Email: zhangyikun1024@gmail.com
• Strong in Algorithm and have a very solid background in Data structure, Object Oriented Programming, System Design and Computer Science Fundamentals.
• 1 year experience as backend software engineer.
• 1 year experience in designing and developing high performance, high scalability, high robustness backend system in Java Spring.
• 3+ years hands on coding experience.
Languages:
Proficient: Java; Prior Experience: Python, SQL.
Tech Skills:
Spring MVC, Spring Boot, Spring Cloud, Node.js, Maven, MySQL, Redis, Eureka,
Hystrix, JWT, React Native, Redux.
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Experience
• Designed and implemented highly scalable RESTful APIs for core microservices of a real estate sales platform by using Spring Boot, Spring Cloud, Spring MVC, Maven, MySQL and Redis.
• Developed Consumer Microservice for user registration and login. Utilized JWT for user authentication.
• Deployed Property Microservice for housing addition, bookmark, and comment. Improved performance by using Redis for query services.
• Implemented Business Intelligence Dashboard of real-time visualization for performance metrics and KPI (key performance indicator) analysis to effectively monitor the whole system.
• Integrated service level monitoring by configuring Spring Cloud Eureka Server Cluster for microservices registration and discovery and Hystrix for circuit breaker.
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Projects
Employee Management System Design
• Built a comprehensive React Native mobile application for user authentication and employee management via applying JavaScript, Node.js, React and Redux.
• Used React Native to address navigation problems among multiple scenes and implement several methods including adding, editing and deleting employees.
• Applied Redux to create actions as well as calculate and render new states by reducers.
• Utilized firebase for data storage to authenticate users and record employee information.
CNN-based Facial Emotion Recognition
• Trained and compared ResNet models in PyTorch based on AffectNet database to recognize different emotions of human faces through the application of CNN.
• Adjusted hyperparameters with cross-validation for optimizing the model; analyzed the emotion confusion matrix for each model and explored the interactions among emotions.
• Improved training speed by 4 times via setting up distributed systems with Spark to implement the model.
• Deployed the trained model into production by using Pyqt5 and Eric to implement a mini-program for the real-time facial emotion recognition.
Instagram Database Design
• Designed a simplified version of Instagram through the adoption of Java where users can post photos, follow/unfollow another user, and acquire the 10 most recent photos in the user's news feed.
• Adopted MySQL as backend and designed the database schema to organize and query the data.
• Introduced the async strategy to reduce the latency of news feed generation.