Ms. Siyan Liu received her Bachelor's Degree in Statistics from East China Normal University in 2020 and is currently pursuing a Doctor of Philosophy (Ph.D.) in Statistics at the same institution under the supervision of Prof. Yukun Liu. In 2023, she served as a joint Ph.D. student at the University of Waterloo, where she was supervised by Prof. Pengfei Li. Her research focuses primarily on the density ratio model, empirical likelihood, and mixture model.

Qinglong Tian earned a BS in Statistics from Renmin University of China (2016) and a PhD in Statistics from Iowa State University (2021). He is now an assistant professor at the Department of Statistics and Actuarial Science at the University of Waterloo. His work in transfer learning and prediction has resulted in several publications.

Prof. Dr. Yukun Liu is a Professor in the School of Statistics at East China Normal University. He obtained his B.A. and Ph.D. degrees from Nankai University, China, in 2003 and 2009, respectively. He joined East China Normal University as an Assistant Professor in 2009 and was promoted to Associate Professor in 2013. He has been a Professor since 2018. He has also been a visiting scholar at the University of British Columbia, the University of Waterloo, and Hong Kong University. His research interests include empirical likelihood, semiparametric statistics, missing data, causal inference, and conformal inference.

Prof. Dr. Pengfei Li received his Ph.D. in statistics in 2007 from the University of Waterloo and then spent six months at the University of British Columbia as a postdoctoral fellow (2008). He worked as an assistant professor at the University of Alberta for three and half years (2008–2011). He joined the University of Waterloo in January 2012 as an assistant professor and was promoted to Associate Professor in July 2014. He has been a professor since July 2019. Prof. Dr. Li’s research interests concern some areas of statistics, including finite mixture models, asymptotic theory, biased sampling problems, empirical likelihood, inference with constraints, experimental design, and smoothing techniques.