- Adelson, Edward T. - Visual perception, machine vision, image processing.
www-bcs.mit.edu/people/adelson
- Amari, Shun-ichi - Neural network learning, information geometry.
www.islab.brain.riken.go.jp/~amari
- Appl, Martin - Reinforcement learning, soft-computing, optimization.
www.planet-interkom.de/martin.barbara/martin.html
- Attias, Hagai - Graphical models, variational Bayes, independent factor analysis.
research.microsoft.com/~hagaia
- Bach, Francis - Machine learning, kernel methods, kernel independent component analysis and graphical models
www.cs.berkeley.edu/~fbach
- Ballard, Dana H. - Visual perception with neural networks.
www.cs.rochester.edu/users/faculty/dana
- Bartlett, Marian Stewart - Image analysis with unsupervised learning, face recognition, facial expression analysis.
ergo.ucsd.edu/~marni
- Beal, Matthew J. - Bayesian inference, variational methods, graphical models.
www.gatsby.ucl.ac.uk/~beal
- Becker, Sue - Neural network models of learning and memory, computational neuroscience, unsupervised learning in perceptual systems.
www.science.mcmaster.ca/Psychology/sb.html
- Beveridge, Ross - Computer vision, model-based object recognition, face recognition.
www.cs.colostate.edu/~ross
- Bishop, Chris - Graphical models, variational methods, pattern recognition.
research.microsoft.com/~cmbishop
- Boutilier, Craig - Decision making and planning under uncertainty, reinforcement learning, game theory and economic models.
www.cs.toronto.edu/~cebly
- Brody, Carlos D. - Somatosensory working memory, computation with action potentials, design of complex stimuli for sensory neurophysiology.
www.cns.caltech.edu/~carlos
- Brown, Andrew - Machine learning of dynamic data, graphical models and Bayesian networks, neural networks.
www.gatsby.ucl.ac.uk/~andy
- Calvin, William H. - Theoretical neurophysiologist and author of The Cerebral Code, How Brains Think.
faculty.washington.edu/wcalvin
- Caruana, Rich - Multitask learning.
www.cs.cmu.edu/~caruana
- Chu, Selina - Artificial intelligence, machine learning, data mining.
www.ics.uci.edu/~selina
- Coolen, Ton - Physics of disordered systems. Working on dynamic replica theory for recurrent neural networks.
www.mth.kcl.ac.uk/~tcoolen
- Cottrell, Garrison W. - An artrificial intelligence researcher who is an expert on neural networks.
charlotte.ucsd.edu/~gary
- Dayan , Peter - Representation and learning in neural processing systems, unsupervised learning, reinforcement learning.
www.gatsby.ucl.ac.uk/~dayan
- de Freitas, Nando - Bayesian inference, Markov chain Monte Carlo simulation, machine learning.
www.cs.ubc.ca/~nando
- de Sa, Virginia - Supervised and unsupervised learning, cross-modal learning.
keck.ucsf.edu/~desa
- Dietterich, Thomas G. - Reinforcement learning, machine learning, supervised learning.
www.cs.orst.edu/~tgd
- Dovzhenko, Alexander Yu. - Neural networks for computer clusters, oscillations in neural networks
www.itp.ac.ru/~alex
- Freeman, William T. - Bayesian perception, computer vision, image processing.
www.merl.com/people/freeman
- Frey, Brendan J. - Iterative decoding, unsupervised learning, graphical models.
www.psi.utoronto.ca/~frey
- Ghahramani, Zoubin - Sensorimotor control, unsupervised learning, probabilistic machine learning.
www.gatsby.ucl.ac.uk/~zoubin
- Ghosh, Joydeep - Adaptive multi-learner systems, intelligent data analysis, data and web mining.
lans.ece.utexas.edu/~ghosh
- Herbrich, Ralph - Statistical learning theory, support vector machines and kernel methods.
www.research.microsoft.com/users/rherb
- Heskes, Tom - Learning and generalization in neural networks.
www.mbfys.kun.nl/mbfys/people/tom
- Hinton, Geoffrey E. - Unsupervised learning with rich sensory input. Most noted for being a co-inventor of back-propagation.
www.cs.toronto.edu/~hinton
- Honavar, Vasant - Constructive learning, computational learning theory, spatial learning, cognitive modelling, incremental learning.
www.cs.iastate.edu/~honavar
- Hopfield, John J. - Neural networks, collective behaviour of systems of simple processors. Most noted for Hopfield networks.
www.hopfield.net/~john
- Jaakkola, Tommi S. - Graphical models, variational methods, kernel methods.
www.ai.mit.edu/people/tommi
- Jensen, Finn Verner - Graphical models, belief propagation.
