1675 Observatory Dr
440 Animal Sciences
Madison, WI 53706
Guilherme Rosa obtained an M.S. in Animal Sciences from Sao Paulo State University (UNESP), Brazil, in 1994, and a Ph.D. in Statistics and Agricultural Experimentation from the University of Sao Paulo (USP), Brazil, in 1998. He began his professional career as a faculty member in the Department of Biostatistics at UNESP (1994-2001) before relocating to the USA as a faculty member at Michigan State University (2002-2006) and eventually joining the faculty at UW-Madison in 2006. Currently, he holds the position of Professor in the Department of Animal and Dairy Sciences, with an affiliate appointment in the Department of Biostatistics & Medical Informatics.
Dr. Rosa’s work involves teaching courses and conducting research on statistical and computational tools for analyzing livestock data, including beef and dairy cattle, swine, poultry, and other species. His research applications encompass the analysis of farm-level operational data to optimize management practices, high-throughput phenotyping techniques for real-time monitoring of individual animals and disease surveillance, as well as quantitative genetics/genomics and breeding. To date, Guilherme has authored 13 book chapters and over 250 refereed papers in scientific journals. He has also secured external grants totaling over $14 million to support his research programs.
Selected Peer-Reviewed Articles
Freitas, L. A., Ferreira, R. E. P., Savegnago, R. P., Dorea, J. R. R., Stafuzza, N. B., Rosa, G. J. M. and Paz, C. C. P. Image analysis to automatically classify anemia based on Famacha© score in sheep using ocular conjunctiva images. Translational Animal Science 10:txad118, 2023.
Alves, A. A. C., Fernandes, A. F. A., Lopes, F. B., Breen, V., Hawken, R., Gianola, D., and Rosa, G. J. M. (Quasi) multitask support vector regression with heuristic hyperparameter optimization for whole-genome prediction of complex traits: a case study with carcass traits in broilers. G3 Genes|Genomes|Genetics 13(8): jkad109, 2023.
Siegford, J. M., Steibel, J. P., Han, J., Benjamin, M., Brown-Brandl, T., Dorea, J. R. R., Morris, D., Norton, T., Psota, E. and Rosa, G. J. M. The quest to develop automated systems for monitoring animal behavior. Applied Animal Behaviour Science 265: 106000, 2023.
Vang, A. L., Bresolin, T., Frizzarini, W. S., Menezes, G. L., Cunha, T., Rosa, G. J. M., Hernandez, L. L. and Dorea, J. R. R. Longitudinal analysis of bovine mammary gland development. Journal of Mammary Gland Biology and Neoplasia 28:11, 2023.
Freitas, L. A., Savegnago, R. P., Alves, A. A. C., Costa, R. L. D., Munari, D. P., Stafuzza, N. B., Rosa, G. J. M. and Paz, C. C. P. Classification performance of machine learning methods for identifying resistance, resilience, and susceptibility to Haemonchus contortus infections in sheep. Animals 13: 374, 2023.
Binversie, E. E., Momen, M., Rosa, G. J. M., Davis, B. W. and Muir, P. Across-breed genetic investigation of canine hip dysplasia, elbow dysplasia, and anterior cruciate ligament rupture using whole-genome sequencing. Front. Genet., 13: 913354, 2022.
Ferreira, R. E. P., Bresolin, T., Rosa, G. J. M. and Dórea, J. R. R. Using dorsal surface for individual identification of dairy calves through 3D deep learning algorithms. Computers and Electronics in Agriculture 201: 107272, 2022.
Momen, M., Brounts, S. H., Binversie, E. E., Sample, S. J., Rosa, G. J. M., Davis, B. W. and Muir, P. Selection signature analyses and genome-wide association reveal genomic hotspot regions that reflect differences between breeds of horse with contrasting risk of degenerative suspensory ligament desmitis. G3: Genes, Genomes, Genetics 12(10): jkac179, 2022.
Li, M., Rosa, G. J. M., Reed, K. F and Cabrera, V. E. Investigating the impact of temporal, geographic, and management factors on US Holstein lactation curve parameters. Journal of Dairy Science 105: 7525-7538, 2022.
Momen, M., Kranis, A., Rosa, G. J. M., Muir, P. and Gianola, D. Predictive assessment of single-step BLUP with linear and non-linear similarity RKHS kernels: A case study in chickens. Journal of Animal Breeding and Genetics 139: 247-258, 2022.
