Rebecca Napolitano
Pennsylvania State University, PA·Engineering·Early-career
Old brick and stone buildings without steel reinforcement fill many small-town main streets and city neighborhoods. They carry a community's history, but no one knows well how they hold up when a tornado hits or how quickly their owners and towns recover.
- Fields
Engineering
Education Research
Social Science
- Topics
unreinforced masonry
tornado
disaster resilience
- Grants
- 3 known grants, through Dec 2030
What they work on
- Identify which structural, social and preservation features best predict tornado damage and recovery of unreinforced masonry buildings, using remote sensing, field surveys, socio-economic data and random forest and gradient boosting models.
- Develop updated fragility curves, which give the probability of damage at a given wind intensity, for unreinforced masonry buildings in tornadoes, using Bayesian statistics and Monte Carlo simulation.
- Convert industrial datasets on building cooling systems and advanced electronics into high school math modeling lessons, guided by a Data Translation Framework of selection rubrics, scaffolds and validation checklists.
- Distinguish productive struggle from unproductive frustration in about 4,500 high school students' modeling work, using learning-process event data, and report it to teachers through dashboards.
- Build transferable, plug-and-play data science lessons and curated datasets for engineering curricula across diverse institutions, co-developed with industry partners, community stakeholders and student organizations.
More about the research
Alongside this disaster-resilience research, Napolitano's work brings real, messy engineering data into classrooms, from high school math to undergraduate engineering. The aim is to teach students to reason with data and to study how they learn to do it.
Why it matters
Communities in tornado-prone parts of the United States could use better damage and recovery models, practitioner guides and tip sheets to prepare for storms. The same tools could help them protect older masonry buildings that anchor rural downtowns and city neighborhoods. On the education side, teachers could get dashboards that flag frustrated students, and researchers and ed-tech developers could use a large open dataset on math learning. Engineering programs could get ready-made data science lessons.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
CAREER: Integrating Structural, Social, and Preservation Factors in Tornado Damage and Recovery Models
NSF · Jul 2025 – Dec 2030
Phase I CAMEL-CN: Modeling the Messy: Capturing Student Reasoning within High-Dimensional Industrial AI Datasets
NSF · Jul 2026 – Jun 2029
Collaborative Research: HDR DSC: Infusion of data science and computation into engineering curricula
NSF · Oct 2021 – Sep 2026
Closest labs
Tara Hutchinson
University of California-San Diego, CA·Engineering
Test individual wall lines and building components of cold-formed steel framing to separate how designated shear walls, gravity walls, finishes and partitions each resist earthquake loads.
Julio Ramirez
Purdue University, IN·Engineering
Convene and support NHERI network governance, including the Council, Network Independent Advisory Committee and User Forum, and update the NHERI Science Plan that sets shared research priorities across earthquake, wind and coastal hazards.
Hyoungsu Park
University of Hawaii at Manoa, HI·Engineering
Measure how tsunami-driven debris damming increases forces on the first-floor columns of elevated structures, using experiments in the large wave flume at the Oregon State University NHERI facility.
The school
Pennsylvania State University: 60 labs on PI Pages, $1.3B a year on research, 743 research doctorates a year.
Reach out
A start for your email. Fill in the brackets.