Jingyi Jessica Li

Jingyi Jessica Li is a researcher and academic affiliated with the University of California, Los Angeles (UCLA), holding academic appointments in both the Department of Biostatistics and the Department of Statistics. Previously, she worked at the University of Southern California from 2013 to 2019. She earned a BSc in Mathematics from Tsinghua University (2003–2007) and a PhD in Statistics from UC Berkeley (2008–2013), under the mentorship of Peter J. Bickel and Haiyan Huang.

Her research focuses on developing innovative statistical methodologies for analyzing high-throughput genomic data, particularly in single-cell RNA sequencing, spatial transcriptomics, and epigenetic studies. Key areas include contamination detection, data imputation, and robust statistical frameworks for genomic data analysis. She has contributed tools such as scDesign, scImpute, and scDEED to enhance experimental design and data quality in computational biology.

Her work bridges statistical theory and biological applications, addressing challenges like double dipping in genomic studies and optimizing machine learning approaches for biomedical data. She was awarded the prestigious 2025 Guggenheim Fellowship for her contributions to data science.

Dr. Li advises graduate students, including doctoral student Zahra S. Razaee, and collaborates on interdisciplinary projects at the intersection of statistics, genomics, and computational biology.