Bio

Originally from Wilmington, NC, Ben Rachunok is an assistant professor in the Edward P. Fitts Department of Industrial and Systems Engineering at NC State University. Broadly, Rachunok works in risk and decision analysis with applications in sustainability and climate change adaptation. More specifically, his research uses methods from simulation and data science to understand how communities respond to natural hazards and climate change. Much of his recent work quantifies the disproportionate impact of climate change and extreme events on low-income or historically disadvantaged communities.

Before (re)joining NC State, Rachunok made several contributions utilizing data science to study critical infrastructure. Notably quantifying the disproportionate impacts of droughts on low-income households in California and developing data science tools that utilize real-time social media data to quantify how communities are impacted by climate change and natural hazards. His work has been featured by Tech Crunch, Gizmodo, Yahoo! Finance, The Huffington Post, and the UN Office of Disaster Risk Reduction. Ben was formerly a Postdoctoral Researcher in the Civil and Environmental Engineering Department at Stanford University and an R&D intern at the Center for Computing Research at Sandia National Labs.

Area(s) of Expertise

Rachunok’s research integrates environmental justice and engineering principles to create climate change adaptation and mitigation strategies that benefit all populations.

Publications

• Advancing Systemic Risk Assessment for Complex, Interdependent Systems: A Research Agenda , Risk Analysis (2026)
• Anticipating Household Rescue Demand in Hurricanes Using Socio-Demographic Data and Machine Learning , SSRN Electronic Journal (2025)
• Leveraging the American Housing Survey to Quantify Risk and Resilience , Risk Analysis (2025)
• Alternative household water affordability metrics using water bill delinquency behavior , Environmental Research Letters (2024)
• Electric vehicles limit equitable access to essential services during blackouts , npj Sustainable Mobility and Transport (2024)
• Predicting and understanding residential water use with interpretable machine learning , Environmental Research Letters (2023)
• Socio-hydrological drought impacts on urban water affordability , Nature Water (2023)
• Socio-hydrological impacts of rate design on water affordability during drought , Environmental Research Letters (2023)
• Mapping climate discourse to climate opinion: An approach for augmenting surveys with social media to enhance understandings of climate opinion in the United States , PLoS ONE (2021)
• Overemphasis on recovery inhibits community transformation and creates resilience traps , Nature Communications (2021)