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New Faculty Profile: IEOR’s Rhonda Righter
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Rhonda
Righter, who joined IEOR last July, also got her Ph.D. at
Berkeley Engineering. “I feel like I’m coming
home,” she says of her new position.
JERRY KAPLER PHOTO |
The word that most frequently appears in her CV is optimal,
as in one of her papers titled Optimal ordering of operations
in a manufacturing chain. But Rhonda Righter never gets frustrated
devising theories and models for optimizing what she calls “the
messy reality” of everyday life.
“Teaching is so much fun,” she says. “And my
research is like solving puzzles all day. Sometimes I sit in the
cafe solving problems on my laptop and I think, ‘Wow! And
they pay me to do this.’”
Righter joined IEOR last July after more than 15 years at Leavey
School of Business at Santa Clara University, where she taught
statistics and operations management. An Oakland resident and
Berkeley Engineering alumna (M.S.’82 Eng Sci, Ph.D.’86
IEOR), Righter is glad to be working closer to her Rockridge home.
“Industrial engineering and operations research started
in World War II with questions like, ‘Where do you drop
the bomb if the submarine is going to move?,’” she
says. As the IEOR arena became larger and more interdisciplinary,
it evolved first to manufacturing and then to industrial applications.
Now Righter is working on a National Science Foundation proposal
to investigate operations in the service industries, which, she
says, account for 80 percent of the U.S. economy. Her own research
focuses on modeling and improving the performance of stochastic
(random) systems, especially manufacturing, service, and telecommunication
systems. The work has implications for workload distribution,
employee training and flexibility, and workplace productivity.
“I see what I do as applied math theories, general enough
that they could apply to computer communications or telecommunications,”
Righter says. “Think of phone calls instead of widgets;
the models are not that different.”
She is enjoying the transition from teaching quantitative subjects
like statistics, which were her bread and butter at Leavey, to
the computer-based and mathematical decision models she works
with now.
“The students here are more self-motivated,” she adds.
“I can’t imagine a better job.”
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