Godstime Taiwo
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Also affiliated: New Mexico State University (2026); West Virginia University (2026)
Research Areas
Biomedical Subjects
Biography and Research Information
OverviewAI-generated summary
Godstime Taiwo's research investigates the intersection of animal nutrition, physiology, and computational modeling to enhance livestock production. His work explores how dietary interventions, such as supplementation with Lactobacillus reuteri and microfused essential oils, impact the plasma metabolome and growth performance in ewes and steers. Taiwo also studies the relationship between residual feed intake phenotypes and ruminal microbiome responses in beef steers, as well as the transcriptomic signatures associated with divergent growth phenotypes. His research extends to developing advanced predictive models, including generalizable long short-term memory models for predicting dry matter intake in beef cattle under grazing conditions, utilizing machine learning and MLOps principles. He has published on topics ranging from microbial community ecology to advanced neural network applications in animal agriculture.
Metrics
- Publications: 8
Selected Publications
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Deployable DMI prediction using GPBoost, MLOps, and flask without the need for exact birth dates (2026)
Collaboration Network
Top Collaborators
- Deployable DMI prediction using GPBoost, MLOps, and flask without the need for exact birth dates
- Deployable DMI prediction using GPBoost, MLOps, and flask without the need for exact birth dates
- Deployable DMI prediction using GPBoost, MLOps, and flask without the need for exact birth dates
- Deployable DMI prediction using GPBoost, MLOps, and flask without the need for exact birth dates
- Deployable DMI prediction using GPBoost, MLOps, and flask without the need for exact birth dates
- Deployable DMI prediction using GPBoost, MLOps, and flask without the need for exact birth dates
- Deployable DMI prediction using GPBoost, MLOps, and flask without the need for exact birth dates
- Deployable DMI prediction using GPBoost, MLOps, and flask without the need for exact birth dates
- Deployable DMI prediction using GPBoost, MLOps, and flask without the need for exact birth dates
- Deployable DMI prediction using GPBoost, MLOps, and flask without the need for exact birth dates
- Deployable DMI prediction using GPBoost, MLOps, and flask without the need for exact birth dates
- Deployable DMI prediction using GPBoost, MLOps, and flask without the need for exact birth dates
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