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Kristine Gierz (Fed)

Mathematical Statistician

Kristine Gierz is a Mathematical Statistician in the Statistical Engineering Division of the National Institute of Standards and Technology's Information Technology Laboratory (ITL). 

Kristine received her B.S. in Evolutionary Biology and Ecology from the University of California, Los Angeles. After a marine conservation internship in Fiji, she continued her studies and obtained her M.S. and Ph.D. in Biostatistics from Old Dominion University. She received the National Science Foundation’s Mathematical Sciences Graduate Internship in 2018 and completed a graduate fellowship at NIST, Gaithersburg in the Statistical Engineering Division. The final portion of her Ph.D. was funded by the DoDs SMART Scholarship, and she worked as an Operations Research Analyst for the Secretary of the Air Force Studies, Analyses, and Assessments at the Pentagon. While there, she completed formative reports to include the military’s first Racial-Ethnic and Gender Disparity Review and the military’s first Maternal Health and Wellness Survey and analysis. She joined the Statistical Engineering Division at NIST in 2022.

Her research interests include analysis of censored data, change point analysis, process control, uncertainty analysis, design & analysis, and statistical computation. 

Kristine enjoys all outdoor activities, is an avid reader and gardener, a reluctant distance runner, and an extremely amateur ukulele player.

technical areas of research and consulting

  • Biostatistics
  • Survival analysis
  • Uncertainty analysis
  • Non-parametric statistics

Professional ACtivities and societies 

American Statistical Association, Member


NSF and NIST logos

National Science Foundation's Mathematical Sciences Graduate Internship (MSGI), 2018. National Institute of Standards and Technology, Gaithersburg. "Meet a Participant" Success Story.



DoD SMART logo

Department of Defense's Science, Mathematics, and Research for Transformation (SMART) Scholarship, 2019 & 2020. Secretary of the Air Force Studies, Analysis, and Assessments, Pentagon. 

Selected External Publications

Gierz K, Park K, Qiu P. Non-parametric treatment time-lag effect estimation. Statistical Methods in Medical Research. 2022;31(1):62-75. doi:10.1177/09622802211032693

Gierz, K., Park, K. Detection of multiple change points in a Weibull accelerated failure time model using sequential testing. Biometrical Journal. 2022; 64: 617– 634.


Created September 12, 2022, Updated June 7, 2023