Lin Wang is Assistant Professor of Statistics at Purdue University. Before joining Purdue in 2022, she held the position of Assistant Professor of Statistics at George Washington University. She earned her Ph.D. in Statistics from the University of California, Los Angeles in 2019. Dr. Wang's research interests include active learning, adaptive sampling, big data subsampling, computer experiments, experimental design, and causal inference. Her contributions to the field are evident in her substantial body of work, with her primary authorship of approximately twenty articles. Many of these articles have been featured in esteemed statistical journals, including the prestigious Annals of Statistics and Annals of Applied Statistics. Dr. Wang serves as the Associate Editor for the Journal of the Korean Statistical Society and the referee for more than 20 academic journals.

Dr. Wang’s research focus encompasses the creation of innovative statistical methodologies and their practical application across various fields. She specializes in robust and reliable statistical learning methodology to tackle the complexities and uncertainties in real data. Her research bridges the gap between theoretical concepts and practical applications, ensuring that her methodologies and findings are applicable to real-world scenarios. Her practical contributions extend through a vast spectrum of fields, including 1) health sciences with a focus on critical facets such as cancer diagnosis, treatment strategies, and drug combination studies; 2) industrial sectors, particularly in areas entailing manufacturing and engineering challenges; 3) computational genetics and genomics.