People
Links
Saul, Lawrence K.
http://www.cis.upenn.edu/~lsaul/
Machine learning, pattern recognition, neural networks, voice processing, auditory computation.
LeCun, Yann
Handwritten recognition, convolutional networks, image compression. Noted for LeNet.
Kearns, Michael
http://www.cis.upenn.edu/~mkearns/
Reinforcement learning, probabilistic reasoning, machine learning, spoken dialogue systems.
Storkey, Amos
http://www.anc.ed.ac.uk/~amos/
Belief networks, dynamic trees, image models, image processing, probabilistic methods in astronomy, scientific data mining, Gaussian processes and Hopfield neural networks.
Roweis, Sam T.
http://www.cs.toronto.edu/~roweis/
Speech processing, auditory scene analysis, machine learning.
Coolen, Ton
http://www.mth.kcl.ac.uk/~tcoolen/
Physics of disordered systems. Working on dynamic replica theory for recurrent neural networks.
Bach, Francis
http://www.cs.berkeley.edu/~fbach/
Machine learning, kernel methods, kernel independent component analysis and graphical models
Winther, Ole
http://eivind.imm.dtu.dk/staff/winther/
Variational algorithms for Gaussian processes, neural networks and support vector machines. Also work on belief propagation and protein structure prediction.
Herbrich, Ralph
http://www.research.microsoft.com/users/rherb/
Statistical learning theory, support vector machines and kernel methods.
Roberts, Stephen
http://www.robots.ox.ac.uk/~sjrob/
Machine learning and medical data analysis, independent component analysis and information theory.
Bishop, Chris
http://research.microsoft.com/~cmbishop/
Graphical models, variational methods, pattern recognition.
Cottrell, Garrison W.
http://charlotte.ucsd.edu/~gary/
An artrificial intelligence researcher who is an expert on neural networks.
Frey, Brendan J.
http://www.psi.utoronto.ca/~frey/
Iterative decoding, unsupervised learning, graphical models.
Hinton, Geoffrey E.
http://www.cs.toronto.edu/~hinton/
Unsupervised learning with rich sensory input. Most noted for being a co-inventor of back-propagation.
MacKay, David
http://www.inference.phy.cam.ac.uk/mackay/
Bayesian theory and inference, error-correcting codes, machine learning.
Smola, Alex J.
Kernel methods for prediction and data analysis.



