Computer Science

The pioneering career of Norman Badler

The computer and information sciences professor retired in June. He chats about his recent ACM SIGGRAPH election and his expansive computer graphics path.

From the Department of Computer and Information Science

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In the News


Now that machines can learn, can they unlearn?

Aaron Roth of the School of Engineering and Applied Science spoke about his research on machine unlearning, which seeks to answer the question, “Can we remove all influence of someone’s data when they ask to delete it but avoid the full cost of retraining from scratch?”


KYW Newsradio (Philadelphia)

The first computer is turning 75 in Philadelphia: 'ENIAC set the stage for everything'

Penn is celebrating the 75th anniversary of ENIAC, an early computer, with a week of virtual presentations and roundtable discussions.


Philadelphia Inquirer

Made in Philadelphia, the ‘first modern computer’ is celebrated on 75th anniversary

Seventy-five years ago, the first all-electronic programmable computer was unveiled at Penn. This year, a weeklong series of events celebrates the men and women that made it possible.


U.S. News & World Report

The AI revolution: For patients, promise and challenges ahead

Ravi Parikh of the Perelman School of Medicine said the use of machine learning in health care can be a double-edged sword. "Even though you might have an AI that's accurate on the whole, if it's mischaracterizing an outcome for a specific group of patients you really have to question whether it's worth it," he said.



These iPhone apps know how you’ll spend and save money—even before you do

Mauro Guillén of the Wharton School weighed in on personal finance apps for smartphones. “With digital technology, the possibilities expand,” he said. “I think we’re just seeing the beginning.”


The New York Times

An algorithm that grants freedom, or takes it away

An algorithm created for the Philadelphia Adult Probation and Parole Department by Richard Berk of the School of Arts and Sciences tries to improve on human judgement by excluding data that could be a proxy for race. “All machine-learning algorithms are black boxes, but the human brain is also a black box,” he said.