World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
57
Citations
10615
World Ranking
703
National Ranking
351

Research.com Recognitions

  • 2008 - Fellow of the American Association for the Advancement of Science (AAAS)
  • 2005 - Fellow of the American Statistical Association (ASA)

Overview

Xuming He is affiliated with Washington University in St. Louis in the United States. Their research spans multiple domains within mathematics, with a primary focus on statistics and probability. They have contributed significantly to fields such as artificial intelligence, epidemiology, public health, environmental and occupational health, and environmental engineering.

The main areas of their scholarly work include statistical methods and inference, statistical methods in clinical trials, advanced causal inference techniques, traumatic brain injury research, Gaussian processes and Bayesian inference, Bayesian methods and mixture models, and soil moisture and remote sensing.

Recent published papers by Xuming He and closely related collaborators include:

  • Challenges and Opportunities in Statistics and Data Science: Ten Research Areas, 2020, Harvard Data Science Review
  • Inference on Selected Subgroups in Clinical Trials, 2020, Journal of the American Statistical Association
  • Concussion-Recovery Trajectories Among Tactical Athletes: Results From the CARE Consortium, 2020, Journal of Athletic Training
  • Analysis of Global and Local Optima of Regularized Quantile Regression in High Dimensions: A Subgradient Approach, 2022, Econometric Theory
  • Bayesian Joint-Quantile Regression, 2020, Computational Statistics

Frequent coauthors contributing to their body of work include Xinzhou Guo, Xihong Lin, Jingshen Wang, Kean Ming Tan, and Ruosha Li.

Xuming He has published multiple times in the following venues:

  • Journal of the American Statistical Association
  • Harvard Data Science Review
  • The Annals of Applied Statistics
  • arXiv (Cornell University)
  • Econometric Theory

The scientist has received recognition within the academic community including election as a Fellow of the American Association for the Advancement of Science (AAAS) in 2008 and as a Fellow of the American Statistical Association (ASA) in 2005.

Best Publications

  • Regression depth. Commentaries. Rejoinder

    P. J. Rousseeuw;M. Hubert;X. He;R. Koenker

  • Quantile Curves without Crossing

    Xuming He

  • Quantile regression methods for reference growth charts.

    Ying Wei;Anneli Pere;Roger Koenker;Xuming He

  • Handbook of quantile regression

    Roger Koenker;Victor Chernozhukov;Xuming He;Limin Peng

  • Estimation in a semiparametric model for longitudinal data with unspecified dependence structure

    Xuming He;Zhong‐Yi Zhu;Wing‐Kam Fung

  • Quantile-adaptive model-free variable screening for high-dimensional heterogeneous data

    Xuming He;Lan Wang;Hyokyoung Grace Hong

  • Bayesian variable selection with shrinking and diffusing priors

    Naveen Naidu Narisetty;Xuming He

  • A general bahadur representation of M-estimators and its application to linear regression with nonstochastic designs

    Xuming He;Qi-Man Shao

  • Non-parametric quantification of protein lysate arrays

    Jianhua Hu;Xuming He;Keith A. Baggerly;Kevin R. Coombes

  • Practical Confidence Intervals for Regression Quantiles

    Masha Kocherginsky;Xuming He;Yunming Mu

  • On Parameters of Increasing Dimensions

    Xuming He;Qi-Man Shao

  • Wild bootstrap for quantile regression

    Xingdong Feng;Xuming He;Jianhua Hu

  • Markov Chain Marginal Bootstrap

    Xuming He;Feifang Hu

  • Bivariate Tensor-Product B-Splines in a Partly Linear Model

    Xuming He;Peide Shi

  • Convergence rate of b-spline estimators of nonparametric conditional quantile functions ∗

    Xuming He;Peide Shi

  • Monotone B-Spline Smoothing

    Xuming He;Peide Shi

  • Robust estimation in generalized partial linear models for clustered data

    Xuming He;Wing K Fung;Zhongyi Zhu

  • A Lack-of-Fit Test for Quantile Regression

    Xuming He;Li Xing Zhu;Li Xing Zhu

  • Bayesian empirical likelihood for quantile regression

    Yunwen Yang;Xuming He

  • Conditional growth charts

    Ying Wei;Xuming He

  • COBS: qualitatively constrained smoothing via linear programming

    Xuming He;Xuming He;Pin Ng

Frequent Co-Authors

Stephen Portnoy
Stephen Portnoy University of Illinois at Urbana-Champaign
Roger Koenker
Roger Koenker University College London
Zhidong Bai
Zhidong Bai Northeast Normal University
Qi-Man Shao
Qi-Man Shao Chinese University of Hong Kong
Lixing Zhu
Lixing Zhu Beijing Normal University
Raymond J. Carroll
Raymond J. Carroll Texas A&M University
Feifang Hu
Feifang Hu George Washington University
Mia Hubert
Mia Hubert KU Leuven
David Ruppert
David Ruppert Cornell University
Kevin R. Coombes
Kevin R. Coombes The Ohio State University

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