Huanyu Zhang is a PhD student in the Finance program at Olin Business School. He graduated from Haverford College in 2021 with a BA in Mathematics, magna cum laude. Drawn increasingly to questions that could be settled with data rather than proof alone, he completed an M.S. in Statistics at the University of Chicago in 2024. During that time he was an equal-contribution co-author of “Statler: State-Maintaining Language Models for Embodied Reasoning,” published at IEEE ICRA 2024, which enables language models to track and update the state of their environment across long sequences of reasoning steps. He then spent a year as a pre-doctoral fellow at Chicago Booth, where he assisted the Asset Embeddings project — work that applies language-model architectures to investor holdings data — and became increasingly interested in what modern machine learning could contribute to financial research. In his current research, Huanyu uses machine learning and textual analysis to study how the information investors pay attention to shapes their trading decisions and, ultimately, market prices.
