Mandli Projects 1

The goal of this project would be to construct a platform for viewing either through a mobile or other AR device previous and predicted flood extents on the surrounding environment as well as suggested adaptation strategies.  This would help both stakeholders and communities to easily visualize both the risk or flooding and the impact a particular protection might have. This would also tie into the existing GIS data available through the project incorporating ESRI's AuGEO platform.  Ideally this project would also be made widely available increasing the impact of such an effort. The resulting software would also be made freely available on GitHub with an API for adding other sources of data.

In this NSF funded project we are developing a methodology that can help inform stakeholders as to how they might best formulate strategies for coastal adaptation that have the potential to both increase the resilience of interdependent critical infrastructure (ICI) and reduce harm while accounting for climate change impacts.  (1) formulate a new strategy for adaptation, (2) computationally determine flooding levels given an ensemble of storms representing the likely threat and future sea-level rise, (3) estimate the damage over the ensemble to the infrastructure considered, and (4) using appropriate metrics evaluate the relative suitability of a given strategy including cost and social acceptability.  This process would repeat iteratively until a sufficiently optimal strategy is found. Developing such a methodology will be challenging however. The magnitude of the computational effort needed is significant. Using a set of computational models that vary in accuracy and speed, the methodology will swap between models appropriate for the optimization stage. Stakeholder involvement is also being incorporated via interviews that will ask what components of the infrastructure system are most critical and/or vulnerable in their eyes as well as provide guidance as to how the results of the methodology would be best communicated.  Eventually this will also lead to community outreach efforts to communicate the potential of such approaches. This is all going to take place using New York City's complex infrastructure and recent events as both a validation test-bed as well as a test for the methodology.

Position Dates: 10 Week program during the summer of 2019

Paid Position: Yes, $800/Week

Qualifications: Programming experience is required, ideally in Python or a similar language.  Highly recommended is knowledge of augmented reality frameworks such as ARCore or ARKit. 

Eligibility: Undergraduate student and a U.S. citizen, U.S. national, or permanent resident of the United States.

Kyle T. Mandli, Assistant Professor