I am a NASA Postdoctoral Fellow at Goddard Space Flight Center and Universities Space Research Association. My research interest lies at the intersection of machine learning, statistical signal processing and remote sensing with applications in Earth and Planetary Sciences.

For my postdoctoral research I am designing algorithms using applied machine learning and signal processing for understanding and monitoring the Earth at night using NASA’s Black Marble dataset to advance the exciting area of nighttime remote sensing. Previously, I was a graduate student in Computer Engineering with Profs. Antonia Papandreou-Suppappola and Philip Christensen at Arizona State University focusing on modeling satellite image time-series for change and novelty detection in Earth and Planetary observations.

My projects are primarily centered around unsupervised learning, change, anomaly and novelty detection. These translate to a variety of research areas in remote sensing such as multitemporal analysis of multispectral datasets with applications in detecting and understanding Earth system changes, natural hazards and utilizing satellite observations for monitoring the variability over time. I am also utilizing machine learning for labeling and cataloging the growing volume of satellite observations.

Broadly, I am interested in studying global environmental change and leveraging satellite observations to enable monitoring and forecasting.

To get in touch please write to srija[dot]chakraborty[at]nasa[dot]gov or srija[dot]chakraborty[at]asu[dot]edu.