Jon Ahlinder

This paper introduces a method to accelerate optimum contribution selection by approximating genomic relationship matrices with low-rank structures, achieving significant speedups while maintaining accuracy.

The paper introduces CVaR-OCS, a method that improves breeding decisions by incorporating uncertainty in genetic evaluations, leading to more robust selection outcomes.

The paper proposes using principal component analysis to improve computational efficiency in multi-trait genetic evaluations, achieving faster results with comparable accuracy.