• Queried RESTful and graphQL APIs using GoLang to allow users to receive notifications on alternate platforms upon receiving Webhook payloads, leading to 10% increase in response times.
• Collaborated with other developers and leveraged object-oriented and asynchronous programming concepts to decrease memory usage by 50%.

• Developed infrastrucure-as-code templates on AWS via Terraform and automated deployments of service containers using Kubernetes and Helm to power a cloud-hosted movie recommendation website.

• Created a collection of Python scripts for automating common tasks, including web scraping, data analysis, and file manipulation, saving 10 hours of manual work per week.

As an undergraduate research assistant at UBC, I worked to improve existing systems and implement multithreading for improving automation systems. Although none of the code or systems I have developed are public, here is a summary of my biggest accomplishments:

• Improved concurrent database access/querying functionality for legacy SQLite database application by integrating multi-threaded architecture, increasing read and write throughput by 120%.
• Configured dynamic Grafana dashboards to visualize system metrics from internal observability tools, yielding monthly savings of 112 person-hours by automating manual database queries.
• Enhanced risk mitigation and error reporting measures by 80% through implementation of Prometheus monitoring and alerting system, ensuring consistent logging and reliable system performance.

I am head of System Architecture and formerly worked on the embedded systems subteam for UBC Agrobot, a design team focused on designing autonomous agriculture robots and their support systems. The team repositories can be seen here. Some of my notable contributions as both a developer and as sub-team lead can be seen below as well as in the past projects section.

• Implemented DevOps practices to streamline development and deployment processes, including improving cross-platform compatibility with Docker containers and making related CI/CD pipelines with GitHub Actions (e.g. Agrobots DevOps Pipelines)
• ROS2 system architecture: developed embedded system for autonomous navigation and control of agricultural robots, including integration of cameras with GPU-accelerated hardware for real-time machine learning applications
• Delivered internal back-end applications to generate system performance reports to other engineering teams, significantly improving process for benchmarking machine learning models.