Chi-Kuang Yeh/葉啓光- PhD

Hello/你好! I am currently a postdoctoral scholar in the Department of Mathematics and Statistics at McGill University jointly with the Department of Statisitcs and Actuarial Science at the University of Waterloo, kindly sponsored by the Canadian Statistical Sciences Institute (CANSSI). I am also affiliated with Mila and UW’s Health Data Science Lab. I was originally from Hsinchu (新竹) and Taipei (台北), Taiwan, and I lived in BC, Canada, for 12 years.
My office is: Room 1216 on the top floor in Burnside Hall.
Note: I am on the 2024-2025 academic job market! Besides, feel free to shoot me an email if you are interested in my work! Happy to chat about them. :)

Teaching:

Direct study course
2024 Fall: NOT teaching this term.
2024 Winter: STAT 230 – Introduction to Probability, along with Erik Hintz, Jeffery Negrea and Justin Ko.

Computing: For those who want to use the MFCF server at UWaterloo, you may find the guidiance below useful. Feel free to contact me if you have any questions.

Guideline to run R on MFCF server.

Reserach Interests:

I possess a wide range of interests, but for now, my research is centred around:

Functional data analysis.
Statistical machine learning and high-dimensional statistical inference.
Dependence modeling.
Optimal design of experiment.
Applications include drug development, toxicology, neuroscience, to only name a few.

Publications

2025

Positive and unlabeled data: model, estimation, inference, and classification,

Journal of the American Statistical Association. [code] [link] [arXiv] [ResearchGate] Siyan Liu, Chi-Kuang Yeh, Xin Zhang, Qinglong Tian & Pengfei Li

2024

FTSgof: White noise and goodness-of-fit tests for functional time series in R,

Preprint. Mihyun Kim, Gregory Rice, Yuqian Zhao & Chi-Kuang Yeh
CVXSADes: a stochastic algorithm for constructing optimal exact regression designs with single or multiple objectives,

Preprint. [code] [arXiv] [ResearchGate] Chi-Kuang Yeh & Julie Zhou

2023

Variable selection in multivariate functional linear regression,

Statistics in Bioscience. [link] Chi-Kuang Yeh & Peijun Sang
Functional spherical autocorrelation: a robust estimate of the autocorrelation of a functional time series,

Electronic Journal of Statistics, 17, 650–687. [code] [link] [arXiv] [ResearchGate] Chi-Kuang Yeh, Gregory Rice & Joel A. Dubin

2022

Evaluating real-time probabilistic forecasts with application to National Basketball Association outcome prediction,

The American Statistician, 76, 214–223. [code] [link] [arXiv] [ResearchGate] Chi-Kuang Yeh, Gregory Rice & Joel A. Dubin

2021

Properties of optimal regression designs under the second-order least squares estimator,

Statistical Papers, 62, 75–92. [code] [link] Chi-Kuang Yeh & Julie Zhou

Theses

2023

Methods in functional data analysis: forecast evaluation, robust serial dependence measures, and a spatial factor copula model,

Ph.D. Thesis, University of Waterloo. [link]

2018

Optimal regression design under second-order least squares estimator: theory, algorithm and applications,

Master’s Thesis, University of Victoria. [link]

Softwares

FTSgof

A R package for white noise and goodness-of-fit tests for functional time series. [GitHub] [CRAN] Mihyun Kim, Chi-Kuang Yeh, Yuqian Zhao & Gregory Rice
evalRTPF

A R package to Evaluating the probabilistic forecasts between competitive forecasters. [GitHub] Chi-Kuang Yeh, Gregory Rice & Joel Dubin
optDesign

A MATLAB toolbox to compute optimal regression design. [GitHub] Chi-Kuang Yeh & Julie Zhou
SLSEdesign

A R package for computing optimal regression designs under the second-order least-squares estimator. [GitHub] [CRAN] Chi-Kuang Yeh, Julie Zhou & Jason Hou-Liu
yehUtil

A R package for knitting some RMarkdown reports and other usages. [GitHub] Chi-Kuang Yeh