- 个人简介 About Me
- 核心技能 Core Skills
- 技术栈 Tech Stack
- 项目经历 Projects
- 科研经历 Research
- 获奖情况 Awards
顾明珂 Mingke Gu
昆明理工大学 Kunming University of Science and Technology
建筑工程学院 621房间 ROOM 621, School of Architecture and Engineering
就读于昆明理工大学，智能建造专业本科生，2023级。对人工智能、计算机、单片机领域充满热情，专注于探索人工智能在结构健康监测中的创新应用。
A sophomore in Intelligent Construction at Kunming University of Science and Technology, passionate about artificial intelligence, computer science, and microcontrollers. Focused on exploring innovative AI applications in structural health monitoring.
核心技能 Core Skills
全栈开发 Full-Stack Development
精通前端与后端开发，能够搭建完整的网站架构，使用Vue.js、Node.js等现代技术栈，实现高效、美观的解决方案。
Proficient in both frontend and backend development, capable of building complete website architectures using modern tech stacks like Vue.js and Node.js.
人工智能应用 AI Applications
探索AI在结构健康监测中的应用，结合计算机视觉和机器学习，开发创新解决方案，提高基础设施安全监测效率。
Exploring AI applications in structural health monitoring, combining computer vision and machine learning to develop innovative solutions.
建筑结构设计 Structural Design
具备扎实的建筑结构设计基础，熟悉主要结构设计软件，能够进行结构稳定性分析与优化，参与多个学校结构设计竞赛项目。
Solid foundation in structural design, proficient in major structural design software, capable of performing stability analysis and optimization.
团队协作 Team Collaboration
优秀的团队协作能力，擅长跨学科交流与项目管理，在多个团队项目中担任队长，引领团队取得优异成绩。
Excellent teamwork skills with interdisciplinary communication and project management abilities. Led multiple team projects as captain.
技术栈 Tech Stack
项目经历 Projects
基础设施智能运维平台 Infrastructure Maintenance Platform
为云南省教育厅基础设施智能运维科技创新团队设计和开发的综合性网站平台，包含团队介绍、科研成果展示、技术交流等功能。
A comprehensive website platform designed for the Yunnan Provincial Education Department's Infrastructure Intelligent Maintenance Technology Innovation Team.
结构健康监测系统 Structural Health Monitoring
基于深度学习的桥梁结构健康监测系统，通过计算机视觉技术自动识别结构损伤，提供实时监测与预警功能。
Deep learning-based bridge structural health monitoring system that uses computer vision to automatically identify structural damage.
科研经历 Research Experience
一种集自然语言交互与自我迭代优化的建筑安全监控系统 A Building Safety Monitoring System with Natural Language Interaction and Self-iterative Optimization
本发明提出了一种创新型建筑安全监控系统，集成自然语言处理与深度学习技术，实现建筑环境的智能监测与风险评估。系统通过持续学习和自我迭代，提高对安全隐患的识别精度和预警能力。
This invention proposes an innovative building safety monitoring system that integrates natural language processing and deep learning technologies to achieve intelligent monitoring and risk assessment of building environments. The system improves the accuracy of identifying safety hazards and early warning capabilities through continuous learning and self-iteration.
更多研究成果即将发布 More research achievements coming soon
我正在积极推进更多的科研项目，包括论文研究与专利申请
I'm actively advancing more research projects, including paper research and patent applications
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