Agriculture: The Next Machine-Learning Frontier

Monday, November 7, 2016 - 11:20 am

In the past decade the high-tech industry has been revolutionized by machine learning algorithms applied to everything from self-driving cars to personalized recommendation systems in domains such as healthcare and marketing.

Agriculture is a less familiar research domain among the machine learning community. Nevertheless, this domain offers unique and challenging scientific opportunities related to the spatio-temporal nature of the data, the multi-resolution data sources, the interaction with environmental models.

In this talk, I will introduce The Climate Corporation and how its using Data Science to tackle some of the most challenging problems growers face these days. Furthermore, I will present a few of our ongoing research projects in the fields of agronomy, remote sensing and weather modeling and our philosophy of solving these problems.

Director of Data Science
Data Science Center for Excellence for The Climate Corporation

Sivan is a Director of Data Science for the Data Science Center of Excellence for The Climate Corporation. In this capacity, Sivan and her team are supporting the development of innovative data-driven solutions to help growers optimize their operations across the globe. In addition, as part of her role Sivan is helping to develop and adopt best-practices for leading Data Science teams.

Sivan began her career in the Israeli military serving as an instructor for an anti-tank missile unit. She then transitioned to school and received her undergraduate degree in Industrial Engineering and a Master in Statistics from the Technion, Israel Institute of Technology. She later moved to the U.S. to complete a Ph.D. degree in Statistics from The Wharton School, University of Pennsylvania.

Sivan’s experiences from the military, academia and private industry shaped her leadership style. She is an enthusiastic disagreeable giver and a constant empirical driven learner. Sivan is also a proud mother of two adorable boys.