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.

• 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.

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.