Ramesh Bahadur Bist
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Assistant Professor
Also affiliated: North Carolina State University (2025–2026); University of Georgia (2022–2025); University of Arkansas System (2026); U.S. National Poultry Research Center (2025)
Faculty Researcher
Research Areas
Biomedical Subjects
Links
Biography and Research Information
OverviewAI-generated summary
Ramesh Bahadur Bist is an Assistant Professor at the University of Arkansas at Fayetteville whose research focuses on the application of computer vision and deep learning technologies to animal welfare and production systems, particularly within poultry farming. His work investigates methods for automatically monitoring animal behavior, such as tracking pecking behaviors and detecting mislaying or piling behaviors in cage-free laying hens. Bist also develops systems for automated egg grading and defect detection. His research addresses environmental concerns in poultry production, including ammonia emissions and mitigation strategies, and explores sustainable farming practices. He has published extensively in these areas, with metrics including an h-index of 18, 68 total publications, and 1,176 total citations. Bist collaborates with several researchers at the University of Arkansas at Fayetteville, including Chaitanya Pallerla, Siavash Mahmoudi, Dongyi Wang, and Amirreza Davar.
Metrics
- h-index: 19
- Publications: 72
- Citations: 1,253
Selected Publications
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Portable electrochemical impedance biosensing with DRT-enabled machine learning for detecting E. coli O157:H7 in poultry meat (2026)
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Smartphone-enabled Depth-aware Transillumination Imaging for Detection of Chicken Breast Fillet Myopathies in Chicken Fillets (2026)
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Thermal imaging-guided detection of transparent plastic contaminants on chicken breast: A combined vision and simulation approach (2025)
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Automated Detection of Kinky Back in Broiler Chickens Using Optimized Deep Learning Techniques (2025)
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Deep-Learning-Enhanced Automated Coherent-Light Diffraction System for High-Speed, Highly Accurate Strain-Specific Foodborne Bacterial Recognition (2025)
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Enhancing Poultry Multi-Behavior Detection with Semi-Supervised Auto-Labeling and Prompt-Driven Zero-Shot Recognition (2025)
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Neural network architecture search enabled wide-deep learning (NAS-WD) for spatially heterogenous property awared chicken woody breast classification and hardness regression (2024)
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Leveraging imitation learning in agricultural robotics: a comprehensive survey and comparative analysis (2024)
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Sustainable poultry farming practices: a critical review of current strategies and future prospects (2024)
Collaboration Network
Top Collaborators
- Leveraging imitation learning in agricultural robotics: a comprehensive survey and comparative analysis
- Neural network architecture search enabled wide-deep learning (NAS-WD) for spatially heterogenous property awared chicken woody breast classification and hardness regression
- Leveraging imitation learning in agricultural robotics: a comprehensive survey and comparative analysis
- Neural network architecture search enabled wide-deep learning (NAS-WD) for spatially heterogenous property awared chicken woody breast classification and hardness regression
- Leveraging imitation learning in agricultural robotics: a comprehensive survey and comparative analysis
- Neural network architecture search enabled wide-deep learning (NAS-WD) for spatially heterogenous property awared chicken woody breast classification and hardness regression
- Leveraging imitation learning in agricultural robotics: a comprehensive survey and comparative analysis
- Neural network architecture search enabled wide-deep learning (NAS-WD) for spatially heterogenous property awared chicken woody breast classification and hardness regression
- Leveraging imitation learning in agricultural robotics: a comprehensive survey and comparative analysis
- Neural network architecture search enabled wide-deep learning (NAS-WD) for spatially heterogenous property awared chicken woody breast classification and hardness regression
- Neural network architecture search enabled wide-deep learning (NAS-WD) for spatially heterogenous property awared chicken woody breast classification and hardness regression
- Neural network architecture search enabled wide-deep learning (NAS-WD) for spatially heterogenous property awared chicken woody breast classification and hardness regression
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