I am a Data Science Master’s student at Columbia University specializing in Natural Language Processing (NLP), Quantitative Research, and Large Language Models (LLMs). I am passionate about leveraging data to drive innovative solutions and business insights.

My professional experience includes:

• Data Science Intern, Trepp, Inc.

  Implemented innovated multiple semantic preprocessing techniques for both unstructured and tabular data using large language models (LLMs) and developed an advanced Retrieval-Augmented Generation (RAG) application to process in-house unstructured data.

• Data Science Intern, Shengang Securities Co., Ltd.

  Designed and implemented a quantitative strategy that integrated trending and machine learning techniques with sentiment analysis and risk mitigation, significantly improving portfolio performance and decision-making processes.

• Research Assistant, Harvard University

  Co-authored a publication in the top-tier NLP conference, the Association for Computational Linguistics (ACL), presenting groundbreaking research on leveraging LLMs for low-resource biomedical applications, with a focus on improving inference efficiency and model optimization.

I am actively seeking full-time opportunities in quantitative research/data science where I can contribute to impactful projects.

Interest

I’m a passionate basketball fan and player who loves the thrill of the game. I also enjoy strategic games like poker, Monopoly, and chess—anything that keeps me on my toes!

When I’m not on the court or playing games, you can find me exploring new cuisines and traveling to exciting places. I have a curious spirit and love discovering what the world has to offer!