Simon Danny Pettinella
Papers
1
Total Citations
3
H-Index
1
About
Simon Danny Pettinella is an emerging leader in veterinary epidemiology and precision livestock farming, with a core focus on integrating artificial intelligence into animal health surveillance. His most cited work, a 2025 field trial on automated detection and scoring of pleurisy in Norwegian slaughtered pigs, demonstrates his pioneering contribution to transforming abattoir inspections. By developing and validating an AI-based system to identify lesions caused by *Actinobacillus pleuropneumoniae*, Pettinella has shown that machine learning can reliably replace manual scoring, enabling large-scale, objective monitoring of respiratory disease. This innovation directly addresses a critical bottleneck in porcine health management, offering a scalable tool for real-time surveillance that can improve both animal welfare and production efficiency. With 3 citations already, his research is gaining traction among veterinary scientists and agritech developers. Pettinella’s work stands out for its practical field application, bridging the gap between computational methods and on-the-ground veterinary practice, and positions him as a key contributor to the future of data-driven animal disease control.
Research Focus
Key Achievements
Top Papers
- 1