Mahya is a Research Scientist at the Hydrological Sciences Laboratory at NASA Goddard Space Flight Center, working with SAIC. Her primary focus is leveraging satellite observations, particularly SAR data (Sentinel-1 and NISAR), combined with advanced AI techniques for precision agriculture. Her work encompasses estimating vegetation water content at high spatial and temporal resolutions, monitoring crop growth stages and health, and forecasting crop yields.
At NASA, Mahya is also contributing to global riparian zone delineation and evaluating their impacts on freshwater quality, biodiversity, flood risk reduction, and carbon sequestration. She utilizes cutting-edge deep learning models, self-supervised learning, and foundation models to map these areas. Additionally, she integrates data from newly developed NASA satellites, such as ECOSTRESS and PACE, for freshwater quality assessments and GEDI for carbon estimation.
In October 2024, Mahya earned her Ph.D. from Michigan State University (MSU) under the mentorship of Dr. Narendara Das. During her time at MSU, she was actively involved in the NASA SERVIR project, where she worked on a coupled hydrological and crop modeling framework (RHEAS) to utilize the estimated SAR-based rice paddy planting dates to improve yield predictions using the DSSAT crop model compared to traditional crop calendars. Furthermore, she developed innovative deep learning approaches, including 3D-CNNs, vision transformers, and self-supervised learning with foundation models, for agricultural applications such as crop attribute detection, yield estimation, and crop biophysical parameters assessments.
Mahya's work bridges cutting-edge satellite technologies and AI to address critical challenges in agriculture and environmental monitoring.