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  1. Leslie Gabriel Valiant FRS (born 28 March 1949) is a British American computer scientist and computational theorist. He was born to a chemical engineer father and a translator mother. He is currently the T. Jefferson Coolidge Professor of Computer Science and Applied Mathematics at Harvard University.

  2. Leslie Gabriel Valiant (nacido el 28 de marzo de 1949) es un informático teórico británico. Educado en el King's College, Cambridge, Imperial College London y la Universidad de Warwick donde recibió su Ph.D. en ciencias de computación en 1974.

  3. Leslie Valiant is a renowned computer scientist who has made contributions to complexity theory, computational learning, parallel computation, and more. He is the T. Jefferson Coolidge Professor of Computer Science and Applied Mathematics at Harvard, and has received several awards and honors, including the ACM A.M. Turing Award.

  4. Leslie Valiant is a theoretical computer scientist who has made transformative contributions to the theory of computation, including PAC learning, complexity of enumeration and algebraic computation, and parallel and distributed computing. He has also advocated for a unified framework to characterize the power, semantics and cortical computation of natural and artificial phenomena.

  5. Leslie Valiant T. Jefferson Coolidge Professor of Computer Science and Applied Mathematics, School of Engineering and Applied Sciences, Harvard University. Contact Info: Email: valiant seas harvard edu . Earlier Publications. Recent Publications: 71. Circuits of the Mind, Oxford University Press, (1994, 2000). 72.

  6. 10 de mar. de 2011 · La Association for Computing Machinery ( ACM) ha otorgado a Leslie G. Valiant el Premio Turing 2010. Valiant, de la Universidad de Harvard, ha recibido este premio por sus " contribuciones...

  7. 6 de may. de 2024 · Leslie Valiant is a Hungarian-born American computer scientist and winner of the 2010 A.M. Turing Award, the highest honour in computer science, “for his fundamental contributions to the development of computational learning theory and to the broader theory of computer science.”