Developed a comprehensive management system based on Spring Boot, MySQL, Redis, MongoDB, and React for managing, importing, analyzing, and calculating musical instrument order data across various platforms.

Handled loading effects uniformly within the project, optimizing loading screen flicker through request counting.

Queried millions of business data records, reducing query time from 10s to under 1s by analyzing SQL and utilizing indexes effectively. Designed and developed the permission management module, ensuring system security control with Spring Security. Ensured appropriate permissions for different user roles, safeguarding system information.

Implemented virtual scrolling to render only the visible area at a time, resolving lag issues when rendering large lists with 2000+ items. Optimized RabbitMQ by increasing consumer instances and implementing batch processing, doubling throughput from 500 to 1000 messages per second. Enhanced handling of large-scale musical instrument orders.

Contributed to API design and development of a distributed system for the company’s data analytics platform.

• Assisted in implementing microservices architecture to decouple services, allowing for better scalability.

• Implemented a dynamic scaling mechanism using Kubernetes, improving resource allocation and reducing

infrastructure costs by 17%.

• Collaborated with cross-functional teams to enhance stability and scalability by migrating monolithic services to

a cloud-based infrastructure, leading to a 2x increase in system throughput.

Built a responsive vessel fuel cost efficacy page with React, HTML, and Bootstrap, supporting real-time calculations, cost comparisons, and optimization suggestions.

Implemented Next.js for selective server-side rendering, reducing page rendering time to 800ms.

Collected user interaction data through event tracking, ensuring the page meets the 3s performance requirement.

Introduced ahooks to improve code readability. Simplified code by using hooks such as useSetState, useRequest, and usePagination, eliminating previous redundancy in request handling.

Optimized bundle size through Tree shaking, Scope Hoisting, and Gzip compression, reducing the size from 17MB to 3.8MB.

• Built a Breadth-first Search Web Crawler across major online travel agencies and visualized data.

• Trained a linear regression model to predict hotel prices for marketing forecasts.

• Developed classifiers using Naive Bayesian Classifier, and Logistic regression to sift through abnormal data sets.

• Built up an automatically Excel file compiling system using Python, reducing time cost from 2hrs to 5 mins

• Design test fixtures using SolidWorks to reduce human involvement, which eliminated the need for training and improved accuracy of the operation

• Help solve the problem of brittle material by testing various lots and building up a database

• Performed force experiments and analysis using Instron and built a database used to cross-reference and finding root cause