
Dan Kluger
Ph.D. Student in Statistics, admitted Autumn 2018
Bio
I am a 5th year PhD student in statistics. I am fortunate to be advised by Professor Art Owen and am also fortunate to work under the supervision of Professor David Lobell. I am grateful to be supported by a Stanford Interdisciplinary Graduate Fellowship as a James and Nancy Kelso Fellow. My research interests include multiple hypothesis testing, data fusion, and applications of statistics to agronomy and remote sensing.
All Publications
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Kernel regression analysis of tie-breaker designs
ELECTRONIC JOURNAL OF STATISTICS
2023; 17 (1): 243-290
View details for DOI 10.1214/23-EJS2102
View details for Web of Science ID 000951095100005
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Combining randomized field experiments with observational satellite data to assess the benefits of crop rotations on yields
ENVIRONMENTAL RESEARCH LETTERS
2022; 17 (4)
View details for DOI 10.1088/1748-9326/ac6083
View details for Web of Science ID 000778724700001
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Two shifts for crop mapping: Leveraging aggregate crop statistics to improve satellite-based maps in new regions
REMOTE SENSING OF ENVIRONMENT
2021; 262
View details for DOI 10.1016/j.rse.2021.112488
View details for Web of Science ID 000663567700002
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Impact of healthcare worker shift scheduling on workforce preservation during the COVID-19 pandemic.
Infection control and hospital epidemiology
2020: 1–15
Abstract
Reducing SARS-COV-2 infections among healthcare workers is critical. We ran Monte Carlo simulations modeling the spread of SARS-CoV-2 in non-COVID wards, and found that longer nursing shifts and scheduling designs in which teams of nurses and doctors co-rotate no more frequently than every three days, can lead to fewer infections.
View details for DOI 10.1017/ice.2020.337
View details for PubMedID 32684183