I am a computational ecologist specializing in landscape-scale vegetation dynamics, phenology, and evolutionary-ecology. My work combines Bayesian statistical modeling, machine learning, and causal inference to analyze long-term climate data, remote sensing observations, and field measurements. In particular, I am investigating the role that phenological plasticity plays in driving heterogenous rates of response to global change and their effects on tundra ecosystems.
I am a PhD student in Ecology and Evolutionary Biology at the University of Colorado Boulder, working in the alpine tundra at the Niwot Ridge Long Term Ecological Research Site. I develop hierarchical Bayesian models and scalable data pipelines to investigate ecological and climatic drivers of plant phenology across individual and landscape scales. My expertise includes statistical computing in R, Python, Stan, and Julia, as well as geospatial analysis and high-dimensional data modeling.
Previously, I was a Professional Scientist at the Institute of Arctic and Alpine Research, where I built automated data pipelines to clean and publish long-term climate datasets. Before that, I worked as a Remote Sensing Data Analyst for NASA’s Arctic-Boreal Vulnerability Experiment (ABoVE) where I worked on an interdiscplinary project to collate data from a joint field and airborne synthetic aperature radar campaign.