Google Scholar

Preprints

  1. Improving RCT-Based CATE Estimation Under Covariate Mismatch via Double Calibration Pal, Samhita, Huling, Jared D., and Asiaee, Amir Preprint (2026) [arXiv:2603.17066]
  2. Estimation of heterogeneous principal effects under principal ignorability Zhang, Rui, Doss, Charles, and Huling, Jared D. Preprint (2026) [arXiv:2603.08963]
  3. Estimating causal effects of functional treatments with modified functional treatment policies Jiang, Ziren, Cui, Erjia, and Huling, Jared D. Preprint (2026) [arXiv:2602.09145]
  4. Partially Retargeted Balancing Weights for Causal Effect Estimation Under Positivity Violations Barnard, Martha, Huling, Jared D., and Wolfson, Julian Preprint (2025)
    ★ Distinguished Student Paper Award, ENAR 2026
    [arXiv:2510.22072]
  5. Data adaptive covariate balancing for causal effect estimation for high dimensional data De, Simion, and Huling, Jared D. Preprint (2025) [arXiv:2512.18069]
  6. Exploring the effects of mechanical ventilator settings with modified vector-valued treatment policies Jiang, Ziren, Crooke, Philip S., Marini, John J., and Huling, Jared D. Preprint (2025) [arXiv:2507.09809]
  7. Heterogeneity-Aware Regression with Nonparametric Estimation and Structured Selection for Hospital Readmission Prediction Wang, Wei, Bailey, Angela, Tignanelli, Christopher, and Huling, Jared D. Preprint (2025) [arXiv:2507.06388]
  8. Transportability of Principal Causal Effects Clark, Justin M., Rott, Kollin W., Hodges, James S., and Huling, Jared D. Preprint (2024) [arXiv:2405.04419]
  9. Causally-Interpretable Random-Effects Meta-Analysis Clark, Justin M., Rott, Kollin W., Hodges, James S., and Huling, Jared D. Preprint (2023) [arXiv:2302.03544]
  10. Improving Precision of RCT-Based CATE Estimation using Data Borrowing with Double Calibration Asiaee, Amir, Di Gravio, Chiara, Beck, Cole, Mei, Yuting, Pal, Samhita, and Huling, Jared D. Preprint (2023) [arXiv:2306.17478]
  11. Selection and estimation optimality in high dimensions with the TWIN penalty Dai, Xiaowu, and Huling, Jared D. Preprint (2021) [arXiv:1806.01936]

Publications

2026

  1. Doss and Huling’s contribution to the Discussion of ‘Augmented balancing weights as linear regression’ by Bruns-Smith et al. Doss, Charles R., and Huling, Jared D. Journal of the Royal Statistical Society Series B: Statistical Methodology (2026) [doi]
  2. A Framework for Causal Estimand Selection Under Positivity Violations Barnard, Martha, Huling, Jared D., and Wolfson, Julian Biometrics (2026) [arXiv:2410.12093] [doi]

2025

  1. Counterfactual fairness for small subgroups Wastvedt, Solvejg, Huling, Jared D., and Wolfson, Julian Biostatistics (2025) [arXiv:2310.19988] [doi] [code]
  2. Modified treatment policy effect estimation with weighted energy distance Jiang, Ziren, and Huling, Jared D. The Annals of Applied Statistics, 19(4):2555–2577 (2025)
    ★ Distinguished Student Paper Award, ENAR 2024
    [arXiv:2310.11620] [doi]
  3. Causally interpretable meta-analysis combining aggregate and individual participant data Rott, Kollin W., Clark, Justin M., Murad, M. Hassan, Hodges, James S., and Huling, Jared D. American Journal of Epidemiology, 194(7):2060–2068 (2025)
    ★ Distinguished Student Paper Award, ENAR 2024
    [doi]

