Igor Geyn, PhD

I work on problems where careful measurement matters and the data is rarely clean, including wildfire and energy risk, elections, education, workforce policy, and product decisions in industry.

My work combines causal inference, statistical modeling, machine learning, survey research, and data engineering to make messy institutional data usable. I have published peer-reviewed research on elections and education, built risk analysis for a major California utility, and worked across large enterprises, research institutions, public-policy settings, and startups.