biotmle: Targeted Learning for Biomarker Discovery. - Nima S. Hejazi; Weixin Cai; Alan E. Hubbard (J. Open Source Softw., 2017)

methyvim: Targeted, robust, and model-free differential methylation analysis in R. - Nima S. Hejazi; Rachael V. Phillips; Alan E. Hubbard; Mark J. van der Laan (F1000Research, 2018)

adaptest: Data-Adaptive Statistics for High-Dimensional Testing in R. - Weixin Cai; Alan E. Hubbard; Nima S. Hejazi (J. Open Source Softw., 2018)

origami: A Generalized Framework for Cross-Validation in R. - Jeremy R. Coyle; Nima S. Hejazi (J. Open Source Softw., 2018)

Exploring high-dimensional biological data with sparse contrastive principal component analysis. - Philippe Boileau; Nima S. Hejazi; Sandrine Dudoit (Bioinform., 2020)

scPCA: A toolbox for sparse contrastive principal component analysis in R. - Philippe Boileau; Nima S. Hejazi; Sandrine Dudoit (J. Open Source Softw., 2020)

txshift: Efficient estimation of the causal effects of stochastic interventions in R. - Nima S. Hejazi; David C. Benkeser (J. Open Source Softw., 2020)

hal9001: Scalable highly adaptive lasso regression in R. - Nima S. Hejazi; Jeremy R. Coyle; Mark J. van der Laan (J. Open Source Softw., 2020)

A framework for causal segmentation analysis with machine learning in large-scale digital experiments. - Nima S. Hejazi; Wenjing Zheng; Sathya Anand (CoRR, 2021)

cvCovEst: Cross-validated covariance matrix estimator selection and evaluation in R. - Philippe Boileau; Nima S. Hejazi; Brian Collica; Mark J. van der Laan; Sandrine Dudoit (J. Open Source Softw., 2021)

'haldensify': Highly adaptive lasso conditional density estimation in 'R'. - Nima S. Hejazi; Mark J. van der Laan; David C. Benkeser (J. Open Source Softw., 2022)

'medoutcon': Nonparametric efficient causal mediation analysis with machine learning in 'R'. - Nima S. Hejazi; Kara E. Rudolph; Iván Díaz (J. Open Source Softw., 2022)

Cross-Validated Loss-based Covariance Matrix Estimator Selection in High Dimensions. - Philippe Boileau; Nima S. Hejazi; Mark J. van der Laan; Sandrine Dudoit (J. Comput. Graph. Stat., 2023)

Statistical learning for constrained functional parameters in infinite-dimensional models with applications in fair machine learning. - Razieh Nabi; Nima S. Hejazi; Mark J. van der Laan; David C. Benkeser (CoRR, 2024)

CausalTables.jl: Simulating and storing data for statistical causal inference in Julia. - Salvador V. Balkus; Nima S. Hejazi (J. Open Source Softw., 2025)