My research focuses on developing and implementing advanced computational algorithms and statistical models to integrate high-dimensional -omics data, driving advancements in animal health and productivity. I specialize in multi-omics data integration, large-scale data analysis, and causal network modeling, with a strong emphasis on artificial intelligence (AI) and machine learning (ML) to address complex biological questions. With interdisciplinary experience spanning both animal and human data, I leverage AI and ML to unravel the genetic complexity of traits and diseases, particularly in predictive analytics and precision livestock farming (PLF). By integrating multi-omics data with predictive modeling, my work enhances real-time decision-making in animal systems, addresses modern agricultural challenges, and provides innovative tools to support precision farming and advance animal health sciences.