معرفی
Lan Zhang holds a Doctor of Philosophy in the Department of Computer Science. His research focuses on formalization of mathematical statements using large language models (LLMs), syntactic analysis, and information retrieval systems. He has contributed to constructing mathematical libraries through consistent autoformalization techniques and explored epistemic ensemble methods for formal mathematical reasoning. His work bridges AI with symbolic mathematics, emphasizing automated theorem proving and latent space modeling.
Research interests include large language models, formal verification, and mathematical logic. His recent studies address challenges in de-noising formal languages and evaluating unsupervised text representations using synthetic datasets. Zhang's publications span topics from latent variable analysis to ensemble methods in mathematical reasoning systems.
His research outputs demonstrate expertise in applying LLMs to formalize complex mathematical definitions and derive multi-operational mathematical processes in latent spaces. While no awards or grants are explicitly mentioned, his active contributions to mathematical formalization and VAE-based text representation indicate significant academic engagement.
