Faculty

Institution

Unit

Venue

Shujie Ma

Professor; Graduate Advisor

University of California, Riverside

Affiliations

College of Natural & Agricultural Sciences (CNAS)

Statistics

Shujie Ma is currently serving as a College Of Natural & Agricultural Sciences (Cnas) Professor; Graduate Advisor at University of California, Riverside.

Honors

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Experiences

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Education

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Shujie Ma

University of California, Riverside

Professor; Graduate Advisor

You can click a keyword to filter the displayed items

statistics applied statistics statistical methodology biostatistics statistical inference statistical models data science applied mathematics causal inference computational statistics model selection estimation statistic econometrics machine learning research treatment effects mathematical optimization spline (mathematics) biomedical informatics semi-nonparametric estimation estimation theory clustering economic modelling statistical theory information fusion bibliometrics multivariate analysis treatment planning curve fitting fusion penalty high-dimensional covariates treatment development parameter estimation community mining community structure community discovery statistical science medical statistics dimensionality reduction multilevel fusion concave fusion policy modeling economic analysis scientific data statistical mechanics neuroscience of aging knowledge discovery global networks social simulation scientific computing experimental analysis regression analysis kernel methods econometric models econometric methods financial econometrics robust optimization measurement theory meta-analysis meta data random graphs probabilistic graph theory robust statistics low-rank approximation simultaneous confidence band sparse longitudinal regression quantile partial correlation index coefficient models spline regression spline-backfitted kernel unknown number profile optimization gene-environment interaction non-linear look semiparametric modeling simultaneous variable selection functional single-index models longitudinal data analysis machine learning precision medicine network analysis subgroup analysis

Notable Scholarly Works

Notable Federal Grants

Collaborators

A Machine Learning Approach to Predicting Dyspnea With Noninvasive Biomarkers. bioRxiv (Cold Spring Harbor Laboratory) (2025)

predictive analyticsdata-driven predictionbiomedical informaticsbiomarkersbiomedical data sciencediagnosismachine learning approachprediction modellingbiostatisticsdisease classificationmachine learning researchrespiratory medicinedata sciencedigital medicinecomputational medicinemachine learning

Neural Network for Correlated Survival Outcomes Using Frailty Model. Journal of Data Science (2025)

neural networksurvival analysisdeath studiesbiostatisticsprognostic evaluationneural network (machine learning)frailty

Addressing Disparities Between Physician Rated and Self-Reported Dyspnea Using Machine Learning. Physiology (2024)

internal medicineoutcomes researchclinical decision support systemsemergency medicineintelligent diagnosticshealth informaticshealth systemsai healthcaredigital medicinedigital healthhealth technologyhealth scienceshealth policy

A Selective Overview of Fusion Penalized Learning in Latent Subgroup Analysis for Precision Medicine. ICSA book series in statistics (2024)

biomedical data sciencestatistical learning theorystatistical inferencemachine learning researchdata sciencefusion learningdigital medicinebiomedical data analysislatent subgroup analysismachine learningselective overviewbiostatisticsstatistical methodologyfusion penalized learningmodel selectionbiomedical informaticsdimensionality reductionpersonalized medicinestatisticsinformation fusion

Health Care Provider Clustering Using Fusion Penalty in Quasi‐Likelihood. Biometrical Journal (2024)

Lili LiuKevin HeDi WangShujie MaAnnie QuYihui LuanJ. Philip MillerYizhe SongLei Liu

health care providerhealth carehealth care analyticsfusion penaltybiostatisticsstatisticsmachine learning researchbiometricsclusteringhealth sciencesinformation fusion

Non-Invasive Prediction of Dyspnea Severity Using Machine Learning. (2024)

predictive analyticsdata-driven predictionbiomedical informaticsnon-invasive predictiondiagnosisintelligent diagnosticshealth informaticsprediction modellingmachine learning researchrespiratory medicinedata sciencedigital medicinemachine learning

Optimal Conditional Quantile Prediction via Model Averaging of Partially Linear Additive Models. Statistica Sinica (2024)

predictive analyticsmathematical optimizationestimation theorysemi-nonparametric estimationmodel averagingstatistical inferencebayesian analysisstatisticsstatistical methodologydata sciencemodel selectionstatistical models

Causal Inference of General Treatment Effects Using Neural Networks With a Diverging Number of Confounders. Journal of Econometrics (2023)

Xiaohong ChenYing LiuShujie MaZheng Zhang

neural networkseconometricsgeneral treatment effectscausal inferencestatistics

Healthcare Center Clustering for Cox's Proportional Hazards Model by Fusion Penalty. Statistics in Medicine (2023)

Lili LiuKevin HeDi WangShujie MaAnnie QuLu LinJ. Philip MillerLei Liu

public healthevidence-based medicinemedical statisticssamplingproportional hazards modelepidemiologyapplied statisticsstatistical theoryhealthcare centerfusion penaltystatistical inferencestatisticsstatistical methodologyclustering

Sensitivity Analysis for Causal Decomposition Analysis: Assessing Robustness Toward Omitted Variable Bias. Journal of Causal Inference (2023)

Soojin ParkSuyeon KangChioun LeeShujie Ma

causal inferencestatisticscausal decomposition analysissensitivity analysis

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Shujie Ma

Professor; Graduate Advisor

University of California, Riverside

Affiliations

College of Natural & Agricultural Sciences (CNAS)

Statistics

Shujie Ma is currently serving as a College Of Natural & Agricultural Sciences (Cnas) Professor; Graduate Advisor at University of California, Riverside.

Honors

Create free account to unlock more features

Experiences

Create free account to unlock more features

Education

Create free account to unlock more features

Shujie Ma

University of California, Riverside

Professor; Graduate Advisor

You can click a keyword to filter the displayed items

Notable Scholarly Works

Notable Federal Grants

Collaborators

A Machine Learning Approach to Predicting Dyspnea With Noninvasive Biomarkers. bioRxiv (Cold Spring Harbor Laboratory) (2025)

Neural Network for Correlated Survival Outcomes Using Frailty Model. Journal of Data Science (2025)

neural networksurvival analysisdeath studiesbiostatisticsprognostic evaluationneural network (machine learning)frailty

Addressing Disparities Between Physician Rated and Self-Reported Dyspnea Using Machine Learning. Physiology (2024)

A Selective Overview of Fusion Penalized Learning in Latent Subgroup Analysis for Precision Medicine. ICSA book series in statistics (2024)

Health Care Provider Clustering Using Fusion Penalty in Quasi‐Likelihood. Biometrical Journal (2024)

Lili LiuKevin HeDi WangShujie MaAnnie QuYihui LuanJ. Philip MillerYizhe SongLei Liu

health care providerhealth carehealth care analyticsfusion penaltybiostatisticsstatisticsmachine learning researchbiometricsclusteringhealth sciencesinformation fusion

Non-Invasive Prediction of Dyspnea Severity Using Machine Learning. (2024)

Optimal Conditional Quantile Prediction via Model Averaging of Partially Linear Additive Models. Statistica Sinica (2024)

Causal Inference of General Treatment Effects Using Neural Networks With a Diverging Number of Confounders. Journal of Econometrics (2023)

Xiaohong ChenYing LiuShujie MaZheng Zhang

neural networkseconometricsgeneral treatment effectscausal inferencestatistics

Healthcare Center Clustering for Cox's Proportional Hazards Model by Fusion Penalty. Statistics in Medicine (2023)

Lili LiuKevin HeDi WangShujie MaAnnie QuLu LinJ. Philip MillerLei Liu

Sensitivity Analysis for Causal Decomposition Analysis: Assessing Robustness Toward Omitted Variable Bias. Journal of Causal Inference (2023)

Soojin ParkSuyeon KangChioun LeeShujie Ma

causal inferencestatisticscausal decomposition analysissensitivity analysis

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Subir Ghosh

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generalized linear

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bayesian analysis

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