Western Washington University

• 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.

• Taught Computer Systems 1 lab across 5 sections (~100+ students), grading code, tests, and written assignments, and holding office hours.
• Graded and TAed two Operating Systems courses.

• Architected the frontend for SPIE's Digital Library redesign as the founding React/TypeScript engineer on the team, defining the tech stack, module structure, and build standards that moved a large legacy Razor/jQuery codebase to a modern React Islands architecture.
• Designed and built the platform's React/TypeScript component library and owned its highest-traffic pages (article detail and account), authoring a live component showcase that onboarded the rest of the team to React and TypeScript.
• Built the cross-site OAuth handshake and end-to-end session handoff (sign-in, signing, and Redux state) shared across SPIE's web properties, backed by a new Redis caching pipeline.
• Cut page load times by 90% and build times by 50% through Webpack chunking, lazy loading, and pruning redundant assets from the build, and implemented hot module reloading the team had previously been unable to achieve with their SSR React Islands setup.
• Refactored legacy model-bound views into well-structured API and Entity Controllers in C#/ASP.NET MVC.

• Taught Computer Systems 1 lab across 2 sections, grading assignments and holding office hours.

• Spearheaded backend development as the sole backend developer using Python (Django) with frontend development in TypeScript (React), integrating with Canvas LMS.
• Conducted qualitative research by interviewing faculty about grading workflows and instructor-TA communication processes.
• Designed backend architecture and RESTful API endpoints for grading, feedback, and course management operations.

• Led development of the Vulkan Synthetic Vision System for Raspberry Pi 5 using Go.
• Collaborated with a multidisciplinary research team, driving meetings and aligning technical direction with project objectives.

• Automated data processing workflows in Go and Python, with PDF processing, reducing manual review by 10 hours weekly.
• Created a duplicate-checking system that identified matching SSNs and names, saving over 200 hours of manual review over the summer and reducing human error in data verification.
• Partnered with team members to identify and automate repetitive workflows, increasing efficiency and accuracy.
• Engineered a flexible document processing framework with configuration-based rule management, enabling non-technical staff to update processing logic independently.

• Designed and built a full-stack literary journal submission-management platform in Go with HTMX/Templ server rendering and a strict TypeScript admin bundle, spanning a public submission funnel and a complete editorial back office with a review queue, role-based team accounts, and bulk email notifications.
• Engineered the persistence and operations layer by embedding Litestream into the server binary to stream SQLite to Cloudflare R2 with automatic cold-start restore, and splitting editorial and analytics into two independently-replicated databases tuned to stay within R2's free tier.
• Implemented manuscript processing that extracts text from TXT, DOCX, and PDF submissions for plagiarism phrase-search, plus a live CodeMirror workbench that converts accepted pieces into typeset HTML.

• 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.

• 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.

• Trained a DQN policy in Webots simulation for autonomous light-seeking on a 29g Crazyflie drone, using camera-based brightness detection and ToF rangefinders for obstacle avoidance.
• Deployed the trained model on-device via ONNX on the GAP8 RISC-V MCU, running real-time inference alongside a PID flight controller on the STM32 Cortex-M4 (168 MHz, 192 KB SRAM).
• Built the full sim-to-real pipeline including a Gymnasium environment with custom reward shaping, relative brightness CV, and offboard-to-onboard deployment staging.

• Built a TypeScript VSCode extension with custom lexer and abstract syntax tree parser to provide syntax highlighting and linting for KPL (Kernel Programming Language) and its compiled Blitz assembly output.
• Implemented context-aware hover documentation, 7+ diagnostic lint rules for symbol validation, and an automated Blitz assembly formatter with label-based indentation and comment alignment.
• Published to the VS Code Marketplace with automated CI/CD via GitHub Actions.

Project: Vulkan Synthetic Vision System. Faculty Spotlight