People

Adelson, Edward T.
Visual perception, machine vision, image processing.
http://web.mit.edu/persci/people/adelson/

Agakov, Felix
Probabilistic graphical modeling, statistical learning theory, pattern recognition, prediction, and causality.
http://www.inf.ed.ac.uk/people/staff/Felix_Agakov.html

Allan, Moray
Computer vision, probabilistic models for image sequences, invariant features.
http://www.morayallan.com/

Amari, Shun-ichi
Neural network learning, information geometry.
http://www.brain.riken.jp/labs/mns/amari/home-E.html

Andonie, Razvan
Data structures for computational intelligence.
http://www.cwu.edu/~andonie/

Andrieu, Christophe
Particle filtering and Monte Carlo Markov Chain methods.
http://www.stats.bris.ac.uk/~maxca/

Anthony, Martin
Computational learning theory, discrete mathematics.
http://www.maths.lse.ac.uk/Personal/martin/

Attias, Hagai
Graphical models, variational Bayes, independent factor analysis.
http://research.goldenmetallic.com/

Bach, Francis
Machine learning, kernel methods, kernel independent component analysis and graphical models
http://www.di.ens.fr/~fbach/

Ballard, Dana H.
Visual perception with neural networks.
http://www.cs.rochester.edu/users/faculty/dana

Bartlett, Marian Stewart
Image analysis with unsupervised learning, face recognition, facial expression analysis.
http://ergo.ucsd.edu/~marni/

Beal, Matthew J.
Bayesian inference, variational methods, graphical models, nonparametric Bayes.
http://www.cse.buffalo.edu/faculty/mbeal

Becker, Sue
Neural network models of learning and memory, computational neuroscience, unsupervised learning in perceptual systems.
http://www.science.mcmaster.ca/Psychology/sb.html

Bengio, Samy
Torch machine learning library, including SVMTorch support vector machine program. Research on mixture models, hidden markov models, multimodal fusion, speaker verification.
http://www.idiap.ch/~bengio/index_en.html

Beveridge, Ross
Computer vision, model-based object recognition, face recognition.
http://www.cs.colostate.edu/~ross/

Bishop, Chris
Graphical models, variational methods, pattern recognition.
http://research.microsoft.com/~cmbishop/

Boutilier, Craig
Decision making and planning under uncertainty, reinforcement learning, game theory and economic models.
http://www.cs.toronto.edu/~cebly/

Brody, Carlos D.
Somatosensory working memory, computation with action potentials, design of complex stimuli for sensory neurophysiology.
http://www.cshl.edu/public/SCIENCE/brody.html

Brown, Andrew
Machine learning of dynamic data, graphical models and Bayesian networks, neural networks.
http://www.ecs.soton.ac.uk/people/adb

Bulsari, A.
Neural networks and nonlinear modelling for process engineering.
http://www.abo.fi/~abulsari

Calvin, William H.
Theoretical neurophysiologist and author of The Cerebral Code, How Brains Think.
http://faculty.washington.edu/wcalvin/

Caruana, Rich
Multitask learning.
http://www.cs.cmu.edu/~caruana/

Cheung, Vincent
Machine learning and probabilistic graphical models for computer vision and computational molecular biology.
http://www.psi.toronto.edu/~vincent/

Chu, Selina
Artificial intelligence, machine learning, data mining.
http://www-scf.usc.edu/~selinach

Coolen, Ton
Physics of disordered systems. Working on dynamic replica theory for recurrent neural networks.
http://www.mth.kcl.ac.uk/~tcoolen/

Cottrell, Garrison W.
An artrificial intelligence researcher who is an expert on neural networks.
http://charlotte.ucsd.edu/~gary/

Dahlem, Markus A.
