Rate My Professor Emre Karaman

Emre Karaman is an Associate Professor at the Center for Quantitative Genetics and Genomics (QGG) within the Faculty of Technical Sciences at Aarhus University. Originally from Turkey, he brings a background in econometrics and animal science, having earned his PhD from Akdeniz University in Antalya. Karaman joined QGG as a postdoctoral researcher in 2016 and advanced to a tenure-track assistant professorship in December 2020. His career at Aarhus University reflects a commitment to advancing statistical genetics methodologies. In 2024, he received the prestigious Sapere Aude grant from the Independent Research Fund Denmark to lead the project 'Unravelling admixture-introduced complex genetic variation in genomic research,' enabling him to establish his own research group focused on genomic approaches for admixed populations.

Karaman's research centers on quantitative genetics and genomics, with key contributions to genomic prediction in livestock, particularly dairy cattle. His work addresses challenges in admixed populations, improving accuracy in ancestry inference and prediction models for traits like methane emissions, rumen microbiota composition, milk vitamin concentrations, and feed efficiency. Notable publications include 'Accuracy of local ancestry inference and its impact on genomic prediction in admixed dairy cattle populations' (2026), 'Predicting riboflavin (vitamin B2) and cobalamin (vitamin B12) concentrations in Danish cow milk using Fourier transform mid infrared spectra' (2026), 'Genomic prediction in Nordic Red dairy cattle considering breed origin of alleles' (2022), and 'Improvement of genomic prediction by integrating additional single nucleotide polymorphisms selected from imputed whole genome sequencing data' (2020). He has developed tools like the NextGP.jl package for biologically informed genomic predictions and serves as a member of the Academic Council and Topical Advisory Panel for the journal Animals in the section on Animal Genetics and Genomics. Karaman's methodologies enhance genetic gain in breeding programs and support sustainable agriculture through better trait prediction.