Satyarth is a robotics graduate with a computer science background, applied machine learning research experience, and a weird fascination with space science and technology. He carries experience from robotics, the autonomous vehicle industry, remote sensing, and academic teaching, with a skillset in computer vision and deep learning subdomains.
His most recent research has been with NASA Frontier Development Laboratory (FDL 2021). He worked as a machine learning researcher with Lockheed Martin on their Geostationary Lightning Mapper (GLM) to upgrade its Lightning detector using machine learning on the raw L0 data. For the previous year (FDL 2020), he worked with the Marshal Space Flight Center to build a reverse image search prototype for the massive NASA Earth Observation Archives, which extended further as a part of the SpaceML initiative. He continues to contribute and mentor teams at SpaceML to make the project more “Technology Ready.” He has also worked with the UK Space Agency on the Machine Learning for Climate Change (ML4CC) Program to develop an MLOps pipeline to better process/predict/learn from the remote sensing flood data.
His research interests lie in artificial intelligence applications, mainly in the subdomains of robotics, Earth Science, and Space Science. In addition to the scientific and technological fascinations, he also enjoys the superhero world (Marvel/DC) and is always up for an exciting conversation.