Linglong Kong, PhD
Contact
Professor, Canada Research Chair in Statistical Learning, and Canada CIFAR AI Chair, Faculty of Science - Mathematics & Statistical Sciences
- lkong@ualberta.ca
Overview
Research
Research Areas
Functional and Neuroimaging data analysis, Statistical machine learning, Robust statistics and quantile regression, Trustworthy Machine learning, and AI in smart health.
Courses
STAT 562 - Discrete Data Analysis
Sampling models and methods of inference for discrete data. Maximum likelihood estimation for complete contingency tables, measures of association and agreement. Goodness-of-fit. Incomplete tables. Analysis of square tables; symmetry and marginal homogeneity. Model selection and closeness of fit; practical aspects. Chi-square tests for categorical data from complex surveys. Prerequisite: STAT 372 or 471.
STAT 664 - Advanced Statistical Inference
Modern methods of statistical inference. Various versions of likelihood: conditional, marginal, integrated, profile, partial, empirical. Estimating equations. Semi-parametric models. Foundational issues. Prerequisites: STAT 512 and 566.
Featured Publications
Scalable inference in functional linear regression with streaming data
Xie, J., Shi, E., Sang, P., Shang, Z., Jiang, B. and Kong. L.
Annals of Statistics. 2025 December;
Adaptive Selection for False Discovery Rate Control Leveraging Symmetry
Wang, K., Che, Y., Han, Y., Xu, W., and Kong, L.
Journal of the American Statistical Association. 2025 June;
Comment on "Measuring Housing Vitality from Multi-source Big Data and Machine Learning"
Tu, W., Jiang, B., and Kong, L.
Journal of the American Statistical Association. 2022 October; 117 (539):1060-1062
High-dimensional spatial quantile function-on-scalar regression
Z Zhang, X Wang, L Kong, H Zhu
Journal of the American Statistical Association. 2022 July; 117 (539):1563-1578
A General Framework for Quantile Estimation with Incomplete Data
Han, P., Kong, L., Zhao, J., and Zhou, X.
Journal of Royal Statistical Society: Series B. 2019 October; 81 (2):305-333
Model-Robust Designs for Quantile Regression
Kong, L. and Wiens, D.
Journal of the American Statistical Association. 2015 January; 110 (507):233-245
Multivariate Varying Coefficient Models for Functional Responses
Zhu, H., Li, R., and Kong, L.
Annals of Statistics. 2014 June; 40 (5):2634-2666
Spatially Varying Coefficient Model for Neuroimaging Data with Jump Discontinuities
Zhu, H., Fan, J., and Kong, L.
Journal of the American Statistical Association. 2012 August; 109 (507):1084-1098
Discussion of "Multivariate Quantiles and Multiple- Output Regression Quantiles: From L1 Optimization to Halfspace Depth"
Kong, L. and Mizera, I.
Annals of Statistics. 2010 November; 38 (2):685-693