www.cs.auc.dk/~fvj
- Joachims, Thorsten - Support vector machines, machine learning and natural language, statistical learning theory, text classification.
www.cs.cornell.edu/People/tj
- Jordan, Michael I. - Graphical models, variational methods, machine learning, reasoning under uncertainty.
www.cs.berkeley.edu/~jordan
- Kakade, Sham - Reinforcement learning and conditioning, mathematical models of neural processing.
www.gatsby.ucl.ac.uk/~sham
- Kali, Szabolcs - Learning and memory in the brain, hippocampus.
www.gatsby.ucl.ac.uk/~szabolcs
- Kappen, Bert - Boltzmann machines, computational neurobiology, online learning.
www.mbfys.kun.nl/mbfys/people/bert
- Kawato, Mitsuo - Computational neuroscience, neural network modelling.
www.isd.atr.co.jp/~kawato
- Kearns, Michael - Reinforcement learning, probabilistic reasoning, machine learning, spoken dialogue systems.
www.cis.upenn.edu/~mkearns
- Keysers, Daniel - Pattern recognition and statistical modelling for object recognition.
www-i6.Informatik.RWTH-Aachen.DE/~keysers
- Koller, Daphne - Probabilistic models for complex uncertain domains.
robotics.stanford.edu/~koller
- Lafferty, John D. - Statistical machine learning, text and natural language processing, information retrieval, information theory.
www.cs.cmu.edu/afs/cs.cmu.edu/user/lafferty/www/homepage.html
- Lawrence, Neil - Graphical models, variational methods.
www.cl.cam.ac.uk/users/ndl21
- Lawrence, Steve - Information dissemination and retrieval, machine learning and neural networks.
www.neci.nj.nec.com/homepages/lawrence
- LeCun, Yann - Handwritten recognition, convolutional networks, image compression. Noted for LeNet.
yann.lecun.com
- Leen, Todd - Online learning, machine learning, learning dynamics.
www.cse.ogi.edu/~tleen
- Leow, Wee Kheng - Computer vision, computational olfaction.
www.comp.nus.edu.sg/~leowwk
- Lerner, Uri N. - Hybrid and Bayesian networks.
robotics.Stanford.EDU/~uri
- Li, Zhaoping - Non-linear neural dynamics, visual segmentation, sensory processing.
www.gatsby.ucl.ac.uk/~zhaoping
- Maass, Wolfgang - Theory of computation, computation in spiking neurons.
www.cis.tu-graz.ac.at/igi/maass
- MacKay, David - Bayesian theory and inference, error-correcting codes, machine learning.
www.inference.phy.cam.ac.uk/mackay
- McCallum, Andrew - Machine learning, text and information retrieval and extraction, reinforcement learning.
www.cs.cmu.edu/~mccallum
- Meila, Marina - Graphical models, learning in high dimensions, tree networks.
www.stat.washington.edu/mmp
- Minka, Thomas P. - Machine learning, computer vision, Bayesian methods.
www.stat.cmu.edu/~minka
- Morris, Quaid - Machine learning for medical diagnosis and biological data analysis.
www.gatsby.ucl.ac.uk/~quaid
- Murphy, Kevin P. - Graphical models, machine learning, reinforcement learning.
www.cs.berkeley.edu/~murphyk
- Murray, Alan - Neural networks and VLSI hardware.
www.ee.ed.ac.uk/~afm
- Neal, Radford - Bayesian inference, Markov chain Monte Carlo methods, evaluation of learning methods, data compression.
www.cs.toronto.edu/~radford
- Ng, Andrew - Reinforcement learning, machine learning.
www.cs.berkeley.edu/~ang
- Oja, Erkki - Unsupervised learning, PCA, ICA, SOM, statistical pattern recognition, image and signal analysis.
www.cis.hut.fi/oja
- Olshausen, Bruno - Visual coding, statistics of images, independent components analysis.
redwood.ucdavis.edu/bruno
- Opper, Manfred - Statistical physics, information theory and applied probability and applications to machien learning and complex systems.
www.ncrg.aston.ac.uk/People/opperm
- Paccanaro, Alberto - Learning distributed representation of concepts from relational data.
www.gatsby.ucl.ac.uk/~alberto
- Pathegama, Mahinda - Intelligent information systems, physiological sciences systems.
www.kes.unisa.edu.au/~mahinda/index.htm
- Phillips, Jonathon - Face recognition.
www.itl.nist.gov/iaui/894.03/staff/jonathon.html
- Rao, Rajesh P. N. - Models of human and computer vision.
www.cs.washington.edu/homes/rao
- Rasmussen, Carl Edward - Gaussian processes, non-linear Bayesian inference, evaluation and comparison of network models.
