I am interested in studying techniques to reveal gerrymandering. I am also interested in computational fluid dynamics and high performance computing.
Greg Herschlag
Related Projects
Pryia Juarez (BME/ECE), Jonathan Pilland (ECE/BME), and Matthew Traum (CS/Econ) spent teen weeks analyzing sensor data synthesized by an agile waveform generator. The team used deep reinforcement learning techniques to understand the performance of different synthetic agents representing potential attackers to the sensor system.
Stats/Sociology major Mitchelle Mojekwu joined Neuroscience majors Kassie Hamilton and Zineb Jaidi in a ten-week exploration of data relevant to an upcoming public school zone redistricting in Durham County. Using information acquired from the General Social Survey and the US Census, the team applied modern mathematical and statistical methods for...
Martin Guo (MIDS), Dani Trejo (CS), James Wang (CS/Math), and Grayson York (Math/CS) spent ten weeks building tools to understand voting patterns and gerrymandering of districts in North Carolina. They used dimension reduction techniques to cluster different elections into common groups, and they tested various methods for generating synthetic elections...
The QSIDES Institute has pulled thousands of pages of police records from the Williamstown Police Department. This project will analyze and identify patterns in police behavior in the town, work with journalists and other activists to use the data to develop action plans to address problems and enact public safety...
A team of students will partner closely with the City of Durham’s newly formed Community Safety Department. The Community Safety Department’s mission is to identify, implement, and evaluate new approaches to enhance public safety that may not involve a law enforcement response or the criminal justice system. The student team...
Duke has a new Chief Engagement Officer, a Double Dukie, who is passionate about advancing and optimizing alumni engagement, involvement, and experience. With a private sector performance marketing and media background, she hopes to lead a team of students, in collaboration with Professor Shep Moyle (a Duke alum, former Duke...
Online data scraping has reached a fever pitch, as AI creators seek food for their hungry models. Researchers from the Argus Lab at Duke are building tools to analyze web scraping at scale based on analysis of Duke’s web logs. Data+ students will investigate the time-scale of AI data scraping (e.g....
A team of students, collaborating with Professors Mike Bergin, David Carlson, and PhD Candidate Zach Calhoun will develop a modeling approach to estimate heat stress in urban areas. Students will further develop a dataset consisting of high-resolution temperature and relative humidity observations in over 60 cities (https://www.heat.gov/pages/mapping-campaigns), satellite imagery and...
The goal of this Data+ project is to apply and extend custom analytics solutions to understand and predict microbial population growth. An explosion of data has resulted from tracking the growth of bacteria in high throughput devices. These data were generated to understand how microbes grow. Better models that fit...
A group of students, guided by climate science and environmental engineering professors, will use deep learning models to enhance flash flood predictions in the Southeastern United States. They will study extreme weather events that contribute to flooding and learn to identify these events using satellite and radar imagery. By applying...