Ruobing Wang

• Developed a resilient, microservices-based distributed task scheduling system, capable of managing 6,000,000 of concurrent tasks, integrating Databases with interface and Redis for rapid recovery and operational continuity, and utilizing Raft consensus algorithm to ensure data consistency across distributed nodes.
• Enhanced system performance by 70% through effective load balancing and intelligent worker selection, while ensuring 99.99% task execution accuracy through robust error handling and recovery mechanisms, thereby maintaining high reliability and precision in various operational scenarios.

• Implemented a novel debugging mechanism using SaaS, enhancing the SQS + Lambda function + OpenSearch of ELK stack and reducing the Average Handling Time from 10.8 to 2 minutes.
• Developed an OpenSearch service with strategic indexing and created customer-centric dashboards, alongside establishing a fully automated CD pipeline using CDK for seamless service stack deployment and Lambda function testing.
• Delivered and deployed project, achieving over 5,000,000 contributions with a 99.99% success rate and 0.23-second latency by leveraging Dependency Injection. Ensured comprehensive testing coverage achieving 100% statement and branch coverage using Mockito and PowerMockito.
• Designed and proposed a new integration with Amazon API Gateway, connecting OpenSearch to the team’s debugging tool and extending its benefits to customers across 5 countries.

• Developed a pre-surgical planning system using Babylon.js for risk assessment, real-time simulations, and multi-layered data visualization.
• Published research work titled "Virtual Reality System for Invasive Therapy" in the IEEE VR 3DUI Conference.