I turn AI, research, and product ideas into systems you can verify.
I move from problem definition to implementation, testing and evidence. This portfolio shows not only the outcome, but also what I owned, what has been verified and what remains limited or conceptual.
Six projects. Six evidence states.
Software screens, tests, terminal output, structural photos and clearly labeled concepts form the portfolio. Work without public proof is not presented as complete.
Public build evidence is still being prepared; no invented screenshot is used as a substitute.
- Health records
- Lifestyle support
- Moxibustion scenario
- Multi-device concept
This is a product concept, not a validated medical product.
- 01Requirement framing
- 02Agent plan
- 03SolidWorks automation
- 04Patent drawing processing
Real task records, scripts, models and image-processing outputs form the case evidence.
The frontend and backend have been verified locally with 49 tests passing. Public screens are privacy-reviewed and exclude student identities, API keys and source classroom data.
Open full case study ↗36 offline tests passed. The interface and reports demonstrate the workflow only. They are not investment advice, a profit claim or proof of autonomous order execution.
Open full case study ↗The frontend structure has been reviewed. Public build evidence is still in preparation, so no invented interface is used.
Open full case study ↗- Health records
- Lifestyle support
- Moxibustion scenario
- Risk notices
- Multi-device concept
This is a product and competition concept, not a completed application or validated medical product.
Open full case study ↗The photos and models show form, position and assembly intent. They do not validate electronics, sensing, atomization, safety or health effects.
Open full case study ↗- 01Requirements and boundaries
- 02Stepwise execution plan
- 03SolidWorks automation
- 04Patent drawing and delivery review
Evidence comes from real task records, scripts, models and image-processing outputs. This is not one packaged software product.
Open full case study ↗Make the problem clear. Then make the result credible.
AI can accelerate implementation, but it does not replace requirement judgment, factual review, privacy boundaries or final acceptance.
- 01Define the real problem
Clarify the user, context, constraints and definition of done before selecting technology.
- 02Build a working path
Break the goal into pages, scripts, interfaces, models or structural prototypes with a fallback.
- 03Verify the output
Use tests, runtime screens, reports, models or structural photos to prove what actually exists.
- 04Document limits and next steps
State what is private, unvalidated or conceptual instead of hiding it behind vague language.
A rehabilitation-science background crossing into AI, web and engineering prototypes.
I am Liu Wenlong, also known as David Liu, a rehabilitation-therapy undergraduate and independent project builder. I participate in medical research and experimental coordination while building AI applications, research websites, automation scripts, market-analysis tools and smart-hardware structural prototypes.
My strength is not limited to calling one model. I turn ambiguous needs into executable paths while keeping facts, risk and delivery boundaries clear across disciplines.
Read the full public resume ↗- AI applications
- Model APIs, prompting, RAG foundations, feature flows and local prototypes
- Web delivery
- HTML, CSS, JavaScript, React, Next.js and static deployment
- Python automation
- CLI tools, data processing, tests, API calls and engineering scripts
- Product and engineering
- Requirements, interaction planning, CAD modeling, patent drawings and acceptance documentation
Deputy lead of a research experiment group · Competition project department lead · Requirements, implementation and test owner across multiple independent AI and web projects
Need someone who can turn a complex problem into working evidence?
I am exploring opportunities in AI applications, web development, digital projects, product operations and cross-domain innovation. Review the project evidence, open the public resume or contact me directly.