I am a consulting data scientist that specializes in physical climate and natural hazards. I build and use computational and statistical tools to inform resilience decision-making for businesses, investors, NGOs, and governments.

I have studied climate change and natural hazards and resilience strategies (to mitigate their impacts) since 2010, publishing over a dozen peer-reviewed articles, reports, and books on probabilistic climate risk assessment, climate adaptation decision-making, and assessments of relevant public policies. I also regularly peer review climate risk research.

A central aspect of my work is applying academic research and cutting-edge statistical methods to help solve "real world" problems that clients are faced with. I also seek to scale up applications of this knowledge using user-friendly digital tools to incorporate natural hazard and climate risks into risk management, risk disclosure, and resilient infrastructure planning. My hope is that these efforts will better price risks, encourage investment in resilience, limit business and governance disruptions, maintain positive reputations, and improve overall human well-being.

I currently a consultant within the Risk and Resilience Team at ARUP, a firm that provides design, engineering, architecture, planning, and advisory services for the built environment.

I am a contributing author of American Climate Prospectus: Economic Risks in the United States. I previously was a research fellow at the National Oceanic and Atmospheric Administration’s (NOAA) Geophysical Fluid Dynamics Laboratory (GFDL). I also served as an air pollution engineer at both the California Air Resources Board and Ramboll.

I completed my PhD in the Science, Technology, and Environmental Policy (STEP) Program at the School of Public and International Affairs at Princeton University. I received an MS in civil and environmental engineering from the University of California-Davis and a BS in atmospheric and oceanic science from UW-Madison.