www.gatsby.ucl.ac.uk/~edward
- Revow, Michael - Hand-written character recognition.
www.cs.toronto.edu/~revow
- Roberts, Stephen - Machine learning and medical data analysis, independent component analysis and information theory.
www.robots.ox.ac.uk/~sjrob
- Rovetta, Stefano - Research on Machine Learning/Neural Networks/Clustering. Applications to DNA microarray data analysis/industrial automation/information retrieval. Teaching activities.
www.disi.unige.it/person/RovettaS
- Roweis, Sam T. - Speech processing, auditory scene analysis, machine learning.
www.cs.toronto.edu/~roweis
- Saad, David - Neural computing, error-correcting codes and cryptography using statistical and statistical mechanics techniques.
www.ncrg.aston.ac.uk/People/saadd
- Sahani, Maneesh - Statistical analysis of neural data, experimental design in neuroscience.
www.gatsby.ucl.ac.uk/~maneesh
- Sallans, Brian - Decision making under uncertainty, reinforcement learning, unsupervised learning.
www.gatsby.ucl.ac.uk/~sallans
- Saul, Lawrence K. - Machine learning, pattern recognition, neural networks, voice processing, auditory computation.
www.cis.upenn.edu/~lsaul
- Saund, Eric - Intermediate level structure in vision.
www.parc.xerox.com/spl/members/saund
- Schetinin, Vitaly - Biomedical data mining, diagnostic rule extraction and quality control in industry using a variety of techniques.
nnlab.tripod.com
- Sejnowski, Terry - Sensory representation in visual cortex, memory representation and adaptive organization of visuo-motor transformations.
www.salk.edu/faculty/sejnowski.html
- Seung, Sebastian - Short-term memory, learning and memory in the brain, computational learning theory.
hebb.mit.edu/people/seung
- Shuurmans, Dale - Computational learning, complex probability modelling.
www.lpaig.uwaterloo.ca:80/~dale
- Simard, Patrice - Machine learning and generalization.
www.research.microsoft.com/~patrice
- Smola, Alex J. - Kernel methods for prediction and data analysis.
mlg.anu.edu.au/~smola
- Storkey, Amos - Belief networks, Dynamic Trees, Probabilistic Methods in Astronomy, Gaussian processes and Hopfield Neural Networks.
www.anc.ed.ac.uk/~amos
- Sutton, Richard S. - Reinforcement learning.
www-anw.cs.umass.edu/~rich/sutton.html
- Teh, Yee Whye - Learning and inference in complex probabilistic models.
www.cs.utoronto.ca/~ywteh
- Tishby, Naftali - Machine learning; applications to human-computer interaction, vision,neurophysiology, biology and cognitive science.
www.cs.huji.ac.il/~tishby
- Tong, Simon - Machine learning, active learning, graphical models, support vector machines.
robotics.stanford.edu/~stong
- Wainwright, Martin - Statistical signal and image processing, natural image modelling, graphical models.
ssg.mit.edu/group/mjwain/mjwain.shtml
- Wallis, Guy - Object recognition, cognitive neuroscience, interaction between vision and motor movements.
www.uq.edu.au/~uqgwalli
- Weiss, Yair - Vision, Bayesian methods, neural computation.
www.cs.huji.ac.il/~yweiss
- Welling, Max - Unsupervised learning, probabilistic density estimation, machine vision.
www.cs.utoronto.ca/~welling
- Wiegerinck, Wim - Inference in graphical models, mean field and variational approaches.
www.mbfys.kun.nl/mbfys/people/wimw
- Williams, Christopher K. I. - Gaussian processes, image interpretation, graphical models, pattern recognition.
www.dai.ed.ac.uk/homes/ckiw
- Winther, Ole - Variational algorithms for Gaussian processes, neural networks and support vector machines. Also work on belief propagation and protein structure prediction.
eivind.imm.dtu.dk/staff/winther
- Wiskott, Laurenz - Face recognition, Invariances in learning and vision.
itb.biologie.hu-berlin.de/~wiskott/homepage.html
- Wu, Yingnian - Stochastic generative models for complex visual phenomena.
www.stat.ucla.edu/~ywu
- Wunsch II, Donald C. - Reinforcement Learning, Adaptive Critic Designs, Control, Optimization, Graph Theory, Bioinformatics, Intrusion Detection.
www.ece.umr.edu/~dwunsch
- Yedidia, Jonathan S. - Statistical methods for inference and learning.
www.merl.com/people/yedidia
- Zemel, Richard - Unsupervised learning, machine learning, computational models of neural processing.
www.cs.utoronto.ca/~zemel
- Zhu, Song Chun - Vision and graphics, statistical modelling and computing, neural computation.
www.cis.ohio-state.edu/~szhu
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