2024

  1. An effective framework for estimating individualized treatment rules with multi-category treatments Lee, Joowon, Huling, Jared D., and Chen, Guanhua Advances in Neural Information Processing Systems (NeurIPS) (2024) [doi]
  2. Independence weights for causal inference with continuous treatments Huling, Jared D., Greifer, Noah, and Chen, Guanhua Journal of the American Statistical Association, 119(546):1657–1670 (2024) [arXiv:2107.07086] [doi] [code] [CRAN]
  3. Energy balancing of covariate distributions Huling, Jared D., and Mak, Simon Journal of Causal Inference (2024) [arXiv:2004.13962] [doi] [code]
  4. An intersectional framework for counterfactual fairness in risk prediction Wastvedt, Solvejg, Huling, Jared D., and Wolfson, Julian Biostatistics, 25(3):702–717 (2024) [arXiv:2210.01194] [doi] [code]
  5. Robust sample weighting to facilitate individualized treatment rule learning for a target population Chen, Rui, Huling, Jared D., Chen, Guanhua, and Yu, Menggang Biometrika, 111(1):309–329 (2024) [arXiv:2105.00581] [doi]

2023

  1. A reluctant additive model framework for interpretable nonlinear individualized treatment rules Maronge, Jacob M., Huling, Jared D., and Chen, Guanhua The Annals of Applied Statistics, 17(4):3384–3402 (2023) [doi]
  2. Doubly structured sparsity for grouped multivariate responses with application to functional outcome score modeling Huling, Jared D., Lundine, Jennifer P., and Leonard, Julie C. Statistics in Medicine, 42(15):2619–2636 (2023) [arXiv:2302.11098] [doi] [code]

2022

  1. Sufficient dimension reduction for populations with structured heterogeneity Huling, Jared D., and Yu, Menggang Biometrics, 78(4):1626–1638 (2022) [arXiv:2212.12394] [doi] [code] [CRAN]
  2. Meta-analysis of individualized treatment rules via sign-coherency Cheng, Justin J., Huling, Jared D., and Chen, Guanhua Machine Learning for Health (ML4H), PMLR, 193:171–198 (2022) [link] [code]
  3. Fast penalized regression and cross validation for tall data with the {oem} package Huling, Jared D., and Chien, Peter Journal of Statistical Software, 104(6):1–24 (2022) [arXiv:1801.09661] [doi] [code] [CRAN]

2021

  1. Subgroup identification using the {personalized} package Huling, Jared D., and Yu, Menggang Journal of Statistical Software, 98(5):1–60 (2021) [doi] [code] [CRAN]
  2. Diagnosis-group-specific transitional care program recommendations for thirty-day rehospitalization reduction Yu, Menggang, Kuang, Chensheng, Huling, Jared D., and Smith, Maureen A. The Annals of Applied Statistics, 15(3):1478–1498 (2021) [doi] [code]
  3. A two-part framework for estimating individualized treatment rules from semi-continuous outcomes Huling, Jared D., Smith, Maureen A., and Chen, Guanhua Journal of the American Statistical Association, 116(533):210–223 (2021) [doi] [code] [CRAN]

2019

  1. Instrumental variable based estimation under the semiparametric accelerated failure time model Huling, Jared D., Yu, Menggang, and O’Malley, A. James Biometrics, 75(2):516–527 (2019) [doi] [code]
  2. Fused comparative intervention scoring for heterogeneity of longitudinal intervention effects Huling, Jared D., Yu, Menggang, and Smith, Maureen A. The Annals of Applied Statistics, 13(2):824–847 (2019) [doi] [code]

2018

  1. Risk prediction for heterogeneous populations with application to hospital admission prediction Huling, Jared D., Yu, Menggang, Liang, Muxuan, and Smith, Maureen A. Biometrics, 74(2):557–565 (2018) [doi] [code] [CRAN]

2017

  1. Accelerating large-scale statistical computation with the GOEM algorithm Nie, Xiao, Huling, Jared D., and Qian, Peter Z. G. Technometrics, 59(4):416–425 (2017) [doi]

2016

  1. Orthogonalizing EM: A design-based least squares algorithm Xiong, Shifeng, Dai, Bin, Huling, Jared D., and Qian, Peter Z. G. Technometrics, 58(3):285–293 (2016) [doi] [code] [CRAN]