Data Scientist & ML Researcher
I build end-to-end machine-learning and NLP systems, from LLM multi-agent research to deployed prediction services that turn complex data into clarity and value.
Featured work
M.S. thesis: LLM multi-agent simulations of five real research teams (~24K utterances) with a four-layer fidelity framework and a 55-metric NLP evaluation suite. Under review at EMNLP 2026.
About me
I'm a master's student in Applied Statistics & Data Science at UCLA (GPA 4.0), with a B.S. in Data Science from UC San Diego. My work sits where large language models, NLP, and applied statistics meet, building reproducible pipelines that turn messy interaction data into rigorous inference.
In summer 2025 I researched multimodal LLM merging as an AI Model Research Intern at Samsung Electronics. My current research on LLM multi-agent simulations of research teams is under review at EMNLP 2026.
Tech stack
Let's build something great
I'm always open to research collaborations and data-science opportunities.