About
I’m a postdoctoral fellow at the Environmental Data Science Innovation & Impact Lab (ESIIL), an NSF data synthesis center at CU Boulder. As part of my ESIIL fellowship, I’m a member of the Boettiger Lab. Starting Fall 2026, I’ll be a postdoctoral researcher at the Eric and Wendy Schmidt Center for Data Science & Environment (DSE) at UC Berkeley.
I hold a PhD in operations research from Drexel University, with a graduate minor in computational data science, and a BS in mathematics from the University of Utah. My early research focused on nonlinear optimization, developing algorithms to solve large-scale problems in machine learning. Midway through my PhD, I became concerned about how AI was being used and looked for ways to apply my expertise with clearer public benefit, which led me to environmental science.
Research
My research develops mathematical optimization and AI methods for conservation and natural resource decision-making. I codevelop open-source decision-support tools with practitioners and stakeholders, with attention to how such tools shape policy and practice. This work combines LLMs with optimization to make complex spatial data usable, helping users prioritize where to protect land, where to invest, and how to track policy progress. Recent projects span state, regional, and national scales, including California’s 30x30 assessment with the California Biodiversity Network, conservation prioritization in the Greater Yellowstone Ecosystem, and investment guidance with the Trust for Public Land.
I’m always interested in new collaborations that bring methods and practice together on real-world environmental problems.