Scholar
Dan Kluger
Google Scholar ID: YEO85McAAAAJ
MIT Institute for Data Systems and Society
Citations & Impact
Citations
237
H-index
7
i10-index
4
Publications
16
Co-authors
0
Publications
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
- Published several papers, including: 'Precrop payoffs: causal machine learning reveals large but variable yield benefits of crop rotation in major breadbaskets', 'Prediction-Powered Inference with Imputed Covariates and Nonuniform Sampling', 'Regression coefficient estimation from remote sensing maps', 'A central limit theorem for the Benjamini-Hochberg false discovery proportion under a factor model', 'Kernel regression analysis of tie-breaker designs'.
Research Experience
- Currently a Michael Hammer Postdoctoral Fellow at the MIT Institute for Data, Systems, and Society, hosted by Professors Sherrie Wang and Stephen Bates. Research areas include multiple hypothesis testing, causal inference, data fusion, measurement error, crop rotation, and crop type mapping.
Education
- PhD in Statistics from Stanford University, advised by Professors Art Owen and David Lobell; B.S. in Mathematics and B.A. in Statistics & Data Science from Yale University.
Background
- A statistician and interdisciplinary researcher, broadly interested in developing and deploying statistical methods for applications in agriculture and remote sensing. His current research focuses on methods for conducting reliable statistical analyses that leverage widely available, yet error-prone proxies.
Co-authors