Personal Resume
A high school student passionate about computer science and technological innovation.
I. Quick Overview
National/Provincial-Level Science and Innovation Awards 3 项
Independently/Led development 10+ projects
Github cumulative 27 Stars(As of 2026/7/10)
II. Self-Assessment
Possesses a strong interest in computers and technological innovation, self-taught relevant knowledge through attempting to create project after project, proficient in software and hardware full-stack technologies
- Academically: Through Yichang City's 2024Top Talent Through-Training Program selectionadmissions examination half a year earlyentered a provincial key high school for study.
Skilled inindependent learning and organization, strong time management ability, academic performance ranks among the top of the Innovation Experimental Class - In technological innovation:Self-taught, understood, and became proficient insoftware and hardwarefull-stack development, possesses basicinnovative idea initiation + practical product R&Dcapabilities
- Ideologically: As a Communist Youth League member, establishedthe ideal of invigorating the nation through science and technology, upright in character, respects teachers and elders, possessesteam awareness and communication skills
III. Personal Tech Stack
Embedded & IoT
Main control platforms: ESP32 series, STM32 series, Raspberry Pi
Development languages: C / C++, MicroPython
Protocols & peripherals: MQTT, TCP/UDP, HTTP/HTTPS, various sensor interfaces and hardware drivers
Hardware Design & Fabrication
PCB design: schematic design and circuit board drawing
Structure & manufacturing: 3D modeling and printing, laser cutting and engraving
AI & Computer Vision
Computer vision: YOLO object detection (Ultralytics)
Machine learning/Large models: Scikit-learn machine learning, Ollama deployment and inference
Web & Full-Stack
Frontend development: Vue 3, UniApp, HTML/CSS/JavaScript
Backend development: Python + Flask
Databases: MySQL, SQLite
System & DevOps
Operations & deployment: Linux system management, Docker containerized deployment, Nginx
Network technologies: DHCP, NAT, port forwarding/mapping, DNS resolution and domain management
Version control & tools: Git / GitHub, Shell scripting (Bash)
(……)
IV. Selected Awards and Honors
39th and 40th Hubei Provincial Youth Science and Technology Innovation Competition First Prize
2025 National Youth Information Literacy Competition Finals First Prize
V. Representative Projects
Mesh Adaptive Routing Optimization System Based on Self-Trained AI
Introduction
To address the problem that traditional wireless Mesh networks rely solely on signal strength and are susceptible to obstruction and load fluctuations, I designed and implemented an edge-intelligent routing solution. Using OMNeT++ to generate 6,959 simulation data entries, I trained a random forest model and deployed it to ESP32-C6 nodes to achieve real-time inference and autonomous networking optimization. I also completed the 3D-printed enclosure, PCB design, and full-device integration, and built a cloud monitoring platform based on Flask + Vue, supporting visualization of topology and node status.
Tech Stack: OMNeT++, Scikit-learn, ESP32-C6, PCB design, 3D printing, Flask, Vue3
Results
- The project has been successfully running and can adaptively adjust routing strategies to improve network stability.
- Project documentation:www.ycxhl.top/archives/19
- Theoretical paper:www.ycxhl.top/archives/25




ClarityAI — Intelligent Requirement Alignment Tool
Introduction
This is a tool that helps users gradually clarify vague ideas into structured project requirements through multi-turn interactive dialogue. Users only need to describe their general intent, and the system will guide the questioning, ultimately generating a clear requirements document.
Tech Stack: Vue3, Python, Flask, SQLite, Docker
Results (As of July 10, 2026)
- GitHub received 27 Stars
- Bilibili video views 35k, with 1,674 likes and 1,567 favorites
- Server records show daily user activity, with cumulative dialogue turns reaching 909
Links - Project homepage:www.ycxhl.top/archives/20
- GitHub:Frontend repository Backend repository



Smart Shared Bicycle System (Collaborative Project)
Introduction
A complete shared bicycle solution, including an Android user client, smart bike lock, and backend management platform. I was responsible for full-stack software development and embedded programming.
Functional Modules
- Android client: Map positioning, scan-to-unlock, trip records, user center
- Smart lock: Based on ESP32, integrating GPS positioning and MPU6050 attitude detection, supporting accident alerts (DingTalk push, cancellable within 10 seconds)
- Backend: Flask API + MySQL database, providing log auditing
- Management dashboard: Implemented with Vue, real-time monitoring of vehicle status
- Deployment: Docker containerization
Tech Stack: UniAPP, ESP32, GPS, MPU6050, Flask, MySQL, Vue3, Docker
Project homepage: www.ycxhl.top/archives/17





Quadcopter UAV Serial Port Simulated Remote Control
Introduction
I innovatively used a Raspberry Pi to simulate a serial receiver and performed flight control through a web interface. This project covers the complete process from hardware design to software implementation, including PCB fabrication, 3D modeling and printing, serial communication, sensor data processing, as well as joint debugging of STM32 + Raspberry Pi and PID parameter tuning.
Tech Stack: PCB design, 3D printing, STM32, Raspberry Pi, serial port (UART), PID algorithm, web control interface (HTML/JS)
Highlights
- Independently designed remote control solution, low cost and highly scalable.
- Drone attitude can be controlled through a web page, with intuitive operation.



Classroom Management Assistant — AI Classroom Analysis System
Introduction
Utilize visual recognition to analyze the head-up rate of students in the classroom, and generate reports to push to teachers' DingTalk. The system includes data annotation, model training, backend services, and frontend display.
Functional Process
- Use LabelStudio to annotate classroom monitoring images.
- Train YOLO model to detect student head posture.
- Backend (Flask) processes video stream and calculates head-up rate curve.
- Frontend (Vue3) displays charts and automatically generates analysis reports.
- Push reports to teachers via DingTalk robot.
Tech Stack: LabelStudio, Yolo, Python, Flask, MySQL, Vue3, Docker




VI. Contact Me
邮箱:3329932408@qq.com
GitHub:github.com/kazuky233
Blog:ycxhl.top