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Jihao You


Position/Title: Postdoctoral Fellow
email: jyou03@uoguelph.ca
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Current Research Projects

I'm currently working as a post-doctoral fellow under Dr. Jennifer Ellis (supervisor) and Dr. Dan Tulpan (co-supervisor). My research project is "Automation of the Modern Commercial feed mill - Optimization of Pellet Quality using Machine Learning- 2.0" funded by OMAFRA. The objective of this project is to further investigate the relationship between nutrition, manufacturing and environmental factors and pellet quality using machine learning and data analysis approaches. This project builds on our previous project ("Optimization of Pellet Quality a the Mill Level using Machine Learning") by taking the next major step: expanding involvement to include additional feed mills from multiple companies across Ontario. We aims to create a robust and versatile machine learning system to predict PDI across Ontario mills and develop an optimization algorithm to support decision-making when using the model. To achieve the goal, we are collaborating with partners from feed industry, including Trouw Nuturition Canada, Molesworth Feed Supply, MasterFeeds (Canada), and Jones Feed Mills. Additionally, I'm working on developing a dynamic and mechanistic model for turkey growth and metabolism, in collaboration with Hendrix Genetics.

 

Research Interest

My research interest is applying data science and various modeling approaches—such as machine learning, mechanistic modeling, and statistical modeling—to address challenges in animal production systems and feed manufacturing processes. By leveraging predictions, strategies, and data-driven decisions, my work aims to enhance the efficiency of animal production and feed manufacturing, minimize their environmental impact, and improve economic outcomes.

 

Academic History

  • Ph.D. in Animal Biosciences, University of Guelph (2021 - 2024)
  • M.Sc. in Animal Science, University of Alberta (2019 - 2020)
  • M.Sc. in Animal Sciences, Nanjing Agricultural University, China (2010 - 2013)
  • Bachelor's in Animal Science, Shanxi Agricultural University, China (2006 - 2010)

 

First-author Publications

  • You, J., Ellis, J. L., Tulpan, D., & Malpass, M. C. (2024). Review: recent advances and future technologies in poultry feed manufacturing. World's Poultry Science Journal, 1-13. 
  • https://doi.org/10.1080/00439339.2024.2323536
  • You, J., Ellis, J. L., Adams, S., Sahar, M., Jacobs, M., & Tulpan, D. (2023). Comparison of imputation methods for missing production data of dairy cattle. animal, 17, 100921. https://doi.org/10.1016/j.animal.2023.100921
  • You, J., Tulpan, D., Malpass, M. C., & Ellis, J. L. (2022). Using machine learning regression models to predict the pellet quality of pelleted feeds. Animal Feed Science and Technology, 293, 115443. https://doi.org/10.1016/j.anifeedsci.2022.115443
  • You, J., Lou, E., Afrouziyeh, M., Zukiwsky, N. M., & Zuidhof, M. J. (2021). Using an artificial neural network to predict the probability of oviposition events of precision-fed broiler breeder hens. Poultry Science, 100(8), 101187. https://doi.org/10.1016/j.psj.2021.101187
  • You, J., Lou, E., Afrouziyeh, M., Zukiwsky, N. M., & Zuidhof, M. J. (2021). A supervised machine learning method to detect anomalous real-time broiler breeder body weight data recorded by a precision feeding system. Computers and Electronics in Agriculture, 185, 106171. https://doi.org/10.1016/j.compag.2021.106171
  • You, J., van der Klein, S. A., Lou, E., & Zuidhof, M. J. (2020). Application of random forest classification to predict daily oviposition events in broiler breeders fed by precision feeding system. Computers and Electronics in Agriculture, 175, 105526. https://doi.org/10.1016/j.compag.2020.105526

 

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