Jianbin Cui

Jianbin Cui

崔建彬

Software Developer | Graduate Student

软件开发工程师 | 研究生

Contact Information

联系方式

Phone: +86-15266052110 | Email: jianbincui_buaa@outlook.com

电话: +86-15266052110 | Email: jianbincui_buaa@outlook.com | 男 | 生源地: 北京

About Me

个人简介

Passionate software developer with a strong background in full-stack development and machine learning. Seeking opportunities to apply my skills in innovative projects.

热衷于软件开发的工程师,拥有扎实的全栈开发和机器学习背景。寻求机会将我的技能应用于创新项目中。

Education

教育经历

McMaster University

Master of Engineering in Computing and Software | GPA: 3.9/4.0

计算机科学与技术专业 | 研究生 | GPA: 3.9/4.0

09/2022 - 12/2024 | Hamilton, Ontario, Canada

09/2022 - 12/2024 | 汉密尔顿,加拿大

Research areas: Deep Learning, Graph Neural Networks, Interpretability and Security

研究领域:深度学习,图神经网络,可解释性与安全性

Beihang University | 北京航空航天大学

Bachelor of Engineering in Computer Science and Technology | GPA: 89/100 | Rank: Top 20%

计算机科学与技术专业 | 本科 | GPA: 89/100 | 排名: 20%

09/2018 - 06/2022 | Beijing, China

09/2018 - 06/2022 | 北京,中国

Major courses: Software Development, Database, Operating Systems, Object-Oriented Programming, etc.

主要课程:软件开���,数据库,操作系统,面向对象编程等

Work Experience

工作经历

Full Stack Developer Intern (Full-time)

全栈开发实习生(全职)

FGF Brands | 09/2023 - 04/2024 | Toronto, Canada

  • Developed and continuously improved Java Spring Boot framework applications, enabling over 5,000 employees to effectively streamline daily tasks and operations.
  • Implemented order feedback functionality in the front-end using HTML, CSS, React, and Kendo UI library. Optimized JavaScript by reducing DOM operations and Ajax requests, improving page loading speed by 20%.
  • Optimized backend requests through asynchronous processing, reducing request blocking time and improving response speed. Implemented interface rate limiting using Redis and other backend service optimizations to ensure system stability under high concurrency.
  • Upgraded video stream loading by replacing console-based Python script calls with Django API, improving overall video loading speed by 50%.
  • Set up CI/CD pipelines on Azure DevOps, achieving continuous integration and delivery of system updates, ensuring timely delivery of requirements with zero downtime.
  • 开发并持续改进 Java Spring Boot 框架应用程序,使5000 多名员工能够有效地简化日常任务和操作。
  • 使用 HTML, CSS, React, Kendo UI 库在前端实现订单反馈功能,通过减少 DOM 操作, 优化 JavaScript 减少 Ajax 请求,提高了页面加载速度 20%。
  • 通过异步优化后端请求,减少请求阻塞时间,提高响应速度。同时使用 Redis 实现接口限流等优化后端服务,保证高并发下系统的稳定性。
  • 通过 Django API 替代使用控制台调用 Python 脚本的方式升级视频流的加载,将视频整体加载速度提高了 50%。
  • 在 Azure DevOps 上设置 CI/CD 管道,实现了系统的连续集成和更新交付,确保需求及时交付且无停机时间。

Development Intern

开发实习生

Sinopec Shengli Oilfield Company | 06/2022 - 08/2022 | Shandong, China

  • Developed the backend portion of an internal procurement website using the Spring Boot framework, with MySQL as the database, focusing on rewriting the product details module and ensuring system availability.
  • Conducted comprehensive testing of various modules using JUnit5 as the testing framework.
  • 使用 Spring Boot 框架开发了一个内部采购网站的后端部分,使用 MySQL 作为数据库,主要专注于重写商品详情模块并确保系统的可用性。
  • 使用 JUnit5 作为测试框架,对各个模块进行了全面测试。

Research Experience

研究经历

McMaster University Research Project

06/2023 - 06/2024 | Advisor: Dr. Lingyang Chu

Interpretable Unsupervised Graph Neural Network Clustering Method

具备可解释性的无监督图神经网络聚类方法

  • Proposed a method called "Unsupervised Interpretable Deep Graph-level Clustering (IDGC)". The core method is implemented using PyTorch, and the code has been published on GitHub.
  • Our paper has been accepted: Jianbin Cui, Lingyang Chu. Interpretable Deep Graph-level Clustering: A Prototype-based Approach (ICPR 2024).
  • 提出了名为"无监督可解释的深度图级聚类(IDGC)"的方法。核心方法使用 PyTorch 实现,代码已在 GitHub 上发布。
  • 我们的论文已被接收:Jianbin Cui, Lingyang Chu. Interpretable Deep Graph-level Clustering: A Prototype-based Approach (ICPR 2024)。

University of Hong Kong Summer Research Internship

06/2021 - 10/2021 | Advisor: Honorary Professor and Associate Dean, Francis C.M. Lau

Music Similarity Detection

音乐相似度检测

  • Proposed a method for detecting similar sections between two songs, providing similarity scores based on multiple attributes such as pitch, rhythm style, and tempo. Achieved 85% accuracy on the music plagiarism detection dataset. (Python, NumPy, PyTorch, Keras)
  • 提出了用于检测两首歌曲之的相似部分的方法,同时基于音调、节奏风格和节奏等多种属性提供相似度评分。在检测抄袭音乐数据集上,准确度达到了 85%。 (Python、NumPy、PyTorch、Keras)

Projects

项目经历

SDEM Game Mall (Game shopping system based on Spring Boot and Vue.js)

09/2020 - 12/2020

  • Developed an online game store using Spring Boot as the backend and Vue.js as the frontend framework.
  • Used MySQL as the database, designed a database with 9 tables and 10 entities, and used indexing for database access acceleration.
  • Implemented user login based on Session and Cookie, and used RESTful APIs to handle HTTP requests.
  • 使用 Spring Boot 作为后端和 Vue.js 作为前端框架开发了一个在线游戏商城。
  • 使用了 MySQL 作为数据库,设计了包含 9 个表和 10 个实体的数据库,并使用索引进行数据库访问加速。
  • 实现基于 Session 和 Cookie 的用户登录, 使用 Restful API 来处理 HTTP 请求。

Complex Computer Networking

09/2020 - 12/2020

  • Completed the construction of a complex network containing 4 Autonomous Systems (AS), 26 routers, and 8 switches. The network used Open Shortest Path First (OSPF) protocol for intra-AS routing and Border Gateway Protocol (BGP) for inter-AS routing.
  • Implemented IP phone routing optimization, enabling a phone to connect with other phones located in different AS through the optimal route.
  • 完成了包含 4 个自治系统(AS)、26 台路由器和 8 台交换机的复杂网络的构建。该网络使用了开放最短路径优先(OSPF)协议进行 AS 内路由,并使用边界网关协议(BGP)进行 AS 间路由。
  • 实现了 IP 电话的路由优化,使得一个电话能够通过最佳路由与位于不同 AS 的其他电话连接。

Skills

技能