Sequoia is interested in developing and applying statistical methods to real-world problems related to social good, including wildland fires and social justice. Prior to joining UC Berkeley as a student, she worked as a research engineer at NASA Ames Research Center with a focus on statistical and machine learning applications to wildland fire operations and safety. Her research there included developing and deploying custom natural language processing and pre-trained computer vision models. Most recently, she has worked on the Open Data Integration for Wildland Fire project (ODIN). During her Master's program, she completed a thesis on prescribed and wildland fires in the changing California Climate. She is also an awardee of the National Science Foundation Graduate Research Fellowship Program (NSF GRFP).
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