In this ongoing project, I have designed and implemented an Integer Linear Programming (ILP) optimization model to automatically redistrict states that have historically been relentlessly “gerrymandered”. In order to combat this biased process where legislators draw maps to gain a competitive advantage for their party in future elections, this model optimizes a state’s map for not only compactness, contiguity, integrity, and population, but also for an added key measure: fairness.
Stop Sign Detection
In this project as a part of a Spring 2019 one-on-one tutorial with Dr. David Chelberg, I created an OpenCV project using C++ to implement multiple components that aid in detecting the existence of a stop sign in an image (e.g. thresholding, corner detection, line detection, perspective transformations, etc.). This project served as an entry into classic computer vision algorithms and applying them to object detection.
n-FOLD ILP SOLVER
This project was performed as part of a research internship at the University of Bonn in Bonn, Germany. In this internship, funded by German government through the internationally competitive award program DAAD RISE, I studied algorithmic implementations of Integer Linear Programming solvers. Specifically, I studied algorithms to solve models that have a n-fold structure in nearly linear time. In this implementation of one such solver, I achieve a speedup by a factor of dimensionality over previous implementations.
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