Luhuan Wu is an assistant professor in the Department of Applied Mathematics and Statistics and a member of the Data Science and AI Institute at Johns Hopkins University. Her research lies at the intersection of generative modeling, sampling, probabilistic modeling, and applications in the biochemical sciences.
Her recent work focuses on leveraging biomolecule foundation models for protein design and aligning generative models with experimental data to solve biological inverse problems. She also builds sampling methods that harness generative modeling to sample from complex target distributions, such as the Boltzmann distributions that arise in molecular systems. She is a co-founder of Reciprocal Space Station, a consortium developing open-source methods for the next generation of structural biology.
She received her BS in mathematics from Nanjing University and both her MS in data science and PhD in statistics from Columbia University. During her PhD, she interned with the Machine Learning Research group at Apple. Prior to joining Johns Hopkins, she spent a year as an associate research scientist at the Center for Computational Mathematics, Flatiron Institute.