and AI assistants.

GitHub-native collaboration with a built-in knowledge graph and 22 MCP tools. Tracks artifacts, review gates, context packs, and distributed tasks using git as the shared substrate.

Biometric measurement

ofiqpy

Python

Face-image-quality measurement with a reference comparison workflow.

Python implementation of the fixed BSI OFIQ v1.1.0 profile: 27 quality components plus the unified quality score. Includes configuration and model integrity checks and a live C++ comparison workflow.

Knowledge integrity

okf-tools

Python

Validation that checks what a knowledge bundle means, as well as its format.

Tools to validate, lint, migrate, and index Open Knowledge Format bundles. Detects broken relationships and silent semantic failures that basic conformance checks do not reject.

Autonomous systems

lunar-terrain-sidecar

TypeScript / Godot

Lunar terrain authoring grounded in real south-polar terrain products.

Terrain generation, authoring, and preprocessing for Godot robotics simulation. Uses LOLA/PGDA terrain products, ephemeris-derived illumination, explicit provenance, automated validation, and CI.

Computer vision

swinvit-face-verification

Python / Jupyter

A common evaluation interface for SwinFace and ArcFace encoders.

Reproducible face verification over public benchmark data, with documented provisioning, integrity checks, metrics, limitations, and optional mixed-effects analysis.

Scientific data systems

medicaid-kg

Python / TypeScript

Knowledge-graph and geospatial exploration of Medicaid provider spending.

An exploration system for a 227-million-row HHS T-MSIS dataset. Combines DuckDB, NetworkX, FastAPI, React, MapLibre/deck.gl, and agent-assisted querying.

Design stage

OpenFIQA Studio

A scientific IDE for biometric quality, verification research, controlled degradation experiments, and publication-artifact generation. The public work currently comprises product architecture, scientific schemas, and decision records.

Read the architecture and design records

Research practice

I treat provenance, reproducible environments, evaluation protocols, and explicit limitations as part of the engineering work. The repositories above provide the implementation and documentation behind each project.