About me (after several attempts, still a draft)

I am passionate about using research and engineering to help folks. I have a Bachelor of Science degree in Civil Engineering, Master of Science degree in Production Engineering, and Doctor of Philosophy degree in Urban and Regional Science. However, I don’t consider myself an expert in any one particular area—I’m more of a generalist.

I research to improve practices on risk assessment related to natural hazards with social impacts. The research areas I focus on are at the nexus of the sub-fields of urban geography and human ecology, and include using geographic information science for spatial analyses of risk, urban hazards, social impacts, and community-based participatory research.

As part of the hurricane evacuation studies, one of my works focuses on examining hurricane risk on coastal communities using causal probabilistic analysis through influence diagrams (Bayesian networks), which includes mapping risk for possible better risk communication and to the development of behavioral surveys. Also, I love teaching and preparing presentations. I am privileged to teach Urban Analytical Methods, Introduction to QGIS, and Spatial Analysis in R.

At work, I’m a coding and reproducible research enthusiast, intensely employing open-source software. I am an avid R user, who loves GIS, statistics, and fancy data visualizations. When I'm not at the computer, I enjoy building with Legos, running on streets and biking, and traveling with my family.

Educational Background


Research Interests

  • Probabilistic causal analysis through influence diagrams (i.e. Bayesian networks)

  • Spatial analyses of risk, including thematic cartography and geo-visualization

  • Risk assessment for natural hazards with social impacts (e.g. hurricane evacuation planning)

  • Impact of natural disasters on suicide risk

  • Human geography and the production of space

Expertise in Geospatial Technologies

Expertise in Analytical Methods

  • Bayesian Networks (BN)

  • Difference in Difference (DID)

  • Principal Component Analysis (PCA)

  • Hypothesis Testing for Means & Proportions


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QGIS / GIS day
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Terminal Codes
R notes
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