I work with big data in agriculture, focusing on the intersection of data analysis and agricultural science to improve plant and animal breeding. A key component of my work is the development of robust, scalable analysis pipelines for the systematic assessment and correction of metadata — an often overlooked but critical component of large-scale studies. By addressing data integrity and methodological consistency, I aim to improve the reliability of downstream analyses and facilitate more informed, data-driven decision-making in breeding research.
