Maosi Chen - Homepage

My academic background combines geographical information systems (GIS) and remote sensing, providing a strong foundation for analyzing spatial data. This foundation fueled my pursuit of expertise in atmospheric science and ecology.

One of my core areas involves ensuring the quality of data collected by a ground-based radiometer, instrumental for atmospheric characterization. Additionally, I leverage remote sensing data, from both ground stations and satellites, to extract information on atmospheric constituents and Earth’s surface characteristics. Furthermore, my research interests extend to ecosystem modeling.

One of my goals is to bridge the gap between large-scale, remote sensing data and the fine-grained processes governing our planet. This is where machine learning becomes particularly relevant. I believe these data-driven algorithms have the potential to analyze vast datasets, offering deeper insights into the intricate interactions between ecosystems and the atmosphere they depend on. It is an honor to be a researcher at this pivotal time, where innovative technologies are poised to revolutionize our understanding of Earth’s complex systems.