Assistant Professor Dan Goldwasser joined the department in 2014. He hopes algorithms that teach computers to understand natural language will help humans understand other humans and break biases. His most recent project with computer science graduate student Kristen Johnson analyzed U.S. politicians’ tweets on the topic of health care. Republicans framed the issue around cost, while Democrats framed it around care and empathy.
There were, however, some Republicans who defected from their party’s line. Goldwasser’s algorithm successfully identified which politicians would vote with the Democrats solely based on how they framed an issue in the public sphere – in this case, Twitter.
If computers can read between the lines, it would make it much harder for politicians to talk around an issue. Inversely, it would be harder for political activists to send coded messaging in the guise of fake news. Read more about how Goldwasser thinks artificial intelligence may be able to solve the problem of fake news.
Bruno Ribeiro joined the department as an assistant professor in 2014. His work in machine learning centers around large-scale complex social and communications systems. These networks are everywhere as they naturally frame some of the highest impact computing applications: from online social networking, to Web search, to product recommendations, to mobile ad-hoc networking.
Ribeiro studies the vast amount of data that these networks make available in order to gather insights and make predictions. His research blends practical issues with theory, focusing on how new theoretical results can advance novel applications. Learn more about Ribeiro's work.