World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
40
Citations
7428
World Ranking
2033
National Ranking
859

Research.com Recognitions

  • 2013 - Fellow of the American Statistical Association (ASA)

Overview

Hua Liang is affiliated with George Washington University in the United States, contributing extensively to the field of Mathematics, with a focus on subfields such as Statistics and Probability, Artificial Intelligence, Management Science and Operations Research, and Genetics.

Their research encompasses several main topics including:

  • Statistical Methods and Inference
  • Statistical Methods and Bayesian Inference
  • Advanced Statistical Methods and Models
  • Statistical Methods in Clinical Trials
  • Bayesian Methods and Mixture Models
  • Probabilistic and Robust Engineering Design
  • Control Systems and Identification

Hua Liang has authored numerous papers, with notable recent publications including:

  • "SARS-CoV-2-specific T cells are rapidly expanded for therapeutic use and target conserved regions of the membrane protein," 2020, Blood
  • "Outcome of donor-derived TAA-T cell therapy in patients with high-risk or relapsed acute leukemia post allogeneic BMT," 2022, Blood Advances
  • "Simultaneous confidence intervals for ratios of means of zero-inflated log-normal populations," 2021, Journal of Statistical Computation and Simulation
  • "The impact of pre-existing HLA and red blood cell antibodies on transfusion support and engraftment in sickle cell disease after nonmyeloablative hematopoietic stem cell transplantation from HLA-matched sibling donors: A prospective, single-center, observational study," 2020, EClinicalMedicine
  • "Estimation and inference in partially functional linear regression with multiple functional covariates," 2020, Journal of Statistical Planning and Inference

Their work has appeared frequently in several publication venues, including:

  • Statistica Sinica
  • arXiv (Cornell University)
  • Blood
  • Statistics and Computing
  • SSRN Electronic Journal

Frequent collaborators in Hua Liang's research include:

  • Xinmin Li
  • Xinyu Zhang
  • Feifei Chen
  • Dalei Yu
  • Shunyao Wu

In recognition of their work in the field of statistics, Hua Liang was named a Fellow of the American Statistical Association in 2013.

Best Publications

  • Partially Linear Models

    Wolfgang Hardle;Hua LIang;Jiti Gao

  • Estimation in a semiparametric partially linear errors-in-variables model

    Hua Liang;Wolfgang Härdle;Raymond J. Carroll

  • Variable Selection in Semiparametric Regression Modeling.

    Runze Li;Hua Liang

  • Parameter Estimation for Differential Equation Models Using a Framework of Measurement Error in Regression Models

    Hua Liang;Hulin Wu

  • ESTIMATION AND TESTING FOR PARTIALLY LINEAR SINGLE-INDEX MODELS.

    Hua Liang;Xiang Liu;Runze Li;Chih Ling Tsai

  • Variable Selection for Partially Linear Models with Measurement Errors.

    Hua Liang;Runze Li

  • Optimal Weight Choice for Frequentist Model Average Estimators

    Hua Liang;Guohua Zou;Alan T. K. Wan;Xinyu Zhang

  • Safety and immunogenicity of a baculovirus-expressed hemagglutinin influenza vaccine: a randomized controlled trial.

    John J. Treanor;Gilbert M. Schiff;Frederick G. Hayden;Rebecca C. Brady

  • Focused information criterion and model averaging for generalized additive partial linear models

    Xinyu Zhang;Hua Liang

  • Optimal Model Averaging Estimation for Generalized Linear Models and Generalized Linear Mixed-Effects Models

    Xinyu Zhang;Dalei Yu;Guohua Zou;Hua Liang

  • Partially linear models with missing response variables and error-prone covariates

    Hua Liang;Suojin Wang;Raymond J. Carroll

  • A note on conditional AIC for linear mixed-effects models

    Hua Liang;Hulin Wu;Guohua Zou

  • The relationship between virologic and immunologic responses in AIDS clinical research using mixed-effects varying-coefficient models with measurement error.

    Hua Liang;Hulin Wu;Raymond J. Carroll

  • Estimation in Partially Linear Models With Missing Covariates

    Hua Liang;Suojin Wang;James M Robins;Raymond J Carroll

  • Statistical inference for semiparametric varying-coefficient partially linear models with error-prone linear covariates

    Yong Zhou;Hua Liang

  • Quantile Regression Estimates for a Class of Linear and Partially Linear Errors-in-Variables Models

    Xuming He;Hua Liang

  • Estimation and Variable Selection for Semiparametric Additive Partial Linear Models (SS-09-140)

    Xiang Liu;Li Wang;Hua Liang

  • ESTIMATION AND VARIABLE SELECTION FOR GENERALIZED ADDITIVE PARTIAL LINEAR MODELS

    Li Wang;Xiang Liu;Hua Liang;Raymond J. Carroll

  • Additive Partial Linear Models with Measurement Errors

    Hua Liang;Sally W. Thurston;David Ruppert;Tatiyana Apanasovich

  • Sparse Additive Ordinary Differential Equations for Dynamic Gene Regulatory Network Modeling

    Hulin Wu;Tao Lu;Hongqi Xue;Hua Liang

  • Estimation and variable selection for generalized additive partial linear models

    Li Wang;Xiang Liu;Hua Liang;Raymond J. Carroll

Frequent Co-Authors

Hulin Wu
Hulin Wu The University of Texas Health Science Center at Houston
Wolfgang Karl Härdle
Wolfgang Karl Härdle Humboldt-Universität zu Berlin
Raymond J. Carroll
Raymond J. Carroll Texas A&M University
David Ruppert
David Ruppert Cornell University
Jiti Gao
Jiti Gao Monash University
Lixing Zhu
Lixing Zhu Beijing Normal University
Robert J. Wilkinson
Robert J. Wilkinson The Francis Crick Institute
Runze Li
Runze Li Pennsylvania State University
John J. Treanor
John J. Treanor University of Rochester Medical Center
Mary Carrington
Mary Carrington Ragon Institute of MGH, MIT and Harvard

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