About

I am a second-year Ph.D. student in the Statistics Department at UCLA. My research interests involve explainability and fairness in deep learning, machine learning interpretability, and convex optimization. I obtained my master's degree in Data Science from Stanford University, and I graduated from Southern Methodist University while triple majoring in Mathematics, Statistics, and Management Science.

In industry, I will be working as an AI/ML intern at Apple during the summer of 2025. I worked as a Deep Learning model development intern at ASML in 2024, and in 2023 I implemented model explainability methods and developed various simulations for model probing during a six-month internship at Chemix AI, a San Francisco Bay Area startup. Additionally, I formulated convex optimization methods for experimentation design during an internship at Uber in 2022.