Brandon Davidson

Founding Engineer @ iya | Software, AI & Data Engineering

Atlanta, Georgia

Computer Science undergraduate at Georgia Tech building full-stack agronomy systems, machine learning pipelines, and agent-ready developer tools.

Projects

  • Brandon Brain- Rust, SQLite, Tokio, Clap, Obsidian, Docling

    Apr 2026

    Built an Obsidian-first knowledge compiler with CLI workflows for workspace initialization, health checks, ingest queues, and OCR bootstrap.

    • Implemented SQLite state, file walking, hashing, config persistence, and Markdown/PDF ingestion for agent-ready artifacts.
    • Packaged install and doctor commands to validate local runtimes, workspace paths, and OCR dependencies.
  • Biomechanical Stress Analysis- Python, OpenCV, YOLOv8, scikit-learn, PyTorch

    Dec 2025

    Built an end-to-end computer vision system to predict biomechanical injury risk from short exercise videos.

    • Extracted pose keypoints with YOLOv8 and engineered joint-angle, velocity, and movement-stability features.
    • Trained Random Forest and neural network models to predict continuous stress scores with 84% accuracy.

Experience

  • Founding Engineer- iya

    Apr 2026 - Present / Atlanta, GA

    Building a full-stack agronomy platform for field records, weather, soil, satellite, and crop-stage decision support.

    • Developed a Python PCSE/WOFOST agronomy engine with Gymnasium RL training, baselines, and trace export.
    • Implemented offline-first pipelines for NASA POWER weather, soil caches, Sentinel metadata, and vegetation features.
    • Shipped React/Vite product surfaces and discovery workflows for scouting, alerts, records, and agronomic explanations.
    • Built tests and playback tooling to compare learned policies against heuristic agronomy baselines.
  • Software Engineer (AI & Machine Learning)- GROWER Lab

    Aug 2024 - Dec 2025 / Atlanta, GA

    Built a React.js geospatial dashboard for real-time outage analysis across 50+ U.S. states.

    • Developed Python data pipelines ingesting records from 1,000+ utilities for national resilience monitoring.
    • Designed and evaluated machine learning forecasting models, reaching 85% accuracy on historical outage data.
    • Analyzed millions of outage records with pandas, matplotlib, and Seaborn for DOE-facing reports.
  • Data Engineering Intern (Technology Consulting)- Protiviti

    May 2025 - Jul 2025 / Atlanta, GA

    Automated Azure ETL pipelines processing 10K+ daily rows for production business intelligence systems.

    • Migrated 10 complex SQL stored procedures to Microsoft Fabric, reducing reporting runtime by 40%.
    • Designed 5 production SQL views integrating tariff metrics into SAP-backed reporting workflows.
    • Presented bi-weekly technical updates to align data models with client reporting requirements.