Hello! I am a Statistics master’s student in Prof. Cynthia Rudin's Interpretable Machine Learning Lab at Duke University. My research focuses on building interpretable, scalable, and efficient machine learning models. I am interested in sparse models and variable importance, motivated by the question: What model should we use, and which features truly matter?
I feel fortunate to have previously collaborated with Prof. Anru Zhang on deep learning theory, Prof. Aditya Devarakonda on accelerating solvers for penalized regression, and Prof. Yiran Chen on accelerating generative models. Prior to Duke, I earned my honors B.S. in Mathematics at University of Science and Technology of China through the School of the Gifted Young.
