Third-year master's student at Nankai University. My technical work is self-taught and project-driven, spanning data engineering, software systems, web protocols, computational research tools, and agent runtimes.
I like turning difficult one-off investigations into small systems that can be tested, explained, and maintained.
- TripAdvisor Hotel Review Data Scraper — schema-aware review parsing, pagination guards, privacy-minimized checkpoints, and a documented multi-stage research history.
- Expedia Hotel Review Data Scraper — GraphQL response parsing with explicit separation between Akamai/transport evidence and normalized data.
- Airbnb Listing Data Scraper — recursive extraction of embedded listing state with ID deduplication and clear schema-drift failures.
- Yelp Review Data Scraper — review-edge normalization and privacy-minimized pagination diagnostics that retain state without cursor values.
- Agoda Hotel Review Data Scraper — review-envelope validation and explicit ten-point to five-point rating normalization.
- Booking.com Hotel Data Scraper — an evidence-bounded challenge-state and checksum experiment for scraper-oriented protocol research.
Each repository is independently installable, bilingual, offline-tested, and contains only artificial fixtures.
- China Travel Platform Research — documentation-only protocol studies for Ctrip and Tujia; no operational collection code is published.
- Research analysis app — a research website refined through real use rather than designed first as a commercial product.
- Agent runtime learning — reading Pi and other public agent systems to understand events, sessions, tools, durable execution, trace comparison, and evaluation.
I am building toward reliable data and agent infrastructure: software that records evidence, exposes failure boundaries, and supports reproducible empirical work.
Python is my main language. I am learning TypeScript through public agent-runtime codebases.
Email: wwk990630@gmail.com