Pursuing the Next Level of Artificial Intelligence

Jim Wilson/The New York Times

Daphne Koller’s award-winning work in artificial intelligence has had commercial impact.

By JOHN MARKOFF

Published: May 3, 2008

PALO ALTO, Calif. — Like a good gambler, Daphne Koller, a researcher at Stanford whose work has led to advances in artificial intelligence, sees the world as a web of probabilities.

There is, however, nothing uncertain about her impact.

A mathematical theoretician, she has made contributions in areas like robotics and biology. Her biggest accomplishment — and at age 39, she is expected to make more — is creating a set of computational tools for artificial intelligence that can be used by scientists and engineers to do things like predict traffic jams, improve machine vision and understand the way cancer spreads.

Ms. Koller’s work, building on an 18th-century theorem about probability, has already had an important commercial impact, and her colleagues say that will grow in the coming decade. Her techniques have been used to improve computer vision systems and in understanding natural language, and in the future they are expected to lead to an improved generation of Web search.

“She’s on the bleeding edge of the leading edge,” said Gary Bradski, a machine vision researcher at Willow Garage, a robotics start-up firm in Menlo Park, Calif.

Ms. Koller was honored last week with a new computer sciences award sponsored by the Association for Computing Machinery and the Infosys Foundation, the philanthropic arm of the Indian computer services firm Infosys.

The award to Ms. Koller, with a prize of $150,000, is viewed by scientists and industry executives as validating her research, which has helped transform artificial intelligence from science fiction and speculation into an engineering discipline that is creating an array of intelligent machines and systems. It is not the first such recognition; in 2004, Ms. Koller received a $500,000 MacArthur Fellowship.

Ms. Koller is part of a revival of interest in artificial intelligence. After three decades of disappointments, artificial intelligence researchers are making progress. Recent developments made possible spam filters, Microsoft’s new ClearFlow traffic maps and the driverless robotic cars that Stanford teams have built for competitions sponsored by the Defense Advanced Research Projects Agency.

Since arriving at Stanford as a professor in 1995, Ms. Koller has led a group of researchers who have reinvented the discipline of artificial intelligence. Pioneered during the 1960s, the field was originally dominated by efforts to build reasoning systems from logic and rules. Judea Pearl, a computer scientist at the University of California, Los Angeles, had a decade earlier advanced statistical techniques that relied on repeated measurements of real-world phenomena.

Called the Bayesian approach, it centers on a formula for updating the probabilities of events based on repeated observations. The Bayes rule, named for the 18th-century mathematician Thomas Bayes, describes how to transform a current assumption about an event into a revised, more accurate assumption after observing further evidence.

Ms. Koller has led research that has greatly increased the scope of existing Bayesian-related software. “When I started in the mid- to late 1980s, there was a sense that numbers didn’t belong in A.I.,” she said in a recent interview. “People didn’t think in numbers, so why should computers use numbers?”

Ms. Koller is beginning to apply her algorithms more generally to help scientists discern patterns in vast collections of data.

“The world is noisy and messy,” Ms. Koller said. “You need to deal with the noise and uncertainty.”

That philosophy has led her to do research in game theory and artificial intelligence, and more recently in molecular biology.

Her tools led to a new type of cancer gene map based on examining the behavior of a large number of genes that are active in a variety of tumors. From the research, scientists were able to develop a new explanation of how breast tumors spread into bone.

One potentially promising area to apply Ms. Koller’s theoretical work will be the emerging field of information extraction, which could be applied to Web searches. Web pages would be read by software systems that could organize the information and effectively understand unstructured text.

“Daphne is one of the most passionate researchers in the A.I. community,” said Eric Horvitz, a Microsoft researcher and president of the Association for the Advancement of Artificial Intelligence. “After being immersed for a few years with the computational challenges of decoding regulatory genomics, she confided her excitement to me, saying something like, ‘I think I’ve become a biologist — I mean a real biologist — and it’s fabulous.’ ”

To that end, Ms. Koller is spending a sabbatical doing research with biologists at the University of California, San Francisco. Because biology is increasingly computational, her expertise is vital in gaining deeper understanding of cellular processes.

Ms. Koller grew up in an academic family in Israel, the daughter of a botanist and an English professor. While her father spent a year at Stanford in 1981 when she was 12, she began programming on a Radio Shack PC that she shared with another student.

When her family returned to Israel the next year, she told her father, the botanist, that she was bored with high school and wanted to pursue something more stimulating in college. After half a year, she persuaded him to let her enter Hebrew University, where she studied computer science and mathematics.

By 17, she was teaching a database course at the university. The next year she received her master’s degree and then joined the Israeli Army before coming to the United States to study for a Ph.D. at Stanford.

She didn’t spend her time looking at a computer monitor. “I find it distressing that the view of the field is that you sit in your office by yourself surrounded by old pizza boxes and cans of Coke, hacking away at the bowels of the Windows operating system,” she said. “I spend most of my time thinking about things like how does a cell work or how do we understand images in the world around us?”

In recent years, many of her graduate students have gone to work at Google. However she tries to persuade undergraduates to stay in academia and not rush off to become software engineers at start-up companies.

She acknowledges that the allure of Silicon Valley riches can be seductive. “My husband still berates me for not having jumped on the Google bandwagon at the beginning,” she said. Still, she insists she does not regret her decision to stay in academia. “I like the freedom to explore the things I care about,” she said.