Nikoo Sabzevar has a Ph.D. in Mechanical Engineering from the University of Calgary -Institute for Sustainable Energy, Environment, Economy. Her interdisciplinary thesis focused on the application of machine-learning and game-theory on the economic and environmental implications of replacing fossil fuels with renewables under demand uncertainty. At the University, she taught statistics, operations-research, optimization, and experimental design to both graduate and undergraduate students.Her background and experiences have contributed to her job as the Lead Data Scientist at Skymatics. In her current research, she is developing novel models and algorithms using machine learning, computer vision, and data science tools to help farmers and insurers inspect damaged crops faster, easier, and with more efficiency. She is currently building a neural network to predict crop type, damage type, and growth stage with aerial imagery as inputs, quantify incurred crop damage and report relative damage severity of every single point in the scene.