Start from the real workflow
Every project begins with a person stuck in a process — not a model looking for a use case.
About / Creative Product Technologist
I turn complex cultural, material, and organizational systems into useful products.
With a background in textile engineering and art and technology, I combine domain research, product judgment, and AI-assisted prototyping to build clear, testable tools and experiences.
Hello
I'm Rongzhang Cao. The domains I work in keep changing — a cultural organization, a garment, a room full of sound — but the way I work stays the same.
My background connects Textile Engineering, an MFA in Art & Technology / Sound Practices, product systems, and AI-assisted prototyping. I start by understanding the context — the people, the information, the workflow — and only then decide what the technology should do.
I care about whether a system holds up: whether the sources are traceable, the evidence is sufficient, and the result is something people can actually use. AI is how I build — it is not the product.
What I do
Focus areas
The problems change shape. These are the parts of the work I keep coming back to.
- 01
Problem framing & workflow design
- 02
Product direction & prioritization
- 03
AI-assisted prototyping & evaluation
- 04
Information architecture & interaction
- 05
Source, evidence & publication governance
- 06
Cross-domain research across culture, textiles, materials, sound, and space
Method
One method,
many domains.
The projects look different because the problems are different. Underneath, the way of working is the same.
Define the product, then the system
Scope, information architecture, and the boundary between public and private come before screens.
Put AI inside boundaries
AI gathers, compares, and drafts. Humans keep judgment, review, and the final call.
Show evidence, not adjectives
Screenshots, sources, and test notes before claims. Where evidence is pending, the page says so.
Cultural & Community Systems
Platforms and information systems for artist communities and cultural organizations — where clarity, source integrity, and review workflows matter more than features.
Fashion & Material Intelligence
Garment evidence, fit reasoning, and material knowledge — grounded in a textile engineering background rather than generic AI demos.
Art, Sound & Spatial Experience
Field research, sound, and spatial installations — open-ended contexts where the outcome is an experience people can walk into, not a screen they scroll past.
Selected experience
Where I've worked
-
2025
School of the Art Institute of Chicago
Graduate Teaching Assistant
Technical support for student projects, teaching support, and studio operations.
-
Feb 2024
Uster Technologies (Suzhou)
Material Analysis Intern
Yarn and fiber testing with Uster Tester 6 and Tensorapid 5; standardized ISO/ASTM protocols and technical documentation.
Education
Where I've studied
-
2026 · MFA
School of the Art Institute of Chicago
MFA in Art & Technology / Sound Practices
-
2020–2024
Soochow University
Bachelor's Degree in Textile Engineering
Working method
How I build with AI
- Problem definition
- Domain research
- Product direction
- Information architecture
- Prioritization
- Acceptance criteria
- Evaluation
- Iteration decisions
- Implementation alternatives
- Code generation
- Refactoring
- Test generation
- Debugging support
- Documentation
I use AI to accelerate implementation — not to replace product judgment, domain understanding, or evaluation.