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BIOPHYSICAL SOCIETY NEWSLETTER
2
JANUARY
2016
BIOPHYSICAL SOCIETY
Officers
President
Edward Egelman
President-Elect
Suzanne Scarlata
Past-President
Dorothy Beckett
Secretary
Frances Separovic
Treasurer
Paul Axelsen
Council
Olga Boudker
Ruth Heidelberger
Kalina Hristova
Juliette Lecomte
Amy Lee
Robert Nakamoto
Gabriela Popescu
Joseph D. Puglisi
Michael Pusch
Erin Sheets
Antoine van Oijen
Bonnie Wallace
Biophysical Journal
Leslie Loew
Editor-in-Chief
Society Office
Ro Kampman
Executive Officer
Newsletter
Catie Curry
Beth Staehle
Ray Wolfe
Production
Laura Phelan
Profile
Ellen Weiss
Public Affairs
Beth Staehle
Publisher's Forum
The
Biophysical Society Newsletter
(ISSN 0006-3495) is published
twelve times per year, January-
December, by the Biophysical
Society, 11400 Rockville Pike, Suite
800, Rockville, Maryland 20852.
Distributed to USA members
and other countries at no cost.
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to Biophysical Society, 11400
Rockville Pike, Suite 800, Rockville,
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the United States of America.
All rights reserved.
David E. Shaw
, Chief Scientist, D.E. Shaw Research, always believed that
he would work as a scientific researcher; he never imagined the unexpected
detour he would take into the world of finance, as a pioneer in quantita-
tive trading. Shaw’s father was a theoretical plasma physicist, his mother a
researcher in education, and his stepfather was an economist and professor
at the University of California, Los Angeles (UCLA). “I was raised in Los
Angeles, near UCLA, and my parents used to take me there so frequently
that it was some time before I learned the difference between a university and
a public park,” he recalls. “They looked pretty much the same to me, though
the university had a wider range of interesting things going on, and was
generally more entertaining.”
Shaw attended the University of California, San Diego, where he double-
majored in mathematics and in applied physics and information science.
He then earned his PhD from Stanford University in 1980. Shaw wrote a
doctoral dissertation that provided a theoretical framework for a new class of
computer architectures and algorithms that could be shown to offer asymp-
totically superior performance for certain mathematical operations related to
artificial intelligence and database management.
He joined the faculty of the Computer Science Department at Columbia
University, conducting research on the design of massively parallel special-
purpose supercomputers for various applications. “Although my thesis at
Stanford hadn’t involved the construction of any actual hardware,” Shaw
explains, “after arriving at Columbia, I received government funding to actu-
ally start building one of the weird supercomputers I’d designed on paper.”
The machine could not be constructed using standard components, so Shaw
and his students designed their own integrated circuits, and then connected
them to assemble a small-scale working prototype. They wrote code for the
machine that implemented some of Shaw’s algorithms. “We were thrilled
when the whole thing actually started working,” Shaw recalls.
Hooked on the idea of designing and building these special-purpose super-
computers, Shaw saw that building full-scale machines would require a much
larger budget than government grants could likely provide. He wrote a busi-
ness plan for a proposed startup venture that would manufacture massively
parallel supercomputers for commercial use, and began meeting with venture
capitalists.
It quickly became clear to Shaw that this venture would not take off, but in
the course of seeking funding, he had a chance meeting with executives from
Morgan Stanley that led him on a career detour. “The executives I met with
at Morgan Stanley told me that someone there had discovered a mathemati-
cal technique for identifying underpriced stocks,” Shaw says. “A group of
financial and technical people there had written some software that was using
this technique to make investment decisions on a fully automated basis, and
they were consistently earning an unusually high rate of return.” Shaw was
intrigued that they were using quantitative and computational methods in
the stock market, “and I couldn’t help wondering whether state of the art
methods that were being explored in academia could be used to discover
Biophysicist in Profile
DAVID E. SHAW