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PhantomOSG-25/README.md

Hi, I'm Michael B. Wood

I am completing a B.S. in Computer Science with a concentration in Software Engineering and preparing to move from hands-on field operations into technology. I am especially interested in application support, software quality assurance, systems analysis, and select junior development roles.

My background in field service, construction, logistics, equipment operation, customer service, and business ownership gives me a practical approach to software: understand the real problem, communicate clearly, document the work, and verify the result.

Featured Projects

Project What it demonstrates Technologies
Raspberry Pi Thermostat System Embedded software, state-machine design, hardware integration, and data persistence Python, Linux, SQLite, Raspberry Pi
Deep Q-Learning Treasure Maze Reinforcement learning, neural networks, experience replay, and model evaluation Python, TensorFlow, Keras
Animal Rescue CRUD Module Reusable data access, database operations, and client-server design Python, MongoDB, PyMongo
Java Service Validation and Testing Requirements-based validation, unit-test design, and boundary testing Java, JUnit

Technical Foundation

  • Programming and data: Python, Java, SQL, MySQL, MongoDB, SQLite, and foundational JavaScript
  • Systems and tools: Linux, Bash, Git, GitHub, Raspberry Pi, REST APIs, and client-server concepts
  • Quality and analysis: Unit testing, validation, debugging, root-cause analysis, requirements, Agile, Scrum, and technical documentation

Current Direction

  • Completing bachelor's coursework in August 2026
  • Planning to begin an M.S. in Artificial Intelligence in September 2026, subject to final enrollment plans
  • Seeking remote, hybrid, or on-site opportunities where troubleshooting, reliability, testing, communication, and continuous learning matter

Connect

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  1. raspberry-pi-thermostat raspberry-pi-thermostat Public

    Raspberry Pi thermostat controller with state-machine logic, GPIO hardware integration, serial communication, and SQLite logging.

    Python

  2. deep-q-learning-treasure-maze deep-q-learning-treasure-maze Public

    Deep Q-learning agent that learns to navigate an 8x8 treasure maze using experience replay, target networks, and automated tests.

    HTML

  3. animal-rescue-dashboard animal-rescue-dashboard Public

    Python and MongoDB animal-rescue dashboard with a reusable CRUD layer, secure configuration, filtering logic, and automated tests.

    Python

  4. java-service-validation java-service-validation Public

    Java 17 contact, task, and appointment services demonstrating input validation, boundary testing, and JUnit 5 automation.

    Java