Student in Big Data Management and Application, working mainly across agents, full-stack systems, Linux, networks, security,and applied AI.

I do not want repositories to be only file storage. A useful repository should show the problem, the path taken, the result, and what still needs to be improved.

I belong to Hehai University Zhize Laboratory, a mainly undergraduate laboratory shaped around technical practice, project exploration, and innovation-oriented learning.

This context gives my work a practical bias. Software should be tested, discussed, documented, and improved through repeated attempts.

The laboratory atmosphere keeps this profile from becoming a pure resume wall. It should feel like a working bench with selected projects, reproducible notes, learning traces, and technical direction in one place.

I prefer repositories that keep the reasoning visible. Code is important, but setup notes, tradeoffs, failed attempts, and reproduction steps are what make a project useful after the first commit.

This is why the profile mixes project links with visual markers and concise explanations. Each section should feel like part of a learning record, not a detached gallery.

My near-term goal is to make selected repositories easier to read, reproduce, and evaluate: clearer README files, smaller verified examples, and more direct notes about what works.

I mainly study software engineering, but I keep an open interest in adjacent computer-related areas. Operating systems, networks, security, model deployment, robotics, and data workflows often meet in the same project earlier than expected.

I hope to use GitHub as a long-term record of results and knowledge: not only finished code, but also the method behind it, the problems that appeared, and the next question worth asking.