Xiuyuan Cheng

Xiuyuan Cheng is a Professor of Mathematics at Duke University, affiliated with the Department of Mathematics and Trinity College of Arts & Sciences. Their research focuses on developing theoretical and computational techniques for high-dimensional statistics, signal processing, and machine learning. Cheng is also a Professor of Statistical Science, effective 2026. They have contributed to recent publications in journals such as Research in Mathematical Sciences, Communications Biology, and Nature Biotechnology. Their work includes projects on gene trajectory inference and localized marker detection in single-cell RNA-seq data. Cheng has received grants from the National Science Foundation and the Simons Foundation for research in areas such as graph diffusion, transport, and network theory.

Xiuyuan Cheng is a researcher at Duke University with a focus on statistical learning, machine learning, and data analysis. Their work explores advanced methodologies for analyzing complex data, including deep learning techniques for image processing, unsupervised learning, and statistical inference. Cheng's research also extends to the analysis of biological and medical data, such as hypertension prevalence in China. They have contributed to the development of novel algorithms for signal processing, generative models, and kernel methods. Their publications highlight a strong emphasis on theoretical foundations and practical applications in machine learning and data science.