About me
I’m a third-year undergraduate student majoring in Applied Mathematics and Statistics at Stony Brook College of Engineering and Applied Sciences and the Department of Applied Mathematics and Statistics, Stony Brook University. My research interests lie at the intersection of AI for Science, Large Language Models (LLMs), and Generative Models.
Specifically, I focus on leveraging LLMs for molecular optimization and drug editing, investigating how language-based models can understand and manipulate chemical structures through SMILES, SELFIES, or graph-based prompts. I am also interested in generative approaches that can propose novel molecules with desirable properties under complex constraints.
I view LLMs and generative models as foundational tools in the future of scientific discovery. LLMs can encode massive domain knowledge and enable zero-shot reasoning over symbolic and structured scientific data. Meanwhile, generative models—especially diffusion-based and autoregressive architectures—offer a principled way to explore chemical and physical design spaces, opening new doors for molecule generation, materials design, and reaction planning. I believe the synergy of these two paradigms will help build intelligent scientific assistants that can hypothesize, simulate, and even iterate with humans in the loop.
I am currently preparing to apply for Ph.D. or M.S. programs for Fall 2026, aiming to pursue research in machine learning with applications to molecular design, scientific discovery, and automated reasoning.
I am very fortunate to be advised by Professor Yi Liu from Stony Brook University.
You can find my CV here: Yichi Zhang’s Curriculum Vitae.