Bio


I am a final-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


  • Kernel regression analysis of tie-breaker designs ELECTRONIC JOURNAL OF STATISTICS Kluger, D. M., Owen, A. B. 2023; 17 (1): 243-290

    View details for DOI 10.1214/23-EJS2102

    View details for Web of Science ID 000951095100005

  • Combining randomized field experiments with observational satellite data to assess the benefits of crop rotations on yields ENVIRONMENTAL RESEARCH LETTERS Kluger, D. M., Owen, A. B., Lobell, D. B. 2022; 17 (4)
  • Two shifts for crop mapping: Leveraging aggregate crop statistics to improve satellite-based maps in new regions REMOTE SENSING OF ENVIRONMENT Kluger, D. M., Wang, S., Lobell, D. B. 2021; 262
  • Impact of healthcare worker shift scheduling on workforce preservation during the COVID-19 pandemic. Infection control and hospital epidemiology Kluger, D. M., Aizenbud, Y. n., Jaffe, A. n., Parisi, F. n., Aizenbud, L. n., Minsky-Fenick, E. n., Kluger, J. M., Farhadian, S. n., Kluger, H. M., Kluger, Y. n. 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