Publications

A curated bibliography of Ruoqing Zhu’s research.

Research in statistical learning, sequential decisions, and biomedical applications.

Showing 70 publications

Preprints

2026

Rectified Fisher-Bingham Model for Compositional Data with Zeros

Han, E., Perez-Tamayo, M., Holscher, H. D., Zhu, R.

Preprint2026

Method & Theory Nutrition Science

Vector-Valued Distributional Reinforcement Learning Policy Evaluation: A Hilbert Space Embedding Approach

Mohammadi, M., Zheng, Q., Zhu, R.

Preprint2026

Method & Theory Reinforcement Learning

2024

Consistent Order Determination of Markov Decision Process

Ye, C., Zhu, L., Zhu, R.

Preprint2024

Method & Theory Reinforcement Learning

2023

Distributional shift-aware off-policy interval estimation: A unified error quantification framework

Zhou, W., Li, Y., Zhu, R., Qu, A.

Preprint2023

Method & Theory Reinforcement Learning

2022

Confidence Band Estimation for Survival Random Forests

Formentini, S. E., Liang, W., Zhu, R.

Preprint2022

Method & Theory Random Forests Survival Analysis

Published work

2026

Detecting Gender Stereotype Biases Against Women Entrepreneurs in Large Language Models

Cao, X., Li, H., Xu, Q., Zhu, R.

Journal of Business Ethics 207(4), 875-8972026

Collaborative Others

From Problem to Method: Designing Multiview Sequential Canonical Covariance Analysis for Online Word-of-Mouth Dynamics

Cao, X., Folta, T., Li, H., Zhu, R.

In SAGE Research Methods: Doing Research Online. SAGE Publications Ltd2026

Collaborative Others

Interpretability of an FDA-authorized AI/ML sepsis diagnostic tool improved by SHAP values

Watson, G. L., Staples, G., Carver, R., Bhargava, A., López-Espina, C., Schmalz, L., Ali, F., Antkowiak, P. S., Azad, S., Berghea, R., Chawla, L., Crisp, M., Dagan, A., Davila, F., Davila, H., DeMarco, C., Doodlesack, A., Espinosa, A., Evans, N. S., Ezekiel, C., Friederich, A., Gosai, F., Halalau, A., Iyer, K., Kravitz, M. S., Kurtzman, N., Lee, J. H., Maddens, N., Malkani, R., Mayer, S., Oke, V., Palagiri, A. V., Patel, R., Raghavakurup, L., Raouf, S., Reseland, E., Sadaka, F., Sarma, D., Smith, S., Shvilkina, T., Sims, M. D., Singh, S., Stenson, B. A., Syed, A., Tafa, M., Thomas, K., Zhao, S. D., Zhu, R., Bashir, R., Reddy, Jr., B., Shapiro, N. I.

JAMIA Open 9(1), ooag0202026

Collaborative Sepsis

Kernel Mean Embedding Deviation Subspace for Unsupervised Learning with Heterogeneous Data

Yu, L., Zhu, L., Zhu, R., Zhu, X.

Journal of Machine Learning Research 27(97), 1-522026

Method & Theory Dimension Reduction

Machine Learning and Artificial Intelligence in Nutrition Research: Analytical Methods, Applications, and Key Considerations

Southey, N. L., Zhu, R., Holscher, H. D.

The Journal of Nutrition 156(6), 1015282026

Collaborative Nutrition Science

Reinforcement Learning with Continuous Actions Under Unmeasured Confounding

Li, Y., Han, E., Hu, Y., Zhou, W., Qi, Z., Cui, Y., Zhu, R.

Journal of the American Statistical Association 121(553), 209-2222026

Method & Theory Reinforcement Learning

The Sepsis ImmunoScore Predicts Sepsis, Mortality, and Deterioration Better than Clinical Scores and Widely Available Biomarkers

Watson, G. L., Updike, L. C., López-Espina, C. G., Bhargava, A., Schmalz, L. A., Khan, S., Urdiales, D. S., Sims, M. D., Palagiri, A. V., Haimovich, A. D., Dagan, A., Davis, B. P., White, K. C., Gurbel, P. A., Mayer, S. M., Syed, A., Zhao, S. D., Zhu, R., Bashir, R., Shapiro, N. I., Reddy, Jr., B.

