Advisor: Aaron Schein
In 2018, I successfully earned my Bachelor’s degree in Computer Science from UC San Diego. Following this, I engaged in a significant period of professional growth as a software engineer at Microsoft, where I gained practical, hands-on experience until 2021. Driven by my unwavering passion for the field, I embarked on a journey to deepen my knowledge, resulting in gaining a Master’s degree in Computer Science with a specialized focus on Machine Learning from Columbia University in 2023. Since then, my academic pursuits have been dedicated to the intersection of Machine Learning and Statistics, as I have committed myself to research at the University of Chicago.
I aspire to create interpretable probabilistic tools and methodologies, aimed at facilitating the extraction of valuable insights from data. My goal is to collaborate closely with subject matter experts across diverse fields, fostering an interdisciplinary approach that combines their domain knowledge with cutting-edge machine learning techniques. This synergy will enable the development of customized algorithms tailored to specific applications, ultimately empowering individuals to gain a deeper and more meaningful understanding of their data.