Function and Responsibilities:

My research is dedicated to applying machine learning methods to Earth observation and remote sensing, with a focus on Global Navigation Satellite System Reflectometry (GNSS-R). I specialize in integrating advanced machine learning methods to analyze and interpret GNSS-R signals, developing algorithms that improve the understanding of Earth’s surface and atmospheric processes. These include measuring ocean surface wind speeds, especially under extreme conditions such as hurricanes, and monitoring terrestrial variables such as soil moisture and vegetation parameter variations.

Career:

Doctoral Candidate, Technical University of Munich, Munich, Germany
Doctoral Candidate, German Aerospace Center (DLR), Oberpfaffenhofen, Germany, 2024

Education:

M.Sc. Geomatics Engineering, Unversity of Stuttgart, Stuttgart, Germany, 2018

Projects:

Artificial Intelligence for GNSS Reflectometry (AI4GNSSR)

Research Boards and Committees:

Member of Global Geodetic Observing System (GGOS) Study Group "AI for GNSS Remote Sensing"

Member of IAG Working Group 4.3.10 "Remote sensing using GNSS reflected signals"