AI in the sky | Folio

Abigail Azari is an assistant professor specializing in using AI to study and interpret data from satellites for planetary science applications.
She aims to advance the integration of AI and machine learning in interpreting vast data for better understanding planetary systems and space weather phenomena.
The University of Alberta’s Upper Bound initiative, supported by a $30 million investment from the Canadian Institute for Advanced Research, seeks to bring together top AI minds from various disciplines.
Her research employs a “physics-informed” machine learning approach to discard physically improbable models and prioritize more likely solutions.
Understanding space environments and their dynamics through AI-enhanced models helps predict significant space weather phenomena that might affect Earth, such as auroras, radiation storms, and geomagnetic storms.
Azari’s research is crucial for prioritizing data collection from space, helping to select what observations satellites should capture when full data retrieval is impossible due to various constraints.
Her work is also relevant to studying the space environment of Mars and understanding its magnetic fields’ role in the planetary space environment’s history and evolution.
Ultimately, Azari aims to improve the use of machine learning to answer fundamental physics questions that were previously unanswerable, combining these methods with physical understanding.