Area of research
Atmospheric Science · Astronomy and Astrophysics
Research interest
Research focused on Radiative transfer and Construct (python library), with related work in Artificial neural network, Planet, Field (mathematics). Notable publications include 'Accurate Machine-learning Atmospheric Retrieval via a Neural-network Surrogate Model for Radiative Transfer', 'Characterizing a World Within the Hot-Neptune Desert: Transit Observations of LTT 9779 b with the Hubble Space Telescope/WFC3', and 'Integrating Machine Learning for Planetary Science: Perspectives for the Next Decade'.