Our Work Is Local, but Our Impact Is Global

The rise of social media and the growing scale of online information has led to a surge of intentional disinformation and incidental misinformation. It is increasingly difficult to tell fact from fiction, and the challenge is more complex than simply differentiating fake news from simple facts.

This project examines the temporal dynamics of emotional appeals in Russian campaign messages used in the 2016 election on Facebook and Twitter. 

This project investigated how data ethics can be a point of departure in designing and evaluating good systems, examining the contradictions and pressure points among various data practices. 

This project examined how children from groups underrepresented in STEM programs understand, interact with, and evaluate AI-driven digital assistants. 

Information and cultural heritage professionals have become increasingly interested in using data science, machine learning, and AI applications in the management of data and operations at libraries, archives, museums.

Artificial intelligence systems increasingly automate and assist people in making managerial and governance decisions. AI manages worker routines and tasks, determines how to distribute resources within cities, and assists in transportation management.

One of the main tasks of any city government is to keep infrastructure such as roads, signs, accessibility ramps, and sewers in perpetual working order. The first step of maintenance is the timely identification of a problem. However, many infrastructure defects are left undetected and unattended for long periods of time

The widespread use of service robots has been predicted to be just around the corner for decades. This project seeks to overcome the prevailing technical and social hurdles to deploying these robots by building and studying them in communities where they will be used rather than just in laboratories and warehouses.

The Austin History Center, the City of Austin, and UT Libraries maintain substantial collections of scanned maps, which are needed for historical reference when conducting research or planning new projects. Unfortunately, these scanned maps can be difficult to use due to the challenges involved with discovering, processing, and analyzing map images in their current digitized form.

Optimizing ambulance allocation and routing is one of the most efficient ways for EMS to save more lives at virtually no cost. However, current EMS software was developed under models that assume normal demands.