Principal Investigator, Hopfield Group, Princeton University, U.S.A.
J. J. Hopfield has made important contributions in an impressively broad spectra of scientific subjects. His special and rare gift is his ability to cross the inter-disciplinary boundary to discover new questions and propose answers that uncover the conceptual structure behind the experimental facts. His early research on the Light Emitting Diodes has been recognised with the Buckley Prize. In Biology he understood the need for and proposed the principle ("proof-reading") by which the replication mechanism manages to achieve accuracy far beyond the possible in equilibrium processes. The famous Hopfield model of neural processing demonstrated by construction how qualitatively different computation in a computer and in the brain could be. More recently, he has found an entirely different organising principle in olfaction and demonstrated a new principle in which neural function can take advantage of the temporal structure of the "spiking" interneural communication.
1962-1964 : Alfred Sloan Fellow
1969 Guggenheim Fellow (Cavendish, Cambridge, England)
1969 : Buckley Prize, Am. Phys. Soc.
1983-88 : John and Catherine T. MacArthur Award
1985 : APS Prize in Biophysics
1988 : Michelson-Morley Award, Case-Western Univ.
1989 : The Wright Prize, Harvey Mudd College
1991 : California Scientist of the Year, California Museum of Science and Industry
1992 : Hon. D. Sci. Swarthmore College
1997 : Neural Network Pioneer Award, IEEE
1999 : International Neural Network Society Helmholtz Award
2001 : Dirac Medal and Prize, International Center for Theoretical Physics, Trieste
2002 : Pender Award, Moore School of Engineering, University of Pennsylvania
J.J. Hopfield, (1998) Computing with action potentials in Neural Information Processing Systems. MIT Press, 10, pp 166-172.
J.J. Hopfield, (1996) Transforming neural computations and representing time PNAS 93, 15440-15444.
J.J. Hopfield, (l995) Pattern recognition computation using action potential timing for stimulus representation. Nature 376, 33-36.
D. Dong and J.J. Hopfield (1992) Dynamic properties of neural networks with learning and feedback Network 3, 267-283.
J. J. Hopfield (1991) Olfactory computation and object perception PNAS 88, 6462-6466.
D.W. Tank and J.J. Hopfield (l989) Neural architecture and biophysics for sequence recognition in Neural Models of Plasticity, Academic Press, 363-377.