M.S. CS @ Northeastern | Amazon & Health tech Experience
Hi, I'm Yazhe! I'm a full-stack developer, currently finishing my Master’s in Computer Science at Northeastern University.
I’m passionate about building systems that not only work, but scale, integrate AI meaningfully, and make a real impact on users.
Collaborated with the commercial team to develop a web application with interactive graphs using Vue.js and Vuetify, enhancing UX by transforming complex healthcare data into actionable insights.
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Built a context summarizing feature on Salesforce platform using Gemini AI, improving user productivity by delivering essential physician information and driving a 10% growth in click rate on physician profile.
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Engineered advanced indexing strategies for PostgreSQL databases on Google Cloud Platform to ensure high availability and fast retrieval of physician and hospital data, elevating query performance by 38%.
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Constructed RESTful API endpoints with Flask for database CRUD operations on millions of physician records, reducing query latency from 1s to 20ms with Redis caching.
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Created a comprehensive test suite using Pytest, Jest, and Vitest, utilizing Sentry for error monitoring, improving backend stability and ensuring robust application performance.
Developed an expanded toolset with AWS services to fully automate the manual workflow for Alexa Skill revocation requests across NA, EU, and JP regions.
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Optimised CRUD operations using API Gateway by defining versioned HTTP endpoints, ensuring robust validation and fortifying security with IAM authentication.
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Built four AWS Lambda functions with Java, integrated SQS to scale processing from 100 QPS to 30,000 QPS, and implemented Dead-Letter-Queue to enhance reliability in handling failed requests.
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Leveraged partitioning, indexing, and data stream with DynamoDB to efficiently manage over 2.5 million data.
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Created real-time monitoring with CloudWatch metrics and AWS SNS alerts to notify on-calls within 2 seconds when system health issues arise.
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Created a CI/CD pipeline with AWS Code Pipeline to automate testing, reducing release cycles by 33% and attaining 95% unit testing coverage with Junit and Mockito.