Amir received his bachelor’s degree in chemical engineering from Guilan University in Rasht, Iran and joined RIT and the Imaging Science program in 2017. Amir joined the DIRS group in September 2018 and started working under the supervision of Jan van Aardt. He currently works on yield modeling and harvest scheduling of snap-bean, as a proxy crop using sUAS and remote sensing approaches. His research interests are precision agriculture, remote sensing, hyperspectral data as well as machine learning and deep learning methods. Amir is also keen in briding remote sensing to deep learning. His research so far, up until summer 2019, involved a greenhouse study in RIT as well as field data collection using sUAS in Geneva, NY. His project is one that focuses on transitioning academia to industry by delivering packages to farmers and growers so they can rent a drone, set up the flight lines, sit and relax while watching the drone fly on its own, uploading the data to the software, have a cup of coffee, and take actions based on the given probability map.