
About
Reka Howard is an Associate Professor in the Department of Statistics at the University of Nebraska-Lincoln's Institute of Agriculture and Natural Resources (IANR), where she bridges advanced statistical methodology with agricultural innovation through genomic prediction research and graduate education.
Education:
- PhD in Statistics and Plant Breeding, Iowa State University (2016)
Research Focus: Dr. Howard pioneers statistical methods for genomic prediction in plant breeding, with emphasis on optimizing prediction accuracy and modeling genotype by environment interactions. Her work integrates environmental data with genomic information to develop robust models for crop improvement across soybean, wheat, and sorghum systems, directly addressing challenges in climate-resilient agriculture through computational innovation and field application.
Publication Trends: Recent publications (2023-2025) reveal three dominant themes: (1) Methodological advances in genomic prediction including lambda optimization for ridge regression and sparse testing protocols; (2) Integration of environmental features with genomic data for transferable prediction models; and (3) Physiological investigations into nitrogen dynamics and canopy architecture in soybean production systems. Her work increasingly employs artificial intelligence techniques while maintaining rigorous statistical foundations.
Teaching & Service: Dr. Howard instructs graduate statistical methods courses for agronomy, animal science, and engineering students, developing curriculum that translates complex methodologies into practical research tools for the next generation of agricultural scientists.
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