Jane-Ling Wang

Jane-Ling Wang is a Distinguished Professor in the Department of Statistics at the University of California, Davis. Her research focuses on advancing statistical methodologies for functional and longitudinal data analysis, deep learning applications, and survival analysis. She holds a Ph.D. from UC Berkeley and has contributed extensively to interdisciplinary fields including neuroscience, biostatistics, and machine learning.

Wang has received numerous accolades, including being elected an Academician at Academia Sinica (2022), recipient of the Humboldt Research Award (2020), and the ICSA Distinguished Achievement Award (2018). Her work bridges theory and practice, addressing challenges in data sparsity, dynamic systems modeling, and high-dimensional statistical inference.

Her recent publications emphasize innovative techniques such as SAND (Transformer-based data imputation) and adaptive basis layers for functional data analysis. These contributions underscore her expertise in integrating modern computational tools with classical statistical frameworks.