Qiyuan Zhao

Qiyuan Zhao works at the intersection of machine learning and chemistry, developing computational tools such as interatomic potentials, generative models, and large language models to predict molecular structures, chemical reactions, and material properties like electrolytes and metal complexes. Much of the work involves building large reaction and molecular datasets (databases of chemical reaction pathways and molecular properties) to train and test these machine learning methods. Applications span drug discovery, catalyst and material design, and reaction mechanism exploration.

Publication output grew substantially from 2017 through a 2022-2023 peak (17-18 papers/year), then dipped in 2024 before rising again in 2025, indicating an overall growing but somewhat variable publication cadence.

Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026