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Artificial intelligence may feel like a recent revolution, but for School of Engineering and Applied Science’s Chris Callison-Burch, program director of the online Master of Science in Engineering in Artificial Intelligence degree program, it’s the culmination of a 25-year journey—one that shows how breakthroughs happen when technology, data, and vision align. This is a moment that he calls “exactly the most exciting time to get into this field.”
Callison-Burch traces his entry into AI to 1999, when a visiting-day presentation at Stanford during his senior year of high school introduced him to the Symbolic Systems Program—an interdisciplinary blend of computer science, linguistics, psychology, and philosophy centered on how humans and machines communicate.
Today, as program director for the MSE-AI Online degree program, he’s channeling decades of experience into training the next generation of AI innovators. As a professor in the Computer and Information Science department, he leads online courses for graduate students and also teaches undergraduate AI courses on campus.
As a young faculty member at Johns Hopkins in 2007, Chris Callison-Burch made his mark by developing translation systems that helped institutions like the European Union draft documents across multiple languages. His most-cited paper—now referenced more than 7,400 times—introduced the statistical approach that powered this breakthrough. By releasing the software as open source, he democratized machine translation worldwide, proving that research matters most when shared.
Over the past 25 years, Callison-Burch has seen artificial intelligence reinvent itself again and again.
As Callison-Burch notes, the environment at Penn gave him and his peers access to the resources, mentorship, and collaborations that helped drive progress. Penn was also among the universities contributing to the Defense Advanced Research Projects Agency challenges that accelerated autonomous driving, an example of how progress emerges when universities, government, and industry work together. Today, that tradition continues as Penn Engineering students learn directly from faculty who are not only teaching but also actively contributing to the breakthroughs defining AI’s future.
Read more at Penn Engineering.
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