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| Bei Jiang, Ph.D. |
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| Associate Professor |
| Department of Mathematical and Statistical Sciences |
| University of Alberta |
| Canada CIFAR AI Chair, Fellow
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| Alberta Machine Intelligence Institute (Amii) |
| Edmonton, AB Canada T6G 2G1 |
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| Office: CAB 435 |
| Email: bei1-at-ualberta-dot-ca |
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| Education |
| 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 |
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| 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 |
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| 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 |
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| Fundings and Grants |
| Current: |
| 2023 - 2024: Achieving Fairness in AI with Synthetic Data,
Amii RAP, PI: Bei Jiang $77,000 (total) |
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| 2023 - 2024: Gaussian Differential Privacy Over Riemannian Manifold,
Amii RAP, PI: Bei Jiang $77,000 (total) |
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| 2022 - 2027: Novel Analytics and Privacy Tools for Heterogeneous Health Data,
Canada CIFAR AI Chairs Program, PI: Bei Jiang $375,000 (total) |
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| 2023 - 2024: Novel Statistical Integration Methods for Multi-View Data,
NSERC Alliance - Alberta Innovates Advance Program, PI: Bei Jiang $36,000 (total) |
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| 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) |
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| 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) |
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| 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) |
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| 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). |
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| 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. |
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| Past: |
| 2021 - 2023: Designing Appropriate Credit Risk Model for Big Data via Cloud Computing,
MITACS Accelerate, PI: Bei Jiang, $45,000 (total) |
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| 2021 - 2023: Organizational Life Cycle Modelling: Assessing and Aligning Financial Institution Resources and
Methodology,
MITACS Accelerate, PI: Bei Jiang, $15,000 (total) |
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| 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)
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| 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) |
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| 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. |
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| 2018 - 2019: Statistical Machine Learning Methods Applied to ATB Data for Credit Risk Modelling, MITACS, PI: Bei Jiang $40,000(total). |
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| 2015 - 2018: Start-up Funds, University of Alberta, PI:Bei Jiang, $50,000 (total) |
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