About the Speaker

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 School of Engineering and Applied Sciences at Harvard University, 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, the Knuth Award in 1997, the European Association for Theoretical Computer Science EATCS Award in 2008, and the 2010 A. M. Turing Award. He is a Fellow of the Royal Society (London) and a member of the National Academy of Sciences (USA).

Computer Science as a Natural Science

Computer science can be approached as mathematics, as technology, and as a natural science. Turing's foundational contributions opened up all three of these avenues and his lasting imprint on them is still evident. The first two approaches may be the ones that have been most thoroughly explored to date, but this talk will argue that the last is at least as fundamental and was perhaps the one closest to the core of Turing's thinking.

Turing's success in capturing the phenomenon of mechanical mental activity by means of the notion of computability sets the standard as a robust mathematical definition of a natural phenomenon. This talk will review more recent attempts to capture the phenomena of biological evolution, learning, and intelligence by means of definitions that seek to capture these various phenomena by analogously robust mathematical definitions.