University of Alberta Department of Mathematical and Statistical Sciences
Welcome to Homepage of Bei Jiang!
Home Experience Publications Teaching Software Students Resume Links


Bei Jiang, Ph.D.
Associate Professor
Department of Mathematical and Statistical Sciences
University of Alberta
Canada CIFAR AI Chair, Fellow
Alberta Machine Intelligence Institute (Amii)
Edmonton, AB Canada T6G 2G1
Office: CAB 435
Email: bei1-at-ualberta-dot-ca

2014: PhD in Biostatistics, University of Michigan, Ann Arbor, MI
2008: MS in Biostatistics, University of Alberta, Edmonton, AB
2004: BS in Information and Computing Science, Beijing University of Technology (BJUT), Beijing, China

Research Interests
Methods for Joint Modeling of Longitudinal and Health Outcome Data, Bayesian Hierarchical Modeling, Mixture Modeling
Functional and Imaging Data Analysis, Kernel Machine Regression/Classification, Bayesian Support Vector Machine

Honors and Awards
2015: New Research Fellow, SAMSI
University of Michigan, Ann Arbor, MI, USA
2013: Rackham Conference Travel Award
2013: National Institute of Statistical Sciences Affiliate Award
2012: Rackham Conference Travel Award
2009-2012: Alexander Graham Bell Canada Graduate Scholarship, NSERC
University of Alberta, Edmonton, Alberta, Canada
2008: J Gordin Kaplan Graduate Student Award
2008: Statistical Society of Canada Travel Award
2008: The Best Consultant of the Year 2008
2008: Graduate Student Scholarship by Alberta Advanced Education and Technology
Beijing University of Technology, Beijing, China
2005: Excellent Graduate Student Scholarship
2004: Outstanding Graduate by Beijing Municipal Commission of Education
2004: Outstanding Bachelor Dissertation Scholarship
2001: Excellent Student Leader Scholarship
2001-2003: Excellent Student Scholarship

Fundings and Grants
2023 - 2024: Achieving Fairness in AI with Synthetic Data, Amii RAP, PI: Bei Jiang $77,000 (total)
2023 - 2024: Gaussian Differential Privacy Over Riemannian Manifold, Amii RAP, PI: Bei Jiang $77,000 (total)
2022 - 2027: Novel Analytics and Privacy Tools for Heterogeneous Health Data, Canada CIFAR AI Chairs Program, PI: Bei Jiang $375,000 (total)
2023 - 2024: Novel Statistical Integration Methods for Multi-View Data, NSERC Alliance - Alberta Innovates Advance Program, PI: Bei Jiang $36,000 (total)
2022 - 2025: Develop Geospatial Artificial Intelligence Geodatabases and Cloud Platforms for Automating Manual Observation Associated with Wheat Production, MITACS Accelerate, Co-PIs: Bei Jiang and Joy Agnew (Olds College), $480,000 (total)
2022 - 2025: Synthetic Data and Risk Measures for Statistical Disclosure Control, Canadian Statistical Sciences Institute, Collaborative Research Team Grant, Co-PIs: Bei Jiang (50%), Sophie Charest, Universite Laval (50%), $210,000 (total)
2022 - 2025: Using Machine Learning Methods to Predict Truck Productivity in Oil Sands Mining, NSERC Alliance Grant, PI: Wei Liu, UA(50%), Co-PI: Bei Jiang (50%), $375,000 (total)
2020 - 2023: BIAS: Responsible AI for Labour Market Equality, Canada-UK Artificial Intelligence Initiative, PI: Linglong Kong (45%), Co-PIs: Bei Jiang (25%), Nicole Denier (15%), Karen Hughes (15%), $460,000(total).
2020 - 2024: Statistical Machine Learning Methods Applied to ATB Data for Debt Collection Optimization, Small Business Lending Decision Modelling, and Open Banking Initiatives, MITACS Accelerate, PI: Bei Jiang $220,000.
2021 - 2023: Designing Appropriate Credit Risk Model for Big Data via Cloud Computing, MITACS Accelerate, PI: Bei Jiang, $45,000 (total)
2021 - 2023: Organizational Life Cycle Modelling: Assessing and Aligning Financial Institution Resources and Methodology, MITACS Accelerate, PI: Bei Jiang, $15,000 (total)
2016 - 2022: New statistical methods for functional and array-valued brain imaging data: joint modelling and statistical machine learning perspectives, NSERC Discovery Grant, PI: Bei Jiang, $20,000/year; $120,000 (total), including Discovery Grant of Early Career Researcher Supplement ($ 5,000/year)
2020 - 2021: A Principled Approach to Developing Machine Learning Models for the Synthesis of Structured Health Data, MITACS Accelerate, Co-PIs: Bei Jiang (33%), Linglong Kong (UA) (33%), and Adam Kashlak (UA) (33%), $135,000 (total)
2020 - 2021: Using machine learning methods to predict truck productivity in oil sands mining. University of Alberta Pilot Seed Grant, PI: Wei Liu (50%), Co-PI: Bei Jiang (50%), $30,000 in total.
2018 - 2019: Statistical Machine Learning Methods Applied to ATB Data for Credit Risk Modelling, MITACS, PI: Bei Jiang $40,000(total).
2015 - 2018: Start-up Funds, University of Alberta, PI:Bei Jiang, $50,000 (total)