Sindhuja Sankaran, Associate Professor, Department of Biological Systems Engineering, Pullman, WA

Sankaran is working towards advanced sensing techniques for crop phenotyping applications and developing machine learning approaches for phenomic big data management. She is leading the phenomics aspect of two ongoing USDA-NIFA funded projects, where her focus is on developing high-throughput phenotyping tools for field and postharvest crop trait evaluation in cereal, legume, and specialty crops. Through these projects, Sankaran is contributing to training of next-generation researchers from several breeding programs.

Program Description:

High spectral and spatial resolution sensors are useful to detect and assess biologically relevant traits at micro- and macro- scales. With such technological sophistication, there is an inherent need to develop data mining approaches for sensible and functional data analysis. The projects focus on developing crop-specific data processing and analysis pipelines involving generic data mining and machine learning approaches for high-throughput and automated feature extraction from multiple sensors. The student will be trained on field data acquisition using unmanned aerial vehicle integrated with multiple sensors (multispectral/thermal) and development of data processing approaches to automate image analysis.

Location: Pullman, WA