Genevieve Makowski
Papers
1
Total Citations
12
H-Index
1
About
Genevieve Makowski is a rising leader in the intersection of precision agriculture and animal science, with a primary focus on leveraging machine learning to enhance livestock welfare and productivity. Her key research areas include behavioral phenotyping, thermotolerance in dairy cattle, and the development of automated monitoring systems for agricultural applications. Makowski’s most notable contribution is her pioneering work on a machine learning-based approach for the automatic characterization of behavioral phenotypes in dairy cows relevant to heat stress. This research addresses a critical challenge: the United States is projected to see annual milk production declines of 1.4 to 1.9 kg per cow per day by the 2050s and 2080s due to heat stress, with economic losses reaching USD 1.7 billion and USD 2.2 billion, respectively, despite current cooling efforts. By enabling early detection of heat-stressed behaviors, her work offers a scalable, data-driven solution to mitigate these losses. With her 2024 paper already garnering 12 citations, Makowski’s innovative approach is gaining traction among researchers and industry stakeholders, positioning her as a key contributor to sustainable dairy farming in a warming climate.
Research Focus
Key Achievements
Top Papers
- 1