Bei Jiang

Dr. Bei Jiang is an Associate Professor in the Department of Mathematical and Statistical Sciences at the University of Alberta, Canada. She holds the Canada CIFAR AI Chair and is affiliated with the Alberta Machine Intelligence Institute (Amii). Her academic journey includes a PhD in Biostatistics (2014) from the University of Michigan, MS (2008) and BS (2004) from the University of Alberta and Beijing University of Technology, respectively.

• Current Positions: 2021–Present (Associate Professor), 2022–Present (CIFAR AI Chair)
• Past Appointments: Assistant Professor (2015–2021), Postdoctoral Fellow at Columbia University (2014–2015), Research Assistant at University of Michigan (2009–2013)

Research Interests: Dr. Jiang specializes in methods for joint modeling of longitudinal and health outcome data, Bayesian hierarchical modeling, functional and imaging data analysis, and statistical machine learning. Her work integrates kernel machine regression, differential privacy, and synthetic data generation to address challenges in heterogeneous health data and neuroimaging.

Scientific Awards: Highlights include the 2015 SAMSI New Research Fellow, multiple Rackham Conference Travel Awards (2013, 2012), and prestigious NSERC scholarships (2009–2012). She has also received the J Gordin Kaplan Graduate Award (2008) and Statistical Society of Canada Travel Award (2008).

• Grants: $375,000 (CIFAR AI Chairs, 2022–2027), $480,000 (MITACS Accelerate, 2022–2025), and $210,000 (Canadian Statistical Sciences Institute, 2022–2025)

Students and Postdocs: She mentors numerous PhD, MSc, and Postdoctoral Fellows, including Junxi Zhang (2023–Present), Enze Shi (2022–Present), and former advisees like Wenxing Guo (now Lecturer at University of Essex) and Yafei Wang (Assistant Professor at University of Alberta).