Faculty

Institution

Unit

Venue

Yang Ning

Associate Professor of Statistics and Data Science

Cornell University

Affiliations

College of Computing and Information Science

Department of Statistics and Data Science

Yang Ning is currently serving as a College Of Computing And Information Science Associate Professor of Statistics and Data Science at Cornell University.

Honors

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Experiences

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Education

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Yang Ning

Cornell University

Associate Professor of Statistics and Data Science

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statistics statistical methodology statistical inference applied statistics statistical models computational statistics high-dimensional statistics biostatistics high-dimensional method data science estimation statistic semi-nonparametric estimation estimation theory latent modeling applied mathematics machine learning research parameter estimation statistical hypothesis test graphical models medical statistics model selection statistical genetics inference bayesian analysis mixture distribution treatment effects average treatment effect mathematical optimization biomedical informatics mixture analysis latent variable models unsupervised machine learning test statistics digital medicine multivariate analysis statistical foundation graph analysis causal models variable clustering policy modeling molecular diagnostics health information science matrix factorization supervised learning statistical learning theory semi-supervised learning regression analysis sampling (statistics) data heterogeneity confidence regions high dimensions statistical optimization high dimensional parameters semiparametric model pseudolikelihood ratio convergence rate concentration inequality gaussian copula distribution cancer discovery heredity statistical software scientific data approximate reasoning knowledge discovery density estimation distributed learning distributed data analytics rare event estimation robust statistics meta-analysis matching technique bootstrap resampling general theory general theorems mixed data surrogate likelihood approach machine learning

Video Presentations

Notable Scholarly Works

Notable Federal Grants

Collaborators

Disc 2 O-Hd: Distributed Causal Inference With Covariates Shift for Analyzing Real-World High-Dimensional Data.. PubMed (2025)

Jiayi TongJie HuGeorge HripcsakYang NingYong Chen

statistical methodologyhealth datahealth informaticsbiomedical informaticscovariate shiftdata heterogeneitydigital medicinehealth information scienceclaims datadata scienceclinical dataapplied statisticsaverage treatment effectstatistical inferencestatisticshigh-dimensional statistics

Optimal Variable Clustering for High-Dimensional Matrix Valued Data. Information and Inference A Journal of the IMA (2025)

Inbeom LeeSiyi DengYang Ning

statistical methodologycluster separationweighted covariance matrixclusteringoptimal weightmachine learningdimensionality reductionunsupervised machine learningdata miningcomputational statisticsdata sciencemachine learning researchhigh-dimensional methodstatistical inferencestatisticshigh-dimensional statistics

Communication‐Efficient Distributed Estimation of Causal Effects With High‐Dimensional Data. Stat (2024)

Xiaohan WangJiayi TongSida PengYong ChenYang Ning

causal inferencestatistical methodologysample sizecausal modelsestimation statisticcommunication‐efficient distributed estimationcomputational statisticsdata scienceaverage treatment effectapplied statisticstreatment effectsstatistical inferencestatistical modelsstatisticshigh-dimensional statistics

Inference With Non-Differentiable Surrogate Loss in a General High-Dimensional Classification Framework. arXiv (Cornell University) (2024)

Liang, MuxuanNing, YangSmith, Maureen AZhao, Ying-Qi

mathematical optimizationnon-differentiable surrogate losssurrogate loss functionmachine learningclassification methodmachine learning researchsurrogate lossdata sciencekernel methodsapplied statisticshigh-dimensional methodstatistical inferencestatisticshigh-dimensional statistics

Discussion of ‘Statistical Inference for Streamed Longitudinal Data’. Biometrika (2023)

Yang NingJingyi Duan

biostatisticsstatistical methodologycohort studiesnew york 14853medical statisticslongitudinal studiesscientific dataapplied statisticsstatistical inferencestreamed longitudinal datastatistics'statistical inference

Inference in High-Dimensional Multivariate Response Regression With Hidden Variables. Journal of the American Statistical Association (2023)

Xin BingWei ChengHuijie FengYang Ning

biostatisticsstatistical methodologyestimation statistichidden variableshidden effectmultivariate analysisregression coefficient matrixcomputational statisticsregression analysisapplied statisticshigh-dimensional methodstatistical inferencestatisticshigh-dimensional statistics

