Originally from Wilmington NC, I am currently a Ph.D. candidate in the School of Industrial Engineering at Purdue University in the Laboratory for Advancing Sustainable Critical Infrastructure working with Professor Roshi Nateghi. My current research currently focuses on formulating scientific and machine learning methods for extracting patterns from messy, complex, and high-dimensional data.
This is all applied to the study of communitites in response to natural disasters. Currently, I am developing algorithms which use social media as a source of data to predict the community dynamics in response to major disruptions and natural hazards.
Another interst and area of experience is in developing statistical-machine learning tools and methods to understand the relationship between climate change, natural hazards, human behavior, and urban systems.
In the future, I am interested in expanding this research into a variety of fields and applications:
- Fairness/Accountability/Transparency. How do statistical and optimization tools used for supporting disaster response contribute to social inequality?
- Grid design/optimization. How can renewable energy production and storage be utilized to build electrical transmission and distribution systems robust to natural disasters?
- Statistical-Machine Learning. How can we make predictions about how a disaster imapcts a community if we have no data? Emblamatically: what happens when a blizzard hits Miami?
Prior to my doctoral work, I received my undergraduate degree in Industrial Engineering from the Industrial and Systems Engineering Department at North Carolina State University. I additionally currently work in an optimization and data science group at Sandia National Labs as an R&D intern, working to large-scale probabilistic optimization methods for the integration of renewables into unit-commitment planning. More to come here as we work to get our code open sourced!
… more to come when reviews trickle in!