Resume - Cooper Morgan

Cooper Morgan

Bellingham, WA • [email protected]in/Cwoopercwooper.me

Education

Western Washington University

MS in Computer Science • GPA: 4.0 Sep 2025 - Jun 2026
  • Paper: Adversarial DNS Exfiltration: Framework and Defense Evaluation.
  • Graduate courses in Machine Learning, Deep Learning, Robotics, and Neural Terrain Representation.
BS in Computer Science • GPA: 3.9 Dec 2022 - Jun 2025
  • Minor in Anthropology

Experience

Software Developer Intern

SPIE

Jun 2025 - May 2026

  • Designed the frontend architecture for SPIE's Digital Library, building a React/TypeScript component library that coordinated React Islands via a Redux global store, allowing for consistent UI/UX across the platform.
  • Refactored legacy model-bound views into well-structured API and Entity Controllers in C#/ASP.NET MVC.
  • Redesigned the Digital Library's session system end-to-end, from frontend state to backend authentication controllers.
  • Decreased page load times by 90% through Webpack bundle optimizations, lazy loading, and Redis caching.

Graduate Research Assistant

AI for Adversarial Cybersecurity, WWU

Jul 2025 - Present

  • Designed and built a novel adversarial framework in Python that outperformed state-of-the-art detection methods, validating results against real municipal network data with cross-dataset validation.
  • Developed a novel encoding scheme, rethinking adversarial DNS Exfiltration by using combinatorial mathematics to optimize data transmission through structural patterns rather than payload manipulation.
  • Implemented reinforcement learning and LSTM models to optimize system configurations and mimic realistic network behavior, maximizing throughput while evading detection.
  • Engineered concurrent data pipelines for simulating, parsing, and validating large volumes of DNS records.

Projects

TINRS — Terrain Implicit Neural Representation

Sep 2025 - Present

WWU Graduate Research
  • Evaluated 6+ neural architectures for terrain compression, achieving 30x compression over raw elevation data.
  • Built a real-time Vulkan compute shader terrain renderer in Zig with a 7-level clipmap LOD system, hitting 20,000+ FPS on desktop and 300+ FPS on a Raspberry Pi 5. Compression error is within source data noise.
  • Designed a training pipeline processing Copernicus GLO-30 GeoTIFF tiles with per-channel INT8 quantization, producing models 50-75x smaller than PNG baselines for global terrain coverage.
WWU Schedule Optimizer

Jan 2024 - Present

  • Designed and developed a full-stack course scheduling application serving up to 1,000 monthly users, using bitmask-based conflict detection with backtracking to generate optimized schedules based on timing, compactness, and GPA.
  • Built a Go backend with SQLite persistence, a background job scheduler for automated data synchronization, and a concurrent web scraper pulling from WWU's Banner API to maintain up-to-date course catalogs.
  • Developed a responsive React/TypeScript frontend with persistent client-side state, real-time course search with relevance scoring, and an interactive calendar interface for browsing and comparing generated schedules.

Skills

Languages: Go, TypeScript, C, C#, Python, SQL, Zig
Frameworks & Tools: Git, React, ASP.NET MVC, AWS, Claude Code, Linux, Tailwind CSS, Django, Docker
Specializations: Cybersecurity, Edge Computing, Machine Learning, Systems Programming, Vulkan, Robotics