University of Alberta Department of Mathematical and Statistical Sciences
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Linglong Kong, Ph.D.
Associate Professor
Canada Research Chair in Statistical Learning
Department of Mathematical and Statistical Sciences
University of Alberta
Edmonton, AB Canada T6G 2G1
Office: CAB 431
Email: lkong-at-ualberta-dot-ca

2009: PhD in Statistics, University of Alberta, Edmonton, Canada
2002: MS in Statistics, Peking University, Beijing, China
1999: BS in Probability and Statistics, Beijing Normal University, Beijing, China

Research Interests
Functional and Neuroimaging Data Analysis: Varying coefficient model, Multiscale adaptive regression model, Imaging genetics, Connectivity Analysis, MRI, fMRI, and DTI data analysis
Statistical Machine Learning: Variable screening, Sparse learning, Ensemble Learning, Dimension reduction, Adaptive learning, Predictive Learning, Online Learning, Deep learning and Reinforcement learning
Robust Statistics and Quantile Regression: Multivariate, Functional, and Bayesian quantile regression, Depth-based methods, Robustness in neuroimaging data analysis, Robustness in machine learning

Editorial Service
2021 - present: Guest Editor, Frontiers in Neuroscience,
2019 - present: Associate Editor, Journal of the American Statistical Association, Applications & Case Studies
2019 - present: Associate Editor, International Journal of Imaging Systems and Technology
2017 - present: Associate Editor, Canadian Journal of Statistics
2019 - 2021: Guest Editor, Canadian Journal of Statistics,

Fundings and Grants
2021 - 2021: Zipstall -- On-line and Off-line Parking Availability Prediction , MITACS $30,000 (PI)
2021 - 2022: Indoor Virtual Tour and Virtual Object Display in 360 Degrees , MITACS, $213,333.33 (Co-PI $53,333.33, PI, Di Niu - UAlberta)
2021 - 2021: AI-Enabled Subnetwork Selection, , MITACS, $15,000 (PI)
2020 - 2022: High Dimensional Sampling in Reinforcement Learning and its Applications , HTCCL, $156,000 (PI)
2020 - 2023: BIAS: Responsible AI for Labour Market Equality, Canada-UK Artificial Intelligence Initiative, $460,000 (PI; Co-PIs: Bei Jiang, Nicole Denier, Karen Hughes - U Alberta)
2020 - 2023: Distributional Reinforcement Learning: Theories and Applications, UAHIJIC, $202,500 (PI)
2018 - 2023: Novel Statistical Methods in Functional and Brain Imaging Data Analysis, NSERC-RGPIN, $205,000 (PI)
2020 - 2021: A Principled Approach to Developing Machine Learning Models for the Synthesis of Structured Health Data, MITACS, $135,000 (Co-PI, Co-PIs: Bei Jiang - U Alberta and Yan Liu - Concordia Univ.)
2020 - 2020: Statistical machine learning for urban transportation system, MITACS, $30,000 (PI)
2019 - 2019: Augmented decision making capabilities for innovation management and continuous improvement by organizations, MITACS, $30,000 (PI)
2019 - 2019: Cognitive Dissonance in Financial Wellbeing: Using Statistical Machine Learning to Understand Perceived and Objective Financial Fitness, $36,000 (PI)
2019 - 2019: Feature selection for Deep Learning applied to the identification of impaired drivers, MITACS, $30,000 (PI)
2018 - 2019: Anomaly detection and simulation for unlabeled sensor data, MITACS, $45,000 (PI)
2018 - 2018: Robust estimation of treatment effects in high-dimensional heterogenous data with application to e-commerce, NSERC ENGAGE, $25,000 (PI)
2017 - 2019: Genome-wide diet-gene interaction analysis for risk of psychiatric comorbidity in inflammatory bowel disease, WCUC Collaborative Project Seed Funding, $20,000 (Co-PI, PI: Pingzhao Hu - U Manitoba)
2017 - 2018: Statistical Machine Learning Framework in Retention and Attrition Modelling, MITACS, $30,000 (PI)
2017 - 2017: Statistical machine learning applied to screening drivers with cognitive impairment, NSERC ENGAGE, $25,000 (PI)
2017 - 2017: New statistical machine learning methods applied to high dimensional sensory input data from chemistry, MITACS, $30,000 (PI)
2016 - 2019: Joint Analysis of Neuroimaging Data: High-dimensional Problems, Spatio-Temporal Models and Computation, CANSSI-CRT, $180,000 (Co-PI, Co-PI: Farouk Nathoo - U Victoria)
2016 - 2018: Using statistical methods to study the relationships between fat and weight changes during pregnancy and early postpartum, WCHRI, $50,000 (Co-PI, PI: Yan Yuan - U Alberta)
2015 - 2018: Analyzing real estate transaction and pricing data via statistical machine learning, NSERC- CRDPJ, $270,000 (Co-PI, PI: Di Niu - U Alberta)
2013 - 2018: Quantile Regression in Brain Imaging Data Analysis, NSERC-RGPIN, $75,000 (PI)
2012 - 2015: Start-up Funds, University of Alberta, $50,000 (PI)

Honors and Awards
2018: Representative to Future Leaders Program of Japan's STS Forum, NSERC
2018: Great Supervisor Award, University of Alberta
2017: Josephine Mitchell Mentoring Award, University of Alberta
2015: Research Fellow, SAMSI
2014: IMS New Researchers Conference Travel Award, IMS
2014: New Research Fellow, SAMSI
2013: IMS New Researchers Conference Travel Award, IMS
2013: SAMSI Neuroimaging Data Analysis Workshop Travel Award, SAMSI
2013: Discovery Grant of Early Career Researcher (ECR) Supplement, NSERC
2013: ENAR Workshop for Junior Researchers Travel Award, ENAR
2012: Developing Statistical Methods for NeuroImaging Workshop Scholarship, NSF, USA
2008: Student Travel Award, Statistical Society of Canada
2007: The Best Consultant of the Year 2007, University of Alberta
2007: Mary Louise Imrie Graduate Student Award, University of Alberta
2005: Josephine Mitchell Scholarship, University of Alberta
2004: Provost Doctoral Entrance Award, University of Alberta
2004: Eoin L. Whitney Scholarship, University of Alberta
2003: Pundit RD Sharma Memorial Graduate Student Award, University of Alberta
2000: GangSong Graduate Student Scholarship, Peking University
1998: Second Rank Major Scholarship, Beijing Normal University
1997: Third Rank Major Scholarship, Beijing Normal University
1996: Second Rank Major Scholarship, Beijing Normal University
1994: Second Rank in National High School Mathematical Olympics Contest in China