World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
33
Citations
12571
World Ranking
2972
National Ranking
1195

Research.com Recognitions

  • 1998 - Fellow of the American Statistical Association (ASA)
  • 1961 - Fellow of the American Association for the Advancement of Science (AAAS)

Overview

Wei-Yin Loh is affiliated with the University of Wisconsin-Madison in the United States. Their research primarily spans the fields of Mathematics and Medicine, with a specialization in subfields such as Statistics and Probability, Organizational Behavior and Human Resource Management, Artificial Intelligence, Radiological and Ultrasound Technology, and Infectious Diseases.

Their research work covers several key topics including Advanced Statistical Methods and Models, Statistical Methods and Inference, Statistical Methods and Bayesian Inference, Statistical and Computational Modeling, Job Satisfaction and Organizational Behavior, Occupational Health and Safety Research, and COVID-19 Clinical Research Studies.

Wei-Yin Loh has published in a number of venues, with frequent publications appearing in:

  • arXiv (Cornell University)
  • Journal of Data Science
  • Sustainability
  • Scientific Reports
  • PLOS Global Public Health

Recent papers authored or coauthored by Wei-Yin Loh include:

  • Variable Importance Scores, 2021, Journal of Data Science
  • Variable importance scores, 2021, arXiv (Cornell University)
  • A Machine-Learning Classification Tree Model of Perceived Organizational Performance in U.S. Federal Government Health Agencies, 2021, Sustainability
  • Machine learning models of tobacco susceptibility and current use among adolescents from 97 countries in the Global Youth Tobacco Survey, 2013-2017, 2021, PLOS Global Public Health
  • A machine learning analysis of correlates of mortality among patients hospitalized with COVID-19, 2023, Scientific Reports

Frequent collaborators include Peigen Zhou, Nayoung Kim, In Gu Kang, Barbara A. Bichelmeyer, and Timothy B. Baker.

Wei-Yin Loh has received recognition in the form of fellowships, including being named a Fellow of the American Statistical Association in 1998 and a Fellow of the American Association for the Advancement of Science in 1961.

Best Publications

  • Classification and regression trees

    Wei-Yin Loh

  • SPLIT SELECTION METHODS FOR CLASSIFICATION TREES

    Wei-Yin Loh;Yu-Shan Shih

  • A Comparison of Prediction Accuracy, Complexity, and Training Time of Thirty-Three Old and New Classification Algorithms

    Tjen-Sien Lim;Wei-Yin Loh;Yu-Shan Shih

  • Fifty Years of Classification and Regression Trees

    Wei-Yin Loh

  • REGRESSION TREES WITH UNBIASED VARIABLE SELECTION AND INTERACTION DETECTION

    Wei-Yin Loh

  • Classification trees with unbiased multiway splits

    Hyunjoong Kim;Wei Yin Loh

  • Tree-Structured Classification via Generalized Discriminant Analysis.

    Wei-Yin Loh;Nunta Vanichsetakul

  • A comparison of tests of equality of variances

    Tjen-Sien Lim;Wei-Yin Loh

  • Classification and Regression Tree Methods

    Wei‐Yin Loh

  • A regression tree approach to identifying subgroups with differential treatment effects

    Wei-Yin Loh;Xu He;Michael Man

  • Calibrating Confidence Coefficients

    Wei-Yin Loh

  • LOTUS: An Algorithm for Building Accurate and Comprehensible Logistic Regression Trees

    Kin-Yee Chan;Wei-Yin Loh

  • Gender, race, and education differences in abstinence rates among participants in two randomized smoking cessation trials

    Megan E. Piper;Jessica W. Cook;Tanya R. Schlam;Douglas E. Jorenby

  • IMPROVING THE PRECISION OF CLASSIFICATION TREES

    Wei-Yin Loh

  • Generalized regression trees

    Probal Chaudhuri;Wen-Da Lo;Wei-Yin Loh;Ching-Ching Yang

  • Classification Trees With Bivariate Linear Discriminant Node Models

    Hyunjoong Kim;Wei Yin Loh

  • Consistent Variable Selection in Linear Models

    Xiaodong Zheng;Wei-Yin Loh

  • Regression trees for longitudinal and multiresponse data

    Wei-Yin Loh;Wei Zheng

  • Nonparametric estimation of conditional quantiles using quantile regression trees

    Probal Chaudhuri;Wei-Yin Loh

  • Tree-structured proportional hazards regression modeling.

    Hongshik Ahn;Wei-Yin Loh

  • Implementing Clinical Research Using Factorial Designs: A Primer.

    Timothy B. Baker;Stevens S. Smith;Daniel M. Bolt;Wei Yin Loh

Frequent Co-Authors

Timothy B. Baker
Timothy B. Baker University of Wisconsin–Madison
Daniel M. Bolt
Daniel M. Bolt University of Wisconsin–Madison
Michael C. Fiore
Michael C. Fiore University of Wisconsin–Madison
Linda M. Collins
Linda M. Collins New York University
Robin J. Mermelstein
Robin J. Mermelstein University of Illinois at Chicago
Awad S. Hanna
Awad S. Hanna University of Wisconsin–Madison
Alan J. Wallcraft
Alan J. Wallcraft United States Naval Research Laboratory
Johannes Gehrke
Johannes Gehrke Microsoft (United States)
Harley E. Hurlburt
Harley E. Hurlburt United States Naval Research Laboratory
Julio Saez-Rodriguez
Julio Saez-Rodriguez Heidelberg University

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring online degrees related to Mathematics can open doors to diverse career opportunities, especially when considering flexible and affordable options. For those interested in advancing business acumen alongside mathematical skills, programs like the easiest mba program offer an accessible pathway. These degrees often balance rigorous content with practical applications, making them popular among working professionals.

Cost is another critical factor for students seeking further education. The cheapest dba online programs provide an economical option for those looking to specialize in database administration, complementing quantitative analytical abilities gained through mathematics.

Finance professionals with a mathematics background can explore cheap online masters in finance, which serve as a gateway to careers in financial analysis, risk management, and investment strategies. Programs highlighting cheap online masters in finance combine affordability with quality education.

For individuals seeking faster completion times, the fastest mba programs online provide an effective way to accelerate career growth without compromising on course quality. Such degrees allow for quick upskilling in leadership and strategic thinking, which can be valuable complements to a mathematical foundation.

Best Scientists Citing Wei-Yin Loh

Trending Scientists