About me

I am currently a second-year Master’s student at Yale University, specializing in Biostatistics with a Data Science track. My research interests lie at the intersection of machine learning, statistical modelling, and large-scale, multi-modal complex data.

Previously, I completed my undergraduate studies in Computer Science and Statistics at the University of Toronto. Between my third and final years, I took a gap year to gain industry experience at Huawei Technologies Canada, where I contributed to cloud data engineering projects and large-scale data processing systems.

Currently, I am involved in two research assistantships at Yale University:

• Brain Connectivity Project (with Prof. Yize Zhao: I develop statistical and computational methods for structural–functional brain network modeling. My work includes implementing Block Coordinate Descent and Proximal Coordinate Descent algorithms for low-rank, sparse matrix factorization, designing synthetic-data pipelines to test identifiability of latent brain networks, and exploring theoretical aspects of centralization and sparsity in high-dimensional neuroimaging data.

• Financial GenAI Project (with Prof. Song Ma and Prof. Allen Hu): I am building a Retrieval-Augmented Generation (RAG) system to forecast strategic projects of publicly traded companies by estimating implementation costs and market values. This includes designing and implementing a Python pipeline to parse, sanitize, and embed 2TB+ of diverse datasets—including SEC filings (10-K, 8-K), patents, Wall Street Journal articles, and press releases—using OpenAI embeddings, LangChain, and Pinecone. The system achieves 85% accuracy in forecasting projects while reducing token usage by 30% through optimized memory management.

Outside the lab, I’m a certified instructor with the Canadian Association of Snowboard Instructors (CASI). If you’re ever looking for a snowboarding buddy or simply aiming for a stylish new cast, feel free to reach out!