Alves, A. A., Costa, R. M., Fonseca, L. S., Carvalheiro, R., Ventura, R., Rosa, G. J. M. and Albuquerque, L. G. A Random Forest-based genome-wide scan reveals fertility-related candidate genes and potential inter-chromosomal epistatic regions associated with age at first calving in Nellore cattle. Front. Genet., 13: 834724, 2022.
Amalfitano, N., Rosa, G. J. M., Cecchinato, A. and Bittante, G. Nonlinear modeling to describe the pattern of milk protein and nonprotein compounds over lactation in dairy cows. Journal of Dairy Science 104: 10950-10969, 2021.
Ribeiro, L. A. C., Bresolin, T., Rosa, G. J. M., Casagrande, D. M., Danes, M. A. C. and Dórea, J. R. R. Disentangling data dependency using cross-validation strategies to evaluate prediction quality of cattle grazing activities using machine learning algorithms and wearable sensor data. Journal of Animal Science 99(9): 1-8, 2021.
Moreira, L. C., Rosa, G. J. M. and Schaefer, D. M. Board Invited Review: Beef production from cull dairy cows: a review from culling to consumption. Journal of Animal Science 99(7): 1-18, 2021.
Resende, R. T., Piepho, H.-P., Rosa, G. J. M., Silva-Junior, O. B., Silva, F. F., de Resende, M. D. V., and Grattapaglia, D. Enviromics in breeding: applications and perspectives on envirotypic‑assisted selection. Theoretical and Applied Genetics 134: 95-112, 2021.
Selected Book Chapters
Rosa, G. J. M. Quantitative Methods Applied to Animal Breeding. In: Encyclopedia of Sustainability Science and Technology. Meyers, R. A. (Editor). New York: Springer, 2022.
Hutchins, J., Hueth, B. and Rosa, G. J. M. Quantifying Heterogeneous Returns to Genetic Selection: Evidence from Wisconsin Dairies. In: Economics of Research and Innovation in Agriculture, National Bureau of Economic Research, Inc., 2020.
Rosa, G. J. M., Felipe, V. P. S. and Peñagaricano, F. Applications of Graphical Models in Quantitative Genetics and Genomics. In: Systems Biology in Animal Production and Health, Volume 1. Kadarmideen, H. (Ed.) Springer, 2016.
Gianola, D. and Rosa, G. J. M. One Hundred Years of Statistical Developments in Animal Breeding. Book Series: Annual Review of Animal Biosciences Vol 3, p.19-56, 2015.
Rosa, G. J. M. and Valente, B. D. Structural Equation Models for Studying Causal Phenotype Networks in Quantitative Genetics. In: Probabilistic Graphical Models for Genetics, Genomics and Postgenomics. Sinoquet, C. and Mourad, R. (Eds.) Oxford University Press, 2014.
Rosa, G. J. M. Basic Genetic Model for Quantitative Traits. In: Molecular and Quantitative Animal Genetics. Khatib, H. (Ed.) Wiley-Blackwell, Oxford, UK, 2014.
Rosa, G. J. M. Heritability and Repeatability. In: Molecular and Quantitative Animal Genetics. Khatib, H. (Ed.) Wiley-Blackwell, Oxford, UK, 2014.
Valente, B. D. and Rosa, G. J. M. Mixed effects structural equation models and phenotypic causal networks. In: Genome-Wide Association Studies. Gondro, C., van der Werf, J. and Hayes, B. (Eds.) Springer, 2013.
Rosa, G. J. M. Quantitative Trait. In: Brenner’s Encyclopedia of Genetics, 2nd ed. Maloy, S. and Hughes, K. (Editors). San Diego: Academic Press – Elsevier, 2013.
Rosa, G. J. M. Progeny Test. In: Brenner’s Encyclopedia of Genetics, 2nd ed. Maloy, S. and Hughes, K. (Editors). San Diego: Academic Press – Elsevier, 2013.
Rosa, G. J. M. Foundations of Animal Breeding. In: Sustainable Food Production. Christou, P., Savin, R., Costa-Pierce, B., Misztal, I. and Whitelaw, B. (Editors). New York: Springer, 2013.
Rosa, G. J. M. and Tempelman, R. J. Bayesian Mapping Methodology. In: Genetic Analysis of Complex Traits with SAS. Saxton, A. (Editor). Cary, NC: SAS Institute Inc., 2004.
Tempelman, R. J. and Rosa, G. J. M. Empirical Bayes Approaches to Mixed Model Inference in Quantitative Genetics. In: Genetic Analysis of Complex Traits with SAS. Saxton, A. (Editor). Cary, NC: SAS Institute Inc., 2004.
Selected Popular Press Articles
Moreira, L. C., Rosa, G. J. M. and Schaefer, D. Get more value from cull cows. Hoard’s Dairyman, April 10, p.220-221, 2020.
