Ahmed Rady
Research leaders 2025 FellowResearch Interests
I am an agricultural engineer and I am interested in:
- Applying non-invasive and/or rapid sensors coupled with machine learning for food quality evaluation, food fraud, and food safety
- Process Analytical Technology (PAT),
- Digital agriculture,
- Reducing food losses,
- Postharvest technology
Google Scholar:
https://scholar.google.com/citations?user=B3EUTE0AAAAJ&hl=en
Researchgate:
https://www.researchgate.net/profile/Ahmed-Rady-13
LinkedIn: https://www.linkedin.com/in/ahmed-rady-1444b620/
Current Projects
Digital technologies for advanced quality monitoring of traditional processed meats and innovative alternatives
https://www.teagasc.ie/about/research--innovation/research-leaders-2025/funded-projects/digi-meat/
Education
- PhD. (2014) in Biosystems Engineering, Michigan State University, East Lansing, MI, USA
- M.Sc. (2006) in Agricultural Engineering, Alexandria University, Alexandria, Egypt
- B.Sc. (1998) in Agricultural Engineering, Alexandria University, Alexandria, Egypt
Professional Membership
American Society of Agricultural and Biological Engineering (ASABE): member since 2009
Adedeji, A. A., Okeke, A., Rady, A.M. Utilization of FTIR and Machine Learning for Evaluating Gluten-free Bread Contaminated with Wheat Flour. (2023). Sustainability, 15(11), “Sustainable Food Processing Safety and Public Health, 8742; https://doi.org/10.3390/su15118742.
Fisher, O., Rady, A.M., El Sawi, A., Watson, N.J., Hussien, H. (2022). An image processing and machine learning solution to automate Egyptian cotton lint grading. Textile Research Journal, 00405175221145571.
Ozturk, S., Bowler, A. L., Rady, A., & Watson, N. (2023). Near-infrared Spectroscopy and Machine Learning for Classification of Food Powders Under Moving Conditions. Journal of Food Engineering, 341 (111339).
Rady, A., & Watson, N. J. 2022. Detection and Quantification of Peanut Contamination in Garlic Powder using NIR Sensors and Machine Learning. Journal of Food Composition and Analysis, 114, 104820, https://doi.org/10.1016/j.jfca.2022.104820.
Hou, YinChen; Zhao, PengHui; Zhang, Fan; Yang, Sheng Ru; Rady, Ahmed; Wijewardane, Nuwan K. ; Huang, Jihong; Li, Mengxing. 2022. Fourier-transform infrared spectroscopy and machine learning to predict amino acid content of nine commercial insects. Food Science and Technology, 42: 1-7, https://doi.org/10.1590/fst.100821.
Rady, A., Adedeji, A., Watson, N.J. Feasibility of Utilizing Color Imaging and Machine Learning for Adulteration Detection in Minced Meat. 2021. Journal of Agriculture and Food research, Special Issue: Food Safety Engineering, 6: 1-11, https://doi.org/10.1016/j.jafr.2021.100251.
Liu, Z., Rady, A., Wijewardane, N. K., Shan, Q., Chen, H., Yang, S. & Li, M. 2021. Fourier-transform infrared spectroscopy and machine learning to predict fatty acid content of nine commercial insects. Journal of Food Measurement and Characterization, 15(1), 953-960, https://doi.org/10.1007/s11694-020-00694-9.
Rady, A.M., Guyer, D.E., Watson, N.J. 2020. Near-infrared Spectroscopy and Hyperspectral Imaging for Sugar Content Evaluation in Potatoes over Multiple Growing Seasons. Food Analytical Methods, https://doi.org/10.13031/trans.12548.
Rady, A.M. 2022. Quality Evaluation of Processed Meats Using Rapid and/or Non-invasive Sensors and Machine Learning Algorithms, the 37th EFFoST International Conference 2023, Dublin, Ireland (Oral presentation).
Rady, A.M., Adedeji, A. 2022. Hyperspectral Imaging and Deep Learning for Evaluating Adulteration in Meats, the 37th EFFoST International Conference 2023, Dublin, Ireland (Poster).