Optimal and Safe Estimation for High-Dimensional Semi-Supervised Learning. Journal of the American Statistical Association (2023)

Siyi DengYang NingJiwei ZhaoHeping Zhang

statistical methodologysupervised estimatorssafe estimationhigh-dimensional semi-supervised learningstatistical learning theorysupervised learningsemi-supervised learningmachine learningmachine learning researchcomputational statisticsdata scienceapplied statisticshigh-dimensional methodstatistical inferencestatisticshigh-dimensional statistics

Sparse Confidence Sets for Normal Mean Models. Information and Inference A Journal of the IMA (2023)

Yang NingGuang Cheng

sparse confidencestatistical methodologysparse confidence setssparse representationscomputational statisticsapplied statisticshigh-dimensional methodstatistical inferencecoverage probabilityapplied mathematicsstatisticshigh-dimensional statistics

Test of Significance for High-Dimensional Thresholds With Application to Individualized Minimal Clinically Important Difference. Journal of the American Statistical Association (2023)

Huijie FengJingyi DuanYang NingJiwei Zhao

statistical hypothesis testbiostatisticsstatistical methodologyepidemiologybiomedical informaticsoptimal bandwidthestimation statisticmedical statisticsindividualized linear thresholdsurgery procedurecomputational statisticsstatistical foundationapplied statisticshigh-dimensional methodstatistical inferencestatisticshigh-dimensional statistics

Adaptive Estimation in Multivariate Response Regression With Hidden Variables. The Annals of Statistics (2022)

Xin BingYang NingYaosheng Xu

statistical methodologyparameter estimationestimation statisticestimation theoryassociation analysiscomputational statisticsdata scienceregression analysisapplied statisticsmultivariate response regressionresponse vectorstatistical inferencestatisticsstatistical models

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Yang Ning

Associate Professor of Statistics and Data Science

Cornell University

Affiliations

College of Computing and Information Science

Department of Statistics and Data Science

Yang Ning is currently serving as a College Of Computing And Information Science Associate Professor of Statistics and Data Science at Cornell University.

Honors

Create free account to unlock more features

Experiences

Create free account to unlock more features

Education

Create free account to unlock more features

Yang Ning

Cornell University

Associate Professor of Statistics and Data Science

You can click a keyword to filter the displayed items

Video Presentations

Notable Scholarly Works

Notable Federal Grants

Collaborators

Disc 2 O-Hd: Distributed Causal Inference With Covariates Shift for Analyzing Real-World High-Dimensional Data.. PubMed (2025)

Jiayi TongJie HuGeorge HripcsakYang NingYong Chen

Optimal Variable Clustering for High-Dimensional Matrix Valued Data. Information and Inference A Journal of the IMA (2025)

Inbeom LeeSiyi DengYang Ning

Communication‐Efficient Distributed Estimation of Causal Effects With High‐Dimensional Data. Stat (2024)

Xiaohan WangJiayi TongSida PengYong ChenYang Ning

Inference With Non-Differentiable Surrogate Loss in a General High-Dimensional Classification Framework. arXiv (Cornell University) (2024)

Liang, MuxuanNing, YangSmith, Maureen AZhao, Ying-Qi

Discussion of ‘Statistical Inference for Streamed Longitudinal Data’. Biometrika (2023)

Yang NingJingyi Duan

Inference in High-Dimensional Multivariate Response Regression With Hidden Variables. Journal of the American Statistical Association (2023)

Xin BingWei ChengHuijie FengYang Ning

Optimal and Safe Estimation for High-Dimensional Semi-Supervised Learning. Journal of the American Statistical Association (2023)

Siyi DengYang NingJiwei ZhaoHeping Zhang

Sparse Confidence Sets for Normal Mean Models. Information and Inference A Journal of the IMA (2023)

Yang NingGuang Cheng

Test of Significance for High-Dimensional Thresholds With Application to Individualized Minimal Clinically Important Difference. Journal of the American Statistical Association (2023)

Huijie FengJingyi DuanYang NingJiwei Zhao

Adaptive Estimation in Multivariate Response Regression With Hidden Variables. The Annals of Statistics (2022)

Xin BingYang NingYaosheng Xu

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latent space estimation

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