Biology as Computation
Leslie Valiant
Harvard University
Wednesday, November 29, 2006
4:00 p.m. in 1221 CS
(cookies at 3:30 in 2310 CS)
Abstract:
We argue that computational models have an essential role in uncovering
the principles behind a variety of biological phenomena. In particular we
consider recent results relating to the following three questions: How can
brains, given their known resource constraints such as the sparsity of
connections and slow elements, do any significant information processing
at all? How can evolution, in only a few billion years, evolve such complex
mechanisms as it has? How can cognitive systems manipulate large amounts
of such uncertain knowledge and get usefully reliable results? We show
that each of these problems can be formulated as a quantitative question
for a computational model, and argue that solutions to these formulations
provide some understanding of these biological phenomena.
Speaker's Bio:
Leslie Valiant was educated at King's College, Cambridge; Imperial College,
London; and at Warwick University where he received his Ph.D. in computer
science in 1974. He is currently T. Jefferson Coolidge Professor of Computer
Science and Applied Mathematics in the Division of Engineering and Applied
Sciences at Harvard, where he has taught since 1982. Before coming to Harvard
he had taught at Carnegie-Mellon University, Leeds University, and the
University of Edinburgh.
His work has ranged over several areas of theoretical computer science,
particularly complexity theory, computational learning, and parallel
computation. He also has interests in computational neuroscience, evolution
and artificial intelligence.
He received the Nevanlinna Prize at the International Congress of
Mathematicians in 1986 and the Knuth Award in 1997. He is a Fellow of the
Royal Society (London) and a member of the National Academy of Sciences (USA).
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