I am a data scientist with over eleven years of experience working in research and data analysis.  I have a Ph.D. in Statistics from Rutgers University and previously worked as an Assistant Research Professor in the Department of Earth and Planetary Sciences. I consider myself a climate data scientist, working to create novel solutions to complex problems using machine learning and Bayesian statistics. My research focuses on developing and employing spatio-temporal hierarchical models which aim to separate physical processes that drive sea-level change using instrumental data and proxy sea-level records with temporal and vertical uncertainties. These models help constrain future sea-level rise to inform decision-making under uncertainty and quantify risk.  I have demonstrable success creating high-quality, original, cross-disciplinary research with publications in peer-reviewed journals, such as Science, Nature, and Current Climate Change Reports.

I have a unique background, with experience in management consulting, education, sales, and academia, making me a creative and collaborative multi-disciplinary researcher. I work with geologists, oceanographers, and earth scientists all over the world to draw conclusions from complex and sparse data. I am motivated by solving consequential problems with sophisticated tools to find patterns and meaning from a wide variety of data sources and scientific fields.

Outside of my work, I enjoy hiking, snowboarding, scuba diving, camping, international travel, and designing a diverse variety of creations in my home.