Srinivas Sridharan, Ph.D.: Computer Vision and Machine Learning Applications in Agriculture at Corteva
Friday, October 19 at 12 p.m. in IT 252
Agriculture today has changed drastically in the past few decades due to ever growing demands to feed an increasing population. At Corteva we aim to enrich the lives of those who produce and those who consume, ensuring progress for generations to come. Our customers are posed with multiple challenges that limit the yield and quality potential of our seed products. There is a great need to apply science and technology to develop integrated solutions to feed the world.
Robust, ubiquitous and low-cost cameras paired with powerful computer vision and machine learning algorithms can be leveraged across wide applications in modern agriculture. At Corteva, a variety of imaging platforms are utilized, such as microscopes, point-and-shoot cameras, hyperspectral/florescence imagers, satellites, and LIDARs, to phenotype our germplasm in lab and field environments. We apply image analysis techniques including augmentation, classification, detection, segmentation to measure efficacy of insect control treatments, genetic factors, and environmental conditions. In this talk I will give a broad overview of imaging in agriculture, a brief introduction to the deep learning revolution, and examples of how we utilize these techniques to augment our research pipeline.
About Srinivas Sridharan
Srinivas Sridharan joined Corteva Agrisciences in 2017 as a Data Scientist in the Image Analytics and Computer Vision group. Before that, he was working as an assistant professor in the computer science department at Stevens Institute of Technology, Hoboken, NJ. Srinivas received his Master’s in Electrical Engineering and Ph.D. in Computing and Information Sciences from Rochester Institute of Technology, Rochester, NY. His Ph.D. dissertation focused on machine learning and applied perception in computer vision and computer graphics. Before coming to US, Srinivas worked as a senior software engineer in India and Germany for Hexaware and Infosys Technologies Limited. His research interests are machine learning, deep learning, computer vision, and virtual and augmented reality for 3D graphics and visualization.