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										|  | Parallel Computing Pioneer - Leslie G. ValiantGordon McKay Professor of Computer Science and 
	 Applied Mathematics, Harvard University 
										 |  
										| Leslie G. Valiant has conducted groundbreaking research in parallel 
	 computation from the time he first became involved in the field. He took an 
	 early interest in the central role that communication plays in parallel 
	 computation. He developed an efficient randomized routing methodology for 
	 general patterns of communication. This provided some positive evidence for 
	 the possibility of general purpose parallel computing. This work in turn 
	 led to his development, almost a decade later in 1989, of the bulk 
	 synchronous parallel (BSP) model, intended to take the role of a unifying 
	 "bridging" model for parallel computers and programs.
 
	 "When I started my research in the early 1970s, parallel computing was very 
	 confusing as a field," says Valiant. "It contrasted starkly with some other 
	 areas of computer science ‹ for instance, complexity theory had just 
	 developed into a coherent and powerful science. However, despite its 
	 frustrations, the field of parallelism did offer one attraction. It seemed 
	 that there was one central question around which everything revolved: 'What 
	 is the right model?' "
											 
	 He has also contributed to several other areas of computer science. Some of 
	 his early  work was in complexity theory. He introduced the class #P and 
	 showed how it could be used to classify many basic algebraic and 
	 combinatorial counting problems according to their computational 
	 difficulty. He has also a longstanding interest in the theoretical basis of 
	 artificial intelligence.
											 
	 In 1983 he introduced the PAC or "probably approximately correct" model of 
	 learning, which was instrumental in giving rise to the field of 
	 computational learning theory. More recently, he proposed this as a 
	 foundation for a broader computational study of intelligence. His 1994 
	 book, Circuits of the Mind, formulates such a study in a framework 
	 suggested by cortical neurons.
											 
	 Valiant was educated at King's College, Cambridge; Imperial College, 
	 London; and Warwick University, where he received his Ph.D. in computer 
	 science in 1974. He has been the Gordon McKay Professor of Computer Science 
	 and Applied Mathematics at Harvard University's Division of Engineering and 
	 Applied Sciences since 1982. Before coming to Harvard, he taught at 
	 Carnegie-Mellon University, Leeds University, and the University of 
	 Edinburgh.
											 
	 Valiant is an active member of the high-performance computing community. He 
	 is a regularly invited lecturer at conferences an symposia, distinguished 
	 lecture series, and other events. He serve or has served on numerous 
	 editorial boards and program committees including the SIAM Journal on 
	 Computing, Machine Learning Computational Complexity, Neural Computation, 
	 Neural Networks, the International Journal of Foundations of Computer 
	 Science, the Symposium on Theory of Computing (STOC), the Conference on 
	 Computational Learning Theory (COLT), EuroColt, the Symposium on Parallel 
	 Algorithms & Architectures (SPAA), and others.
											 
	 In addition to writing his 1994 book, Valiant is the author or co-author of 
	 more than 80 articles and papers. 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 and the American Association for 
	 Artificial Intelligence.
											
													
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