Rosa, G. J. M. Contribution to “Gene expression technical guide”. Genome Technology, November, 2010. (available also on line at http://www.genomeweb.com)
Steibel, J. P., Suchyta, S. and Rosa, G. J. M. Tackling high variability in gene expression studies. Genomics & Proteomics 5(1): 30-32, 2005.
An Sci/Dy Sci 361 – Introduction to Veterinary Genetics (2 credits, Spring)
Description: The molecular basis for inheritance of monogenic and polygenic traits related to animal disease and production. An introduction to the principles of improving animal health and performance by selection and mating systems in companion animals, horses, livestock, and poultry.
Requirements: Genetics 160 or 466 or con reg course in statistics
An Sci/Dy Sci 363 – Principle of Animal Breeding (2 credits, Spring)
Description: Application of the principles of quantitative genetics to the improvement of livestock and poultry; breeding value estimation and selection techniques; effects of inbreeding and hybrid vigor; crossbreeding systems.
Requirements: Dy Sci/AN SCI/DY SCI 361
An Sci/Dy Sci 610 – Quantitative Genetics (3 credits, Fall)
Description: An advanced approach with emphasis on statistical foundations. Classical theory with extensions to maternal and paternal effects. Selection theory is considered in depth.
Requirements: GENETICS 466and Statistics 572 or cons inst
Co-organizer, 1st International Symposium on Animal Functional Genomics, 2003.
Chair, NCR-204: The Interface of Molecular and Quantitative Genetics in Plant and Animal Breeding, 2005.
Co-organizer, 2nd International Symposium on Animal Functional Genomics, 2006.
Co-organizer, Symposium on Statistical Genetics of Livestock for the Post-Genomics Era, 2009.
Chair, Session on Genomics, XXV International Biometric Conference, 2010.
Member, Research Advisory Committee (RAC) – UW, 2011-2012
Member, Capital Equipment Committee, Department of Animal and Dairy Sciences, UW-Madison
Member, Prospective Students and Scholarships and Loans Committee, CALS, UW-Madison
Member, Steering Committee of the Brazil Initiative, University of Wisconsin-Madison
Co-organizer, 5th International Conference on Quantitative Genetics, Madison-WI, 2016.
Co-chair, Gordon Research Conference and Seminar on Quantitative Genetics and Genomics, 2019.
Ad-hoc Reviewer and Panel Member of various USDA-NIFA Research Grant Programs.
Ad-hoc Reviewer for various UW-Madison Hatch grants
Panel Member, NIH-NIDDK
Referee for various scientific journals including: Animal Genetics, Bioinformatics, Biometrical Journal, Biometrics, BMC Bioinformatics, BMC Genetics, Computational Statistics & Data Analysis, Frontiers in Genetics, Genetical Research, Genetics, G3, Genetics Selection Evolution, Heredity, Human Heredity, Journal of Agricultural, Biological and Environmental Statistics, Journal of Animal Science, Journal of Animal Breeding and Genetics, Journal of Clinical Epidemiology, Journal of Dairy Science, 2009 Journal of Heredity, Journal of the Royal Statistical Society, Livestock Science, Nuclei Acids, Physiological Genomics, PLoS ONE, Poultry Science, Shankia, Statistical Applications in Genetics and Molecular Biology, Veterinary Immunology and Immunopathology
Vilas Associate Award – University of Wisconsin-Madison (2010-11)
Founding Specialty Chief-Editor, Frontiers in Genetics | Livestock Genomics,
LeClerg Rotary Lecturer – Biometrics Program, University of Maryland (2011)
Pond Research Award – College of Agricultural and Life Sciences, University of Wisconsin-Madison (2013)
Visiting Fellow – Technical University of Munich, Germany (2015)
Rockefeller Prentice Memorial Award in Animal Breeding and Genetics – American Society of Animal Science (2016)
Vilas Faculty Mid-Career Investigator Award – University of Wisconsin-Madison (2017-18)
Excellence in International Activities Award – College of Agricultural and Life Sciences, University of Wisconsin-Madison (2017)
Keynote Speaker – KSU Conference on Applied Statistics in Agriculture (2018)
Plenary Speaker – 64th Annual Meeting of the Brazilian Region (RBRAS) of the International Biometric Society (2019)
Founding Specialty Chief-Editor, Frontiers in Animal Science | Precision Livestock
Kellett Mid-Career Award – University of Wisconsin-Madison (2021-22)
Keynote Speaker – Conference on Applied Statistics in Agriculture and Natural Resources (2022)