Payal Shah is a Senior Vice President of Data Science and Analytics Manager at Bank of America, where she currently leads risk modeling work. She completed her PhD in Applied Statistics from UC Riverside in 2008, where she worked primarily on sequential hypothesis testing with applications to pest management. 

Ying Liu works as a data scientist at Meta where she focuses on causal inference. She obtained her PhD degree in statistics at University of California, Riverside in 2022. Her research interests are causal inference, especially in treatment effect estimation, and machine learning.

Rui Ma is a Ph.D. candidate in Statistics at the University of California, Riverside (UCR). Before entering UCR, she completed her Bachelor’s degree in Actuarial Science at University of California, Santa Barbara. Her current research work is related to high-throughput genomic computational analysis techniques, and she is interested in bioinformatics, computational genomics, statistical and machine learning. For the future, she plans to continue to enter academia. 

Ke Huang is a PhD student in the Statistics at University of California, Riverside. Her research focuses on deep learning, including providing theoretical explanations of why deep learning models can be powerful in practice and exploring some applications in medical fields. In her free time, she enjoys hiking and playing board games.

Emily Ouyang is a Ph.D student in the Department of Statistics at UCR, where she also received her Bachelors of Science in Mathematics for Teachers of Secondary School and Pure Statistics. Her main research interest is education research, among other sociological issues.