Diagnostics 16(13), 19622026

Collaborative Sepsis

2025

Integrating Prior Knowledge from Genome-scale Metabolic Model with Metabolomics for Diet Assessment

Sarker, K., Zhu, R., Holscher, H. D., Zhai, C.

IEEE Transactions on Computational Biology and Bioinformatics 22(4), 1347-13572025

Collaborative Nutrition Science

Multiplexed cytokine profiling identifies diagnostic signatures for latent tuberculosis and reactivation risk stratification

Meserve, K., Chapman, C. A., Xu, M., Zhou, H., Robison, H. M., Hilgart, H. R., Arias-Sanchez, P. P., Pathakumari, B., Reddy, M. R., Daniel, K. A., Cox, T. M., Erskine, C. L., Marty, P. K., Vadiyala, M., Karnakoti, S., Van Keulen, V., Theel, E., Peikert, T., Bushell, C., Welge, M., Laniado-Laborin, R., Zhu, R., Escalante, P., Bailey, R. C.

PLOS ONE 20(4), e03166482025

Collaborative Disease Diagnostics and Treatment

Nasal and systemic immune responses correlate with viral shedding after influenza challenge in people with complex preexisting immunity

Walters, K.-A., Blatti, III, C. A., Zhu, R., Banbury, B., Giurgea, L. T., Bean, R., Han, E., Li, Y., Scherler, K., Sherry, J., Formentini, S., Zhou, W., Cervantes-Medina, A., Gouzoulis, M., Rosas, L. A., Han, A., Gatzke, L., Bushell, C., Sherry, N., Taubenberger, J. K., Memoli, M. J., Kash, J. C.

Science Translational Medicine 17(810), eadt14522025

Collaborative Influenza

Predicting Cognitive Outcome Through Nutrition and Health Markers Using Supervised Machine Learning

Verma, S., Holthaus, T. A., Martell, S., Holscher, H. D., Zhu, R., Khan, N. A.

The Journal of Nutrition 155(7), 2144-21532025

Collaborative Nutrition Science

Probabilistic exponential family inverse regression and its applications

Pang, D., Zhu, R., Zhao, H., Wang, T.

Biometrics 81(2), ujaf0652025

Method & Theory Dimension Reduction

Unraveling the Molecular Complexity of Myxomatous Mitral Valve Degeneration: Integrating Transcriptomic and miRNA Profiling Using Random Forests with Boruta Feature Selection

Hagler, M. A., Thalji, N., Russell, N. T., Welge, M. E., Zhu, R., Bushell, C., Berry, M., White, B. A., Matveyenko, A. V., Suri, R. M., Miller, J. D.

Journal of the Heart Valve Society 2(2), 137-1532025

Collaborative Random Forests

2024

Analyzing the online word of mouth dynamics: A novel approach

Cao, X., Folta, T. B., Li, H., Zhu, R.

Decision Support Systems 185, 1143062024

Collaborative Others

Cognitive Outcome Forecasting Using Supervised Machine Learning: A Multi-Factor Analysis With Anthropometrics, Demographics, Diet Indices, and Cardiovascular Markers

Verma, S., Holscher, H. D., Holthaus, T. A., Khan, N., Martell, S., Zhu, R.

Current Developments in Nutrition 8, 103216Conference abstract2024

Collaborative Nutrition Science

Dietary patterns among US food insecure cancer survivors and the risk of mortality: NHANES 1999-2018

Maino Vieytes, C. A., Zhu, R., Gany, F., Koester, B. D., Arthur, A. E.

Cancer Causes & Control 35(7), 1075-10882024

Collaborative Nutrition Science Survival Analysis

Estimating Optimal Infinite Horizon Dynamic Treatment Regimes via pT-Learning

Zhou, W., Zhu, R., Qu, A.

Journal of the American Statistical Association 119(545), 625-6382024

Method & Theory Personalized Medicine Reinforcement Learning

FDA-Authorized AI/ML Tool for Sepsis Prediction: Development and Validation

Bhargava, A., López-Espina, C., Schmalz, L., Khan, S., Watson, G. L., Urdiales, D., Updike, L., Kurtzman, N., Dagan, A., Doodlesack, A., Stenson, B. A., Sarma, D., Reseland, E., Lee, J. H., Kravitz, M. S., Antkowiak, P. S., Shvilkina, T., Espinosa, A., Halalau, A., Demarco, C., Davila, F., Davila, H., Sims, M., Maddens, N., Berghea, R., Smith, S., Palagiri, A. V., Ezekiel, C., Sadaka, F., Iyer, K., Crisp, M., Azad, S., Oke, V., Friederich, A., Syed, A., Gosai, F., Chawla, L., Evans, N., Thomas, K., Malkani, R., Patel, R., Mayer, S., Ali, F., Raghavakurup, L., Tafa, M., Singh, S., Raouf, S., Zhao, S. D., Zhu, R., Bashir, R., Reddy, Jr., B., Shapiro, N. I.

