New voices in AI: machine learning insights on Earth's nightlights with Srija Chakraborty

Welcome to episode 10 of New voices in AI. This time we hear from Srija Chakraborty about her work using ML with large data sets to understand what happens on Earth at night. I am a researcher at the Earth from Space Institute, Universities Space Research Association, working on applied machine learning techniques for remote sensing datasets with the Black Marble Science team. Before this, I completed my doctoral studies at Arizona State University studying machine learning and statistical signal processing approaches for remote sensing applications and then held a NASA Postdoctoral Program Fellowship at Goddard Space Flight Center, working on machine learning techniques for nighttime remote sensing. I currently work with the Black Marble dataset, which captures the Earth at night from space with the VIIRS instrument (Visible Infrared Imaging Radiometer Suite) onboard the Suomi-NPP and NOAA-20 satellites.