Hello, I am Tianyi Zhu, currently a Ph.D. student in Data Analytics and Decision Sciences at the Darden School of Business, University of Virginia, where I am advised by Dr. Max Biggs and Dr. Arthur Delarue. I hold a Master’s degree in Financial Mathematics from the Georgia Institute of Technology and a Bachelor’s degree in Economics and Finance from Ball State University, where I also completed a minor in graduate-level Mathematics.

Research Interest

My research focuses on applying machine learning methods to address real-world business problems, with a particular emphasis on human decision-making and pricing analytics. I am interested in understanding how data-driven models can support better strategic and operational decisions in complex environments.

I also explore advanced techniques in deep learning, reinforcement learning, and natural language processing to capture nuanced decision dynamics. In parallel, I investigate classical and modern optimization methods to improve model performance, ensure computational efficiency, and provide robust, interpretable solutions.

Professional Experience

In Summer 2024, I was a Treasury Intern at the Federal Home Loan Bank of Atlanta, where I applied quantitative modeling to study prepayment behavior in residential and commercial MBS. I developed and calibrated Yield Book and risk models, integrating macroeconomic indicators and historical cash flows to improve risk forecast accuracy and reduce MBS trading volatility. I also performed interest rate shock simulations to evaluate portfolio resilience and inform risk-mitigation strategies.

Previously, as a Student Researcher at Ed-Choice (2022), I investigated the impact of macroeconomic variables on Hong Kong’s real estate market. This work revealed causal links between inflation, wages, exchange rates, and housing prices, offering insights for understanding market dynamics and policy responses.

News

• Deep Taxonomic Networks for Unsupervised Hierarchical Prototype Discovery
  Accepted as a poster at NeurIPS 2025.
  Authors: Zekun Wang, Ethan Haarer, Tianyi Zhu, Zhiyi Dai, Christopher MacLellan.