Tyler Nigon is a Principal Scientist at Sentera, whose analytics solutions primarily use remote sensing, GIS, and machine learning to turn raw agricultural data into valuable insights for agricultural businesses. Tyler grew up on a dairy farm in Greenwood, WI, where he finds much of his inspiration for applying agronomic technologies to solve real-world agricultural problems. He holds a B.S. degree in Soil Science and Geographic Information Systems from the University of Wisconsin-Stevens Point (2010), as well as M.S. and Ph.D. degrees in Land and Atmospheric Science from the University of Minnesota (2012 and 2021). His Masters and PhD research projects mainly focused on the use of hyperspectral aerial imagery and machine learning modeling for predicting crop nitrogen status (in corn and potato).