Dan Kluger

I am a Michael Hammer Postdoctoral Fellow at the MIT Institute for Data, Systems, and Society, where I am fortunate to be hosted by Professors Sherrie Wang and Stephen Bates. I am broadly interested in developing statistical methods for drawing reliable conclusions from heterogeneous data sources that differ in quality, size, or resolution. My research is motivated by applications in agronomy, environmental science, and biomedical science, especially the types of heterogeneous data sets I have encountered when collaborating with scientists in these domains. My recent research focuses on developing methods for reliably leveraging widely available, yet error-prone estimates from machine learning models, and connects to the adaptive sampling, prediction-powered inference, measurement error, and missing data literatures.

Previously, I completed my PhD in Statistics at Stanford University, where I was grateful to be advised by Professors Art Owen and David Lobell and supported as a James and Nancy Kelso Interdisciplinary Graduate Fellow. While at Stanford, my research areas included multiple hypothesis testing, causal inference, and agronomy. Prior to graduate school, I received a B.S. in Mathematics and a B.A. in Statistics & Data Science at Yale University.

Selected Papers

M-estimation under Two-Phase Multiwave Sampling with Applications to Prediction-Powered Inference

Dan M. Kluger, and Stephen Bates

2026

★ ASA Section on Statistical Learning and Data Science Paper Award

arXiv Reproducibility
Demystifying Prediction-Powered Inference

Yilin Song, Dan M. Kluger, Harsh Parikh, and 1 more author

2026

To appear in Harvard Data Science Review

arXiv
Prediction-Powered Inference with Imputed Covariates and Nonuniform Sampling

Dan M. Kluger, Kerri Lu, Tijana Zrnic, and 2 more authors

2025

★ Extended abstract selected for the American Economic Association Papers & Proceedings

arXiv R Python Reproducibility

Regression coefficient estimation from remote sensing maps

Kerri Lu, Dan M. Kluger, Stephen Bates, and 1 more author

Remote Sensing of Environment, 2025

arXiv Bib HTML Reproducibility

@article{LKBW_25_RemoteSensingRegressionCoefficient,
  title = {Regression coefficient estimation from remote sensing maps},
  journal = {Remote Sensing of Environment},
  volume = {330},
  pages = {114949},
  year = {2025},
  issn = {0034-4257},
  doi = {https://doi.org/10.1016/j.rse.2025.114949},
  url = {https://www.sciencedirect.com/science/article/pii/S0034425725003530},
  codereproducibility = {https://github.com/Earth-Intelligence-Lab/uncertainty-quantification},
  author = {Lu, Kerri and Kluger, Dan M. and Bates, Stephen and Wang, Sherrie}
}

Precrop payoffs: causal machine learning reveals large but variable yield benefits of crop rotation in major breadbaskets

Dan M. Kluger, Stefania Di Tommaso, and David B. Lobell

Environmental Research Letters, 2025

arXiv HTML Press Reproducibility

A central limit theorem for the Benjamini-Hochberg false discovery proportion under a factor model

Dan M. Kluger, and Art B. Owen

Bernoulli, 2024

arXiv Bib HTML Video

@article{KO24_BHCLTunderDependence,
  author = {Kluger, Dan M. and Owen, Art B.},
  title = {{A central limit theorem for the Benjamini-Hochberg false discovery proportion under a factor model}},
  volume = {30},
  journal = {Bernoulli},
  number = {1},
  publisher = {Bernoulli Society for Mathematical Statistics and Probability},
  pages = {743 -- 769},
  keywords = {Empirical cumulative distribution function, functional central limit theorem, Functional Delta Method, multiple hypothesis testing, Simes line},
  year = {2024},
  doi = {10.3150/23-BEJ1615},
  url = {https://doi.org/10.3150/23-BEJ1615},
}

Combining randomized field experiments with observational satellite data to assess the benefits of crop rotations on yields

Dan M. Kluger, Art B. Owen, and David B. Lobell

Environmental Research Letters, 2022

Bib HTML Blog

@article{KOL22_ExperimentalObservationalCropRotation,
  doi = {10.1088/1748-9326/ac6083},
  url = {https://dx.doi.org/10.1088/1748-9326/ac6083},
  year = {2022},
  publisher = {IOP Publishing},
  volume = {17},
  number = {4},
  pages = {044066},
  author = {Kluger, Dan M. and Owen, Art B. and Lobell, David B.},
  title = {Combining randomized field experiments with observational satellite data to assess the benefits of crop rotations on yields},
  journal = {Environmental Research Letters},
}