I'm a data engineer who believes the best code is the code you don't have to write twice (thanks, libraries). When I'm not wrestling with distributed systems or convincing databases to play nice with each other, you'll find me experimenting with AI agents that occasionally work better than expected, and sometimes hilariously worse. I've migrated terabytes of data, optimized queries that ran slower than my morning coffee routine, and written ETL pipelines that (mostly) don't break at 3 AM.
Originally from Hong Kong, fluent in English, Chinese, and SQL (though my SQL is definitely more eloquent). I take my infrastructure seriously, but not myself. After all, someone's gotta laugh when production goes down. Currently based in the Bay Area, perpetually caffeinated, and always one YAML file away from either genius or disaster.
View ResumeLangflow is a low-code app builder for RAG and multi-agent AI applications. It’s Python-based and agnostic to any model, API, or database.
Polkadot/Substrate UI for interacting with a Polkadot and Substrate node. This is the main user-facing application, allowing access to all features available on Substrate chains.
A RAG knowledge base built with Dagster, enabling semantic search across Dagster documentation and community resources using Pinecone.
A deep learning-based web application that detects cracks in concrete structures using transfer learning with ResNet18.
This project examines the connections between COVID-19 and global warming, exploring how pandemic-driven changes in human activity impacted environmental metrics like carbon emissions and air quality. The project analyzes data trends to highlight the intertwined effects of health crises and climate change on global sustainability.
Ready to collaborate or discuss exciting opportunities? Whether you're a recruiter, colleague, or fellow alumnus, I'd love to connect and share insights. Feel free to reach out to me connect with me on LinkedIn! Let's shape the future together.
Ping me