Pascal Duenk

Pascal Duenk is an Assistant Professor in the Animal Breeding and Genetics group at Wageningen University & Research, Faculty of Animal Sciences. His work bridges quantitative genetics, genomics, and livestock improvement, with a strong focus on poultry and genomic prediction methodologies.

• PhD in Animal Breeding and Genetics, Wageningen University
• Engineering degree (ir.), likely from Wageningen University

His research interests center on genomic prediction, genetic correlation, resilience in livestock, and integration of functional genomic information. He applies advanced statistical models and machine learning to improve breeding values and animal health. His work often involves collaboration across European institutions and participation in major livestock genetics forums.

The most recent articles show a consistent trend in applying genomic tools to real-world animal breeding challenges—particularly in poultry welfare, thermal stress resilience, and accuracy of genomic models. There is a clear emphasis on translating theoretical genetics into practical breeding applications.

While no formal awards are listed in the provided text, his active role as editor and presenter at major conferences like WCGALP highlights his recognition in the field.

Duenk has served as co-promotor (co-supervisor) for multiple PhD projects, including those of C. Fu, J. Yang, and his own earlier PhD under the GenolViiX project. He has contributed to research grants and collaborative projects focused on improving genomic prediction models and utilizing crossbred data for genetic gain. His work is supported by datasets shared via Figshare, indicating transparency and reproducibility.

He is actively involved in research teams working on genomic annotation, crossbred genomics, and poultry resilience. His projects such as 'Using functional annotations in genomic prediction' and 'Improving genomic prediction models' reflect a forward-looking agenda in precision animal breeding.