Joao Dorea
Credentials: Assistant Professor, Departments of Animal and Dairy Sciences and Biological Systems Engineering
Position title: Departments of Animal and Dairy Sciences and Biological Systems Engineering
Email: joao.dorea@wisc.edu
Joao Dorea’s academic career has been influenced by his farm and industry experience. He grew up on a family dairy farm in northeastern Brazil and, after earning his Ph.D., spent two years working in industry, where he learned about artificial intelligence (AI) applications in agriculture. He returned to academia as a postdoc, studying sensing technology and data analyses for precision agriculture. Now a UW-Madison faculty member, Joao applies machine learning and digital technologies to help dairy farmers make optimized day-to-day decisions.
Joao and his students leverage innovation in data science to improve dairy farm management and animal production, health, and welfare. Working in places that have limited or no access to high-speed internet, Joao uses wearable sensors, cameras, and robots to collect individual animal information in large-scale settings, which demands optimized systems to process and store large datasets. He collaborates closely with partners in computer sciences, biology, genetics, and other fields to accelerate his research.
Labor shortages have become a major constraint in many industries, including dairy. Joao uses data science to enhance, but not replace, labor by helping employees follow protocols and communicate with managers. Many dairy workers may not have farm experience or speak English. Using sensors to monitor animals 24/7 and natural language processing to insert audio data into farm management software can improve worker performance.
“I finished my Ph.D. with many ideas, but when I went to industry, I realized how difficult is to implement something developed under a controlled environment. The human component and all the environmental conditions that you cannot control have a huge impact on results. That’s exactly why we develop research using large-scale farm data to develop digital solutions that can be implemented in commercial farms.”