Ahmed Kayad
Ahmed Kayad is an agricultural engineer advisor for applied research and extension at the University of California, Agriculture & Natural Resources (UC ANR), United States. He holds a PhD in environment resources?digital agriculture from the University of Padova in Italy, awarded in 2021. His academic journey began with a BSc in agricultural engineering from Alexandria University, Egypt, followed by an MSc from King Saud University, Saudi Arabia. Ahmed's career has encompassed various roles,...See more
Ahmed Kayad is an agricultural engineer advisor for applied research and extension at the University of California, Agriculture & Natural Resources (UC ANR), United States. He holds a PhD in environment resources?digital agriculture from the University of Padova in Italy, awarded in 2021. His academic journey began with a BSc in agricultural engineering from Alexandria University, Egypt, followed by an MSc from King Saud University, Saudi Arabia. Ahmed's career has encompassed various roles, including serving as a farm machinery engineer at CLAAS agent in Egypt from 2010 to 2011, conducting research at the Precision Agriculture Research Chair (PARC) at King Saud University, Saudi Arabia from 2011 to 2018, and pursuing doctoral and postdoctoral research at the Digital Agriculture Lab, University of Padua, Italy, from 2018 to 2022. Additionally, he was a visiting doctoral researcher at the International Maize and Wheat Improvement Center (CIMMYT), Mexico, in 2020, and pursued postdoctoral studies at the University of California, Riverside, United States, from 2022 to 2023. Ahmed published several articles in scientific journals and international conferences, primarily focusing on remote sensing in agriculture, precision agriculture, and digital agri?culture. His expertise extends to serving as an expert reviewer for prestigious funding agencies in Europe and the United States, particularly in projects related to digital and precision agriculture. Ahmed's research is centered on crop yield monitoring, weed detection, farm machinery, and the application of drones and sensors in agriculture. See less