Hi, I'm
Research Scientist @ Guide Labs
Building AI that is interpretable, trustworthy, and safe for humans.
A sunny day of December in San Diego, CA
I'm a Research Scientist at Guide Labs, a product-focused AI research company in San Francisco dedicated to building interpretable and reliable AI technology.
I earned my PhD in Machine Learning from Auburn University in 2025, working with Anh Nguyen. I was a Presidential Research Fellow — the most prestigious graduate fellowship at Auburn. Previously, I completed my M.Sc. in Computer Science at KAIST, South Korea.
My research focuses on making AI models interpretable to humans — enabling people to debug, understand, and ultimately trust AI systems. I've published at top venues including NeurIPS, CVPR, and TMLR.
Research accepted at top AI venues
News, talks, and announcements
Excited to share that I’ll be moving to San Francisco this summer to start a new chapter as a AI Research Scientist!
Our work Interpretable LLM-based Table Question Answering got accepted at Transactions on Machine Learning Research.
🎉 Exciting News! 🎉
This summer, I joined JPMorgan Chase as an AI Research Intern in Manhattan, NYC.
Our work PCNN: Probable-Class Nearest-Neighbor Explanations Improve Fine-Grained Image Classification Accuracy for AIs and Humans got accepted at T...
Our work Allowing humans to interactively guide machines where to look does not always improve human-AI team’s classification accuracy got accepted...