Murray Campbell on how he became interested in computers:
"Well, interestingly enough, [I became interested in computers] when I was in high school, in Edmonton, Canada, I went to the University of Alberta for an open-house...and at that point I saw a computer playing chess.

"I was a chess player at the time and that fascinated me. I ended up going into the Computer Science Department there and getting my degree, then going on to get my Ph.D. in Computer Science at Carnegie Mellon. So you could say that got me started."

Murray Campbell is the only member of the Deep Blue development team who can say that his interest in chess led him to pursue a career in computer science. Campbell grew up in Edmonton, Alberta, Canada, becoming a strong expert-level player while still in high school. After seeing the computer chess demonstration at the University of Alberta, he was hooked. The rest, as they say, is history.

@ Carnegie Mellon
Campbell received his bachelor's and master's degrees in Computing Science from the University of Alberta in 1981. He specialized in parallel search in the context of chess, a discipline that served him well in developing massively parallel computers like Deep Blue.

He left Canada to enroll at Carnegie Mellon University as a doctoral candidate in Computer Science. Campbell received his Ph.D. in 1987 from CMU for his work on chunking as an abstraction mechanism in solving complex problems.

At Carnegie Mellon he met a fellow doctoral student named Feng-hsiung Hsu who had developed a single-chip chess move generator. The two teamed up in the autumn of 1986 to construct a chess-playing computer, Chiptest, that eventually evolved into Deep Blue. Both Campbell and Hsu joined IBM in 1989.

Role on the Deep Blue team
Brody was recruited into the Deep Blue project in 1990. "Actually, I was between projects, and they were bringing Murray Campbell and Feng-hsiung Hsu [to IBM]. Hsu had worked on this machine, the Deep Thought machine, and they said, 'How would you like to work on this project?' And I said, 'Why not? Sounds great.' And we've been together ever since. It's a good team. We work well together."

Campbell's role on the Deep Blue team is twofold. His main function is the development of the evaluation function, or the component of Deep Blue that assesses the value of the current position.

"That's very important," says Campbell, "because even if you can search many moves into a position, search forward all the possible moves, it's still, you have to evaluate those positions at the end of the sequence of moves that you've looked at. If you evaluate them incorrectly, you're going to play poor chess." Campbell's challenge is to help Deep Blue evaluate positions accurately 100% of the time.

He also works closely with the team's chess consultant, international grandmaster Joel Benjamin, in developing Deep Blue's opening book (link to N.2)

This year's match
Campbell feels that this year's match will be even more competitive than last year's battle. "We know that Deep Blue is going to be playing at a higher level than last year," he says. "Deep Blue -- the current version of Deep Blue -- has already beaten the last version in several test games that we've played. So we know that it's better."

But Campbell isn't quite ready to predict a victory for Deep Blue. "We also know that Kasparov has spent a lot of time, and is spending a lot of time, preparing for this match and will come to this match with some new ideas on how to play against computers, so that will be interesting."

Campbell was the recipient of an IBM Outstanding Innovation Award for his work on the Deep Blue project. His interests include data-mining and parallel-search algorithms.