Managed the full development cycle for a distributed document review platform, serving over 100,000 users and processing 200+ million documents annually, built with Spring Boot, MySQL, PostgreSQL, AWS, and React/Dojo.

• Initialized an automated pipeline using Azure Container Instances and Azure Functions for running university research codes, addressing low automation, low maintainability, and high operational costs.• Integrated existing research codes into the designed pipeline manually, ensuring compatibility and seamless migration.

Cloud task scheduler• Developed a company-wide task scheduler in Python to perform cloud computing tasks on Amazon EC2 Instances, handling up to ~6,000 tasks per second and 4,000 instances through EC2 spot fleet.• Minimized workload cost by implementing a task scheduling algorithm to dynamically adjust instance size and instance computing power, based on task count and resources needed per task.• Decreased ~2.5% instance utilization by diminishing redundant instance initialization, reducing ~$15k budget monthly.Internal tool• Implemented a Python and SQL based solution to optimize the database scripting efficiency for updating mass data.• Developed a wrapper API in Python to batch transactions concurrently for database scripting, increasing speed by 4x and reducing 80%+ memory use.• Logged data changes and transaction events using PG/plSQL, and developed a log-based rollback function to assist with batch scripting; visualized logs in a tabular view by developing 4 web pages in Vue.js.

Developed a biological neuron emulation platform to emulate human brain activities in C++.

• Devised a solution in Python and Azure Functions to analyze students study habits and predict course drop out possibilities.• Optimized 6 hot queries performance by 50 - 80% through query analysis and optimizing query semantics.

Tested two Android cloud gaming applications with over 1m registered users, Netboom and Bifrost.