Farshina is currently pursuing her Ph.D. in Electrical Engineering and her research focuses on the application of Machine Learning for resource optimization. Her recent work addresses the critical issue of irrigation water optimization in drought-prone regions like states of Montana, California and Kansas, employing innovative statistical and machine-learning techniques. Farshina’s solutions effectively bridge gaps in data frequency challenges, providing informed irrigation decisions for farmers. During her master’s program from 2018-2020, her focus was on automated power management in smart grids, emphasizing the enhancement of microgrid resiliency to prevent blackouts. Beyond her academic pursuits, Farshina actively engages in community services, advocating for underprivileged groups. Driven by a passion for solving complex problems, she aspires to make a meaningful societal impact through her ongoing research endeavors.