A curated portfolio bridging architectural design and design engineering — combining spatial problem-solving, user-centered thinking, and hands-on development with an informed, critical perspective on AI systems.
I'm an architect-turned-design technologist with 8+ years of experience translating complex systems into human-centered solutions. My background spans spatial design, front-end development, and independent research into AI systems — including how LLMs behave, where they fail, and what that means for products built on top of them.
This portfolio demonstrates competencies across design, development, and emerging technology:
- User-Centered Design — Designing spaces and systems around human behavior and needs
- Visual Communication — Floor plans, diagrams, and UI as information architecture
- Iterative Process — Sketches → models → renderings mirrors wireframes → prototypes → high-fidelity mockups
- Design + Code — Bridging design intent and implementation across tools and stacks
- Research — Graduate-level academic research with published, internationally distributed work; independent research into AI systems, data privacy, and responsible design
- AI Literacy — Hands-on experience with LLMs alongside critical understanding of their limitations, failure modes, and design implications
📎 View Architecture Portfolio (PDF)
- Residential renovation with before/after analysis
- Floor plans and elevations showing spatial organization
- 3D renderings demonstrating design communication
- Solar analysis and data-driven design decisions
- Google UX Design Professional Certificate (PDF) — Completed
- Mimo Full-Stack Development Certificate (PDF) — Completed
- FreeCodeCamp — In progress (HTML, CSS, JavaScript)
- Master of Architecture, RIT
- Published thesis: Integration of Daylighting into Educational Building Design for Energy Efficiency, Health Benefit, and Mercury Emissions Reduction Using Heliodon for Physical Modeling — viewed by researchers across nearly 100 countries
- International conference presentation (Bern, Switzerland)
- Research methods: physical modeling (heliodon), computational simulation (Revit/Illuminance Rendering in Cloud), environmental performance analysis, multi-criteria design evaluation
| Architecture | Product & UX Translation |
|---|---|
| Program brief, stakeholder interviews, site & user studies | Product discovery & strategy — vision, research synthesis, problem framing |
| Feature definition & prioritization (MVP), success metrics, roadmaps | |
| Space planning & user flow | Information architecture & user journeys |
| Technical drawings & diagrams | Wireframes & system design documentation |
| 3D modeling & rendering | Prototyping & visual design |
| Client presentations | Stakeholder communication & design critiques |
- HTML5, CSS3, JavaScript (in progress)
- Git / GitHub — SSH keys, GPG commit signing, version control workflows
- VS Code, browser DevTools, accessibility auditing
- Responsive layout, component thinking, design-to-code handoff
- Generative AI & LLMs — Hands-on use of Claude, ChatGPT, and other tools for research, writing, prototyping, and code assistance
- Prompt engineering — Iterative prompting, context management, output evaluation
- AI systems research — Independent study of LLM architectures, black box interpretability, model limitations, and failure modes
- AI safety & ethics — Familiarity with alignment literature (Hinton, LeCun), agentic system risks, and responsible AI design principles
- Privacy & data flows — Research into data privacy, browser fingerprinting, and consent design patterns; understanding of how tracking technologies affect user trust and UX decision-making
- Critical evaluation — Ability to assess AI tools not just as a user but as a designer: identifying where AI assistance adds value, introduces risk, or requires human oversight
Design:
Development:
AI & Research:
Architecture Tools:
I'm actively transitioning into design technologist and design engineering roles — positions that sit at the intersection of UX design, front-end development, and systems thinking. I'm building toward roles at companies where design and technology are deeply integrated, with particular interest in teams working on AI-powered products who value designers that bring both design craft and technical depth.
Current focus areas:
- Design engineering — closing the gap between design and code through practical front-end work and component-level thinking
- AI-informed UX — designing for AI systems with an understanding of how they actually work, including edge cases, failure modes, and trust calibration
- Privacy & accessibility — research-driven UX with a focus on consent design, transparency patterns, and inclusive interaction models
- Portfolio development — UX case studies bridging architecture, AI research, and front-end implementation
© 2026 Angela Read. All rights reserved.
