Xiangrui Kong | Software Developer

Hi, I'm Xiangrui Kong.

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Self-motivated, fast to learn, passionate coder who appreciates solving difficult, complex problems in the real world.

About

At Trinity College Dublin, I am a graduate student studying computer science. I like coding and fixing issues. I always try to give my all to the things I perform. During my master's program, I worked with a variety of technologies, including JavaScript, TypeScript, React, Angular, Ionic, Dart, Flutter, Python, Django, MySQL, AWS, MongoDB, HTML5, SCSS, and Java. My twelve months of professional work experience have improved my React, Angular, Springboot, and Django expertise. I have a love for creating sophisticated programs that address issues affecting millions of people in the real world.

Languages: JavaScript,TypeScript, Python, Java, HTML/CSS, Dart
Databases: MySQL, AWS EC2, MongoDB
Libraries: NumPy, Pandas, OpenCV
Frameworks: React, React Hook, Dva,Angular, Ionic, Qian-kun, Flutter, React native, Django, Node.js, Kubernates,AB test, Springboot
Tools & Technologies: Git, Docker, AWS, Heroku

Looking for an opportunity to work in a challenging position combining my skills in Software Engineering, which provides professional development, interesting experiences and personal growth.

Experience

EnergyElephant

Software Engineer

App update and refresh using Flutter. Implemented features such as photo upload and capturing for electric meters.
Implemented an automatic validation feature for data upload forms using Django, HTML, JavaScript, SCSS, and utilized Jest for testing.
Utilized blender + threebox.js to model 3D buildings and display them on Mapbox, allowing visualization of energy usage and data for each building.
Applied machine learning algorithms, specifically crnn+yolov5, along with openCV and AWS Recognition, to interpret data from electricity meter photos and bills.
Tools: Flutter, Django, HTML, JavaScript, SCSS, Jest, Blender, Threebox.js, crnn, yolov5, openCV, AWS Recognition

June 2023 - Present | Dublin, Ireland

Pepsi-Cola, Inc – YumChina

Software Engineer Intern

Adopted Angular, Typescript, and Scss for page development including material list, statistical billboard, user link, alarm details, and more. Primarily performed AI analysis on Pizza Hut and KFC app data, and displayed backend data using echarts charts and tables.
Implemented SSO login jump function and user rights allocation.
Assisted a team in developing back-end services using over 30 database tables. Created over 20 RESTful APIs with SpringBoot and Swagger. Also implemented a microservice using Spring Boot and Spring Cloud to cleanse large data volumes from upstream business sources. This service also fetches the click-through and exposure rates of KFC and Pizza Hut on food delivery platforms.
Configured the Prometheus collector for MySQL database monitoring on the server and developed custom PromQL queries for tracking key metrics such as query response time, throughput, connection pool utilization, and error rates. Designed and configured the Grafana dashboard to present the data, and set up feishu to send real-time alerts to a group.
Tools: Angular, Typescript, Scss, SpringBoot, Swagger, Prometheus, Grafana

Sep 2021 - Jun 2022 | Nanjing, China

Projects

              
Dissertation Management System
                A thesis management system built with micro-front-end and micro-services.
              
AccomplishmentsTools: umi.js, qiankun, kubernetes, SpringBoot, AWS, MongoDB
Divided into different micro-services according to functions. Used Docker for package management and ab for stress testing of micro-services.
Used AWS S3 and MongoDB for distributed database management. Implemented uploading, downloading, searching, collecting, and recommending similar articles.
Incorporated group chat, task assignment, and personal data center management. Used echart for data visualization.

Intelligent Trash Bin
                An app for intelligently managing trash cans using ionic+react.
              
AccomplishmentsTools: ionic, react, blender, AWS, three.js
Used blender to create a simple 3D trash can model. Rendered and loaded the model using three.js.
Connected to AWS IoT via websocket to obtain real-time trash can information.

FindWay App
                A navigation service for Dublin residents built using React, Redis, Django, and Firebase.
              
AccomplishmentsTools: React, Redis, Django, Firebase
Integration of iOS mobile sensors to retrieve and upload user location data to Firebase.
Enabled users to determine location using coordinates from Firebase and get detailed directions.
Utilized Redis to efficiently store Dublin bus info for quick retrieval on the front-end.
Integration of bus stop details into the Mapbox map for easy user identification.
Implemented roadblock detection and A* pathfinding algorithm for alternative route calculation.

Personal Web Page
                A personal homepage showcasing basic information and main projects developed using React and Node.js.
              
AccomplishmentsDeveloped the front-end using React with animation effects realized using react-spring.
Built the back-end on the Node.js framework.
Utilized Nginx redirection for deployment.
Implemented page translation using i18next.

Microblog Public Opinion Monitoring
                A system developed using the SpringBoot framework and Thymeleaf front-end framework for monitoring public opinion on microblogs.
              
AccomplishmentsCrawled the microblog hot search list for visual display and word cloud presentation.
Conducted emotional analysis on microblog comments.
Performed user portrait analysis on bloggers in the hot search list. Utilized the random forest regression model to calculate data characteristics such as blogger fan count.
Implemented emotional alert processing for negative sentiment Weibos and visualized the logs.

Data Visualization
                Interactive real-time Dublin railway track map and Minard’s visualization of Napoleon’s Russian Campaign.
              
AccomplishmentsCreated an interactive real-time Dublin railway track map using HTML and CSS, offering detailed information about each station.
Recreated Minard’s visualization of Napoleon’s Russian Campaign using Tableau and graphical programming.

Plant Recognition System
                A system developed in Python using CNN and KNN algorithms for the purpose of plant recognition.
              
AccomplishmentsImplemented a multi-layered CNN model composed of convolutional layers, pooling layers, and fully connected layers.
Processed dataset with steps such as image normalization and data augmentation.
Used a k-Nearest Neighbors (KNN) algorithm for comparison purposes.
Deepened understanding of deep learning and traditional machine learning algorithms through hands-on development.

Coffee Ordering App
                A café ordering app developed using Ionic and React, allowing functionalities such as order placements, item bookmarking, bill viewing, and payments.
              
AccomplishmentsDeveloped a user-friendly interface using Ionic and React for seamless coffee ordering.
Enabled features such as order placements, item bookmarking, and bill viewing.
Provided a secure payment gateway for users to make payments within the app.
Tested and validated the app's functionalities to ensure reliable performance.