Goals:Conduct research in political informatics that includes the development of a data repository containing, at a minimum, historical federal election results, election district boundary data, demographic data, cultural data, geographic feature data, and Web-based software able to analyze the data to test various political science hypotheses. The project provides support to governmental agencies seeking to establish an analytical basis for proposed judicial and legislative options. Innovative approaches to ensuring the constitutional validity of election processes are tested against a comprehensive data set in order to enhance and ensure the fairness of political processes.

Issues:Measures of political and racial fairness, measures of geometric compactness, algorithmic approaches to automated redistricting, probabilistic analysis of legislative issues, geometric region matching algorithms, and a standard programming interface to political data.

Methods & Technologies:Machine Learning; RESTful Web Services; Data mining; Perceptions of political fairness; Visualization of political data; Multidimensional optimization algorithms

Disciplines:Computer Science, Political Science, Applied Math and Statistics, Sociology

Interests / Preparation by Major:Major CSE: software engineering, visualization, graph algorithms, parallel computing, Major POL: election districting policies, measures of political and racial fairness.

Faculty:
    Robert Kelly (Computer Science)

Team Section:01

Team Established:Spring 2019

Spring Team Meeting:Online at Online Asynchronous

Fall Team Meeting:W 5-5:55 PM at Online

Contact:Robert Kelly <robkelly@cs.stonybrook.edu>

Links:.

Applications:Open