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Alumni Spotlight: Peter Haas

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Peter Haas lectures in front of a classroom. Photo by Jim Fabry.
Peter Haas lectures for a Stanford course. Photo by Jim Fabry.

July 1, 2017

Peter Haas (PhD '86) has led a storied career that is deeply intertwined with Stanford, both as a student and as an Adjunct Professor in Management Science and Engineering (MS&E).

As he prepares to leave the Bay Area this fall, we sat down with Haas to gain perspective on his experiences.

Field of study

"I've always been interested in where simulation, probability, statistics, and computer science come together," said Haas. Those interests led him to IBM, where he has collaborated on pioneering work in big data queries, modeling with uncertain data, collaborative modeling, and more recently machine learning and compression optimization. When asked how he gets enough sleep while being so productive, Haas said, "Fortunately I work with lots of good people, so I can leverage everybody's skills."

Return to Stanford

In the mid 1990s, while Haas had found and was continuing his success at IBM, he started teaching at Stanford as well. "It was a little bit of 'pay it forward,'" Haas said about what motivated him to teach. "I was trying to spread [an] appreciation of these elegant, beautiful, applicable, and practical results to a new generation of students."

But it wasn't only pure interest that led Haas to teach. His connections and experiences at Stanford paved the way. During his PhD, Haas said his advisor, Gerard Shedler, "interestingly… was sort of in the same position I am today—he worked for IBM Research in San Jose as his day job, but he came and he taught the simulation course at Stanford." When Shedler retired, Professor of MS&E Peter Glynn "talked me into teaching the course, which turned out to be a great thing," Haas said. "For me it was sort of ideal, because I always had academic inclinations. It's very rewarding for me to be in a teaching environment part of my year."

Advice for students

When asked, Haas gave the following advice for current students: "Something that I didn't do during my PhD that I wish I had done is to do more in the way of internships at different places." The intent being "to increase your awareness of applications, of problems that need to be solved," and to put "as many tools in your toolbox as you can. I think there's a tendency now for some people to get sucked into machine learning or some 'technique du jour,' but what I found over the years is there are ideas floating around far afield. That's, at least for me, where my sweet spot is."

The next chapter

This fall, Haas will relocate to the East Coast, where his wife will be Dean of the College of Information and Computer Sciences at the University of Massachusetts-Amherst. Haas will teach Computer Science with a courtesy appointment in Industrial Engineering. "I think I might be able to be a bridge" between the computer science and industrial engineering communities, which "suits me and my interdisciplinary inclinations," he said.

Reflections on MS&E

Haas was appreciative of his experiences of MS&E at Stanford. When asked what MS&E means to him, he said, "These days in MS&E, as opposed to hardcore OR, there’s more training on the soft skills. Maybe the most valuable thing that MS&E has given me is the ability to step back, take a systems view, and formulate problems."

"It's been a fabulous environment," Haas said of his time at Stanford. "It's really been worth it."

Written by Jim Fabry.

Alumni stories & voices