NEJM AI 1(12), AIoa24008672024

Collaborative Sepsis

Fecal metagenomics to identify biomarkers of food intake in healthy adults: Findings from randomized, controlled, nutrition trials

Shinn, L. M., Mansharamani, A., Baer, D. J., Novotny, J. A., Charron, C. S., Khan, N. A., Zhu, R., Holscher, H. D.

The Journal of Nutrition 154(1), 271-2832024

Collaborative Nutrition Science

On variance estimation of random forests with Infinite-order U-statistics

Xu, T., Zhu, R., Shao, X.

Electronic Journal of Statistics 18(1), 2135-22072024

Method & Theory Random Forests

Policy learning for individualized treatment regimes on infinite time horizon

Zhou, W., Li, Y., Zhu, R.

In Statistics in Precision Health: Theory, Methods and Applications, 65-100. Cham: Springer International Publishing. Editor: Yichuan Zhao2024

Method & Theory Personalized Medicine Reinforcement Learning

Prevalence, management, and comorbidities of adults with atrial fibrillation in the United States, 2019 to 2023

Oltman, C. G., Kim, T. P., Lee, J. W. Y., Lupu, J. D., Zhu, R., Moussa, I. D.

JACC: Advances 3(11), 1013302024

Collaborative Disease Diagnostics and Treatment

Prior-guided longitudinal metabolomic analysis

Sarker, K., Zhu, R., Holscher, H. D., Zhai, C.

In 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 351-3562024

Collaborative Nutrition Science

Random Forest Weighted Local Fréchet Regression with Random Objects

Qiu, R., Yu, Z., Zhu, R.

Journal of Machine Learning Research 25(107), 1-692024

Method & Theory Random Forests Survival Analysis

Stage-Aware Learning for Dynamic Treatments

Ye, H., Zhou, W., Zhu, R., Qu, A.

Journal of Machine Learning Research 25(408), 1-512024

Method & Theory Reinforcement Learning

2023

AI in Pharma for Personalized Sequential Decision-Making: Methods, Applications and Opportunities

Li, Y., Zhang, H., Anderson, K., Li, S., Zhu, R.

Biopharmaceutical Report 30(3), 14-262023

Method & Theory Personalized Medicine Reinforcement Learning

Augmenting nutritional metabolomics with a genome-scale metabolic model for assessment of diet intake

Sarker, K., Zhu, R., Holscher, H. D., Zhai, C.

In Proceedings of the 14th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics, 1-102023

Collaborative Nutrition Science

Calibrate and Debias Layer-wise Sampling for Graph Convolutional Networks

Chen, Y., Xu, T., Hakkani-Tur, D., Jin, D., Yang, Y., Zhu, R.

Transactions on Machine Learning Research2023

Method & Theory Others

Estimating Heterogeneous Treatment Effect on Multivariate Responses Using Random Forests

Guo, B., Holscher, H. D., Auvil, L. S., Welge, M. E., Bushell, C. B., Novotny, J. A., Baer, D. J., Burd, N. A., Khan, N. A., Zhu, R.

Statistics in Biosciences 15(3), 545-5612023

Method & Theory Personalized Medicine Random Forests

Estimating Heterogeneous Treatment Effects with Right-censored Data via Causal Survival Forests

Cui, Y., Kosorok, M. R., Sverdrup, E., Wager, S., Zhu, R.

Journal of the Royal Statistical Society Series B: Statistical Methodology 85(2), 179-2112023

Method & Theory Personalized Medicine Random Forests Survival Analysis

Quasi-optimal Reinforcement Learning with Continuous Actions

Li, Y., Zhou, W., Zhu, R.

In International Conference on Learning Representations2023

Method & Theory Reinforcement Learning

Random Forests for Survival Analysis and High-Dimensional Data

Zhu, R., Formentini, S. E., Cui, Y.

In Springer Handbook of Engineering Statistics, 831-847. London: Springer London. Editor: Hoang Pham2023

Method & Theory Random Forests Survival Analysis

2022

Consistency of survival tree and forest models: splitting bias and correction

Cui, Y., Zhu, R., Zhou, M., Kosorok, M.

Statistica Sinica 32(3), 1245-12672022

Method & Theory Random Forests Survival Analysis

Dermoscopic Image Classification with Neural Style Transfer

Li, Y., Zhu, R., Yeh, M., Qu, A.

Journal of Computational and Graphical Statistics 31(4), 1318-13312022

Method & Theory Disease Diagnostics and Treatment

Dimension Reduction Forests: Local Variable Importance using Structured Random Forests

Loyal, J. D., Zhu, R., Cui, Y., Zhang, X.

Journal of Computational and Graphical Statistics 31(4), 1104-11132022

Method & Theory Random Forests Dimension Reduction

Efficient gradient boosting for prognostic biomarker discovery

Li, K., Yao, S., Zhang, Z., Cao, B., Wilson, C. M., Kalos, D., Kuan, P. F., Zhu, R., Wang, X.

Bioinformatics 38(6), 1631-16382022

Method & Theory Disease Diagnostics and Treatment

Empirical dietary patterns associated with food insecurity in US cancer survivors: NHANES 1999-2018

Maino Vieytes, C. A., Zhu, R., Gany, F., Burton-Obanla, A., Arthur, A. E.

International Journal of Environmental Research and Public Health 19(21), 140622022

Collaborative Nutrition Science

Fecal Metabolites as Biomarkers for Predicting Food Intake By Healthy Adults

Shinn, L. M., Mansharamani, A., Baer, D. J., Novotny, J. A., Charron, C. S., Khan, N. A., Zhu, R., Holscher, H. D.

The Journal of Nutrition 152(12), 2956-29652022

Collaborative Nutrition Science

Optimizing Health Coaching for Patients With Type 2 Diabetes Using Machine Learning: Model Development and Validation Study

Di, S., Petch, J., Gerstein, H. C., Zhu, R., Sherifali, D.

JMIR Formative Research 6(9), e378382022

Collaborative Disease Diagnostics and Treatment

Population analysis of mortality risk: Predictive models from passive monitors using motion sensors for 100,000 UK Biobank participants

Zhou, H., Zhu, R., Ung, A., Schatz, B.

PLOS Digital Health 1(10), e00000452022

Collaborative Survival Analysis

2021

A Parsimonious Personalized Dose Finding Model via Dimension Reduction

Zhou, W., Zhu, R., Zeng, D.

Biometrika 108(3), 643-6592021

Method & Theory Personalized Medicine Dimension Reduction

Diagnostic and prognostic capabilities of a biomarker and EMR-based machine learning algorithm for sepsis

Taneja, I., Damhorst, G. L., Lopez-Espina, C., Zhao, S. D., Zhu, R., Khan, S., White, K., Kumar, J., Vincent, A., Yeh, L., Majdizadeh, S., Weir, W., Isbell, S., Skinner, J., Devanand, M., Azharuddin, S., Meenakshisundaram, R., Upadhyay, R., Syed, A., Bauman, T., Devito, J., Heinzmann, C., Podolej, G., Shen, L., Timilsina, S. S., Quinlan, L., Manafirasi, S., Valera, E., Reddy, Jr., B., Bashir, R.

Clinical and Translational Science 14(4), 1578-15892021

Collaborative Sepsis

Fecal bacteria as biomarkers for predicting food intake in healthy adults

Shinn, L. M., Li, Y., Mansharamani, A., Auvil, L. S., Welge, M. E., Bushell, C., Khan, N. A., Charron, C. S., Novotny, J. A., Baer, D. J., Zhu, R., Holscher, H. D.

The Journal of Nutrition 151(2), 423-4332021

Collaborative Nutrition Science

Lung epithelial and endothelial damage, loss of tissue repair, inhibition of fibrinolysis, and cellular senescence in fatal COVID-19

D'Agnillo, F., Walters, K.-A., Xiao, Y., Sheng, Z.-M., Scherler, K., Park, J., Gygli, S., Rosas, L. A., Sadtler, K., Kalish, H., Blatti, III, C. A., Zhu, R., Gatzke, L., Bushell, C., Memoli, M. J., O'Day, S. J., Fischer, T. D., Hammond, T. C., Lee, R. C., Cash, J. C., Powers, M. E., O'Keefe, G. E., Butnor, K. J., Rapkiewicz, A. V., Travis, W. D., Layne, S. P., Kash, J. C., Taubenberger, J. K.

Science Translational Medicine 13(620), eabj77902021

Collaborative Others

Risk assessment of latent tuberculosis infection through a multiplexed cytokine biosensor assay and machine learning feature selection

Robison, H. M., Chapman, C. A., Zhou, H., Erskine, C. L., Theel, E., Peikert, T., Lindestam Arlehamn, C. S., Sette, A., Bushell, C., Welge, M., Zhu, R., Bailey, R. C., Escalante, P.

Scientific Reports 11(1), 205442021

Collaborative Disease Diagnostics and Treatment

Topic Modeling on Triage Notes With Semiorthogonal Nonnegative Matrix Factorization

Li, Y., Zhu, R., Qu, A., Ye, H., Sun, Z.

Journal of the American Statistical Association 116(536), 1609-16242021

Method & Theory Disease Diagnostics and Treatment

2020

Assessment of peritoneal microbial features and tumor marker levels as potential diagnostic tools for ovarian cancer

Miao, R., Badger, T. C., Groesch, K., Diaz-Sylvester, P. L., Wilson, T., Ghareeb, A., Martin, J. A., Cregger, M., Welge, M., Bushell, C., Auvil, L., Zhu, R., Brard, L., Braundmeier-Fleming, A.

PLOS ONE 15(1), e02277072020

Collaborative Disease Diagnostics and Treatment

Constructing Dynamic Treatment Regimes with Shared Parameters for Censored Data

Zhao, Y.-Q., Zhu, R., Chen, G., Zheng, Y.

Statistics in Medicine 39(9), 1250-12632020

Method & Theory Survival Analysis

Nonparametric variable selection and its application to additive models

Feng, Z., Lin, L., Zhu, R., Zhu, L.

Annals of the Institute of Statistical Mathematics 72(3), 827-8542020

Method & Theory Others

2019

Bagging and Deep Learning in Optimal Individualized Treatment Rules

Mi, X., Zou, F., Zhu, R.

Biometrics 75(2), 674-6842019

Method & Theory Personalized Medicine

Counting process-based dimension reduction methods for censored outcomes

Sun, Q., Zhu, R., Wang, T., Zeng, D.

Biometrika 106(1), 181-1962019

Method & Theory Survival Analysis Dimension Reduction

Differential Effects of Influenza Virus NA, HA Head, and HA Stalk Antibodies on Peripheral Blood Leukocyte Gene Expression during Human Infection

Walters, K.-A., Zhu, R., Welge, M., Scherler, K., Park, J.-K., Rahil, Z., Wang, H., Auvil, L., Bushell, C., Lee, M. Y., Baxter, D., Bristol, T., Rosas, L. A., Cervantes-Medina, A., Czajkowski, L., Han, A., Memoli, M. J., Taubenberger, J. K., Kash, J. C.

mBio 10(3), e00760-192019

Collaborative Influenza

orthoDr: Semiparametric Dimension Reduction via Orthogonality Constrained Optimization

Zhu, R., Zhang, J., Zhao, R., Xu, P., Zhou, W., Zhang, X.

The R Journal 11(2), 24-372019

Method & Theory Survival Analysis Dimension Reduction

2018

GradientScanSurv: An exhaustive association test method for gene expression data with censored survival outcome

Yi, M., Zhu, R., Stephens, R. M.

PLOS ONE 13(12), e02075902018

Collaborative Survival Analysis

Multivariate Computational Analysis of Biosensor's Data for Improved CD64 Quantification for Sepsis Diagnosis

Hassan, U., Zhu, R., Bashir, R.

Lab on a Chip 18(8), 1231-12402018

Collaborative Sepsis

2017

Combining Biomarkers with EMR Data to Identify Patients in Different Phases of Sepsis

Taneja, I., Reddy, Jr., B., Damhorst, G., Zhao, S. D., Hassan, U., Price, Z., Jensen, T., Ghonge, T., Patel, M., Wachspress, S., Winter, J., Rappleye, M., Smith, G., Healey, R., Ajmal, M., Khan, M., Patel, J., Rawal, H., Sarwar, R., Soni, S., Anwaruddin, S., Davis, B., Kumar, J., White, K., Bashir, R., Zhu, R.

Scientific Reports 7(1), 108002017

Collaborative Sepsis