CHENYU MAO

• Designed a full-stack project that offers phone number history to on-call software engineers and employed machine learning tools to forecast the number's unit of measure, including region and quantity.
• Explored the latest technology stacks and tools for project implementation, authored a design document highlighting the trade-offs of each approach, and created a comprehensive development and end-to-end testing guide for the project.
• Created a workflow to fetch events information in container service and render them to message queue.
• Utilized Lambda to keep recording an asynchronous workflow and storing the service activity data to DynamoDB database.
• Controlled the different AWS services’ resources by AWS Identity and Access Management service.
• Implemented the frontend using React.js and using AWS authentication service to control the access permission.
• Used AWS CDK, Pipeline and AWS CloudWatch log to deploy and monitor the project.
• Trained a model using the number catalog dataset with AutoGluon to predict phone number pool utilization.

• Developed a full-stack solution to remind customers to retain and elevate their membership status, positively influencing an annual merchandise sales volume of three million dollars.
• Used Spring boot to develop the customer information retrieval API and made it talk to other team’s APIs.
• Deployed the backend service to Kubernetes and used CI/CD pipeline to iterate the services.
• Utilized Kafka Queue to process the customer shopping points data distributively.
• Implemented the front end by React.js and tested the code with unit and cypress test.
• Debugged the development environment and wrote the document to help our team speed up the development process.