Software engineer

David Courtney

Experienced software engineer building applications, automation, and integrated systems, with a growing focus on AI and machine-learning engineering.

About

Engineering software and intelligent systems for complex workflows

My background spans application development, automation, systems integration, Linux and Windows environments, virtualization, networking, data migration, workflow orchestration, and technical troubleshooting.

My current academic direction includes machine learning, neural networks, deep learning, large vision-language models, and natural language processing, grounded in practical software engineering with C#, C, Python, .NET, and PowerShell.

Experience

Recent Engineering Experience

Selected recent professional work in software development, automation, integration, and engineering support.

April 2020 – Present

Software Engineer

Leidos

  • Develop and maintain Windows-based automation tools and software applications using C#, .NET Framework, C, and PowerShell.
  • Design Windows GUI utilities for configuration, data migration, workflow orchestration, and integration among files, tools, and software components.
  • Automate repetitive system-administration tasks with PowerShell to improve efficiency and reduce manual effort.
  • Diagnose hardware and software issues across varied engineering environments and collaborate with cross-functional teams on requirements, technical issues, and solution design.
  • Create technical documentation and contribute to best-practice standards for software tools and automation frameworks.

Education

Education and Continuing Study

Graduate study in computer science and artificial intelligence, grounded in engineering technology.

Highest completed degree · August 2025

Master of Science in Computer Science

Case Western Reserve University

GPA: 3.9

Bachelor's degree · completed December 2019

Bachelor of Science in Engineering Technology

Seminole State College

Mechatronics and Robotics specialization · GPA: 4.0 · Summa Cum Laude

Additional degrees · completed 2015–2016

Associate Degrees

Daytona State College

  • Associate of Science in Computer Engineering Technology
  • Associate of Arts
Selected recognition

Academic Distinctions

  • Outstanding Academic Performance in Computer Engineering Technology · 2016
  • Dan Stout Award for Mathematics · 2018
  • Phi Theta Kappa Honor Society · inducted 2015
Industry credentials

Technical Certifications

  • Technical certificates in cable installation, IT support, and microcomputer repair · 2015
  • Arduino Fundamentals: Electronics and Physical Computing · 2019
  • CompTIA A+ (Good-for-Life credential) · 1997

Selected work

Projects

Selected personal and academic work across desktop software, networking, security, artificial intelligence, parallel computing, embedded systems, and robotics.

Personal project · Summer 2026

PathSelect

Portable Windows desktop utility built with C#, .NET Framework, WPF, and MVVM to manage two Ethernet adapters. It supports adapter workflows, IPv4 interface-metric routing priority, default-route inspection, and portable JSON configuration.

Summer 2025 · Data privacy research study

Geo-Inference from Images

Research study examining how convolutional neural networks and large vision-language models can infer geographic location from visual cues. It synthesized findings from five academic papers and proposed a mobile auditing concept that scores geo-inference risk and suggests targeted visual obfuscation.

Spring 2025

LiDAR Smart Parking Sensor

ESP32 and TF-Luna LiDAR integration over UART for real-time parking guidance, using parsing, hysteresis, steady-state detection, and rolling-history confirmation to filter sensor glitches.

Spring 2025

Secure Notes Android Application

Kotlin Android application protecting local notes with salted PBKDF2 key derivation, a randomly generated AES data-encryption key, and key wrapping. The cryptographic layer is separated from the user interface.

Fall 2024

Handwritten Digit Classification

Comparative machine-learning study of KNN, SVM, Random Forest, bagging, multilayer perceptron, and convolutional neural network models using R and Python. Cross-validation, early stopping, and error analysis supported a common-dataset comparison whose top CNN accuracy was 98.86%.

Fall 2024

Peer-to-Peer UDP Chat Application

C application using raw UDP sockets and a custom protocol, with automatic interface detection, peer discovery, dynamic port selection, state-aware sessions, and heartbeat/reconnect logic. A Wireshark Lua dissector supported protocol validation and troubleshooting.

Summer 2024

Parallel Sorting Performance Analysis

Merge Sort and Quick Sort implementations in C using OpenMP for CPU parallelism and NVIDIA CUDA for GPU parallelism, with execution-time comparisons across sorted, nearly sorted, and randomly ordered datasets.

Fall 2019

Autonomous Robotics Prototypes

Two autonomous mobile-robot builds: a RobotC-programmed VEX platform for line following and object delivery, and an Arduino-based vehicle supporting line following, light seeking, obstacle avoidance, and edge detection.

Fall 2019

SCORBOT Tic-Tac-Toe

Human-versus-robot tic-tac-toe system combining an Intelitek SCORBOT ER-4U robotic arm with an Arduino microcontroller, programmed with SCORBASE and the Arduino IDE.

Fall 2019 · Team project

Senior Mechatronics Design

Three-person electromechanical system integrating SolidWorks-modeled components, computer programming, microcontrollers, electronics, and a robotic arm to demonstrate core engineering-technology concepts.

Spring 2019 · Team project

Three-Floor Elevator Prototype

Two-person project to design and build a small-scale, three-floor elevator system using VEX Robotics components and the RobotC programming language.

Supporting toolkit

Skills and Capabilities

Technologies and practices represented in current professional, academic, and project work.

Artificial Intelligence and Machine Learning

  • Artificial Intelligence
  • Machine Learning
  • Neural Networks
  • Deep Learning
  • Large / Vision-Language Models
  • Natural Language Processing
  • Convolutional Neural Networks
  • TensorFlow / Keras
  • scikit-learn

Programming and Software Engineering

  • C#
  • C
  • Python
  • R
  • .NET Framework
  • WPF
  • MVVM
  • PowerShell

Operating Systems and Systems Engineering

  • Windows
  • Linux
  • UNIX / Linux environments
  • Shell scripting
  • System administration
  • Network administration
  • Systems troubleshooting

Virtualization and Containerization

  • VMware
  • Hyper-V
  • VirtualBox
  • vSphere
  • Containerization
  • Docker

Cloud, Infrastructure, and Automation

  • Azure
  • Automation
  • Software integration
  • Systems integration
  • Workflow orchestration
  • Data migration

Data, Networking, and Parallel Computing

  • SQL
  • SQLite
  • Socket programming
  • Wireshark
  • OpenMP
  • NVIDIA CUDA

Tools and Practices

  • Visual Studio
  • Git
  • GitHub
  • Bitbucket
  • JIRA
  • Confluence
  • Codex
  • Claude
  • Technical documentation
  • Cybersecurity best practices

Contact

Professional Links

Public channels for professional correspondence and current work.

Email
Email David Courtney
GitHub
View David Courtney on GitHub
LinkedIn
View David Courtney on LinkedIn
Location
Central Florida, USA