People / Students / Class of 2026
I earned my Bachelor of Science in Data Science from the University of California, San Diego, where I developed a strong foundation in probability, data visualization, machine learning, and scalable analytics. My passion lies in using data science to turn complex datasets into actionable insights, with a particular interest in applied machine learning and decision-making systems. Throughout my studies, I worked on a variety of data-driven projects that strengthened my technical and analytical skills. My interest in how to use machine learning models to solve real world problems led me to the project of credit card fraud detection. The project was begun by evaluating different models such as logistic regression and KNN to learn fraud, but their performance doesn’t have a breakthrough compared with the base-line model. I tested and learnt some algorithms such as XGBoost algorithm, yet the results remained suboptimal. And I found the root of the issue was a huge imbalance in the dataset as the fraud case is rare. So I use SMOTE to balance the dataset and there is a significant improvement with precision scores of the models. Inspired by this experience, I joined a project that uses latent variable models to study neuron trajectories of mice’s brain behavior during decision-making. Through studying the deficient of exsiting models on dealing with the multi-dimentional data, such as PCA (Principal Component Analysis) failed to capture the temporal dynamics of long time-series data, while GPFA (Gaussian Process Factor Analysis) is computationally expensive, I realized the problems that need to be solved by the new model. So our team implemented vGPFA (variational GPFA), which reduces computational demands through sparse GP techniques. Through this project, I enhanced my skills in maximizing computational efficiency and systematically managing operations. My vision of an intelligent system for addressing more large-scale data and complex problems was also enlightened by my summer research internship at Scripps Research Translational Institute. I investigated how to use the power of LLMs to effectively summarize and capture new findings in biomedicical publications. I designed a small application that connects the API of PubMed with ChatGPT’s chatbot (OpenAI). Outside of work and academics, I enjoy finding new cuisines and learning how to cook them myself. As a cat person, I love sharing quiet moments with my pet and unwinding after a long day. In my free time, I would like to explore the neighborhood of Evanston and Chicago to discover hidden gems. I am happy to connecting with you—whether to talk about data science, share food recommendations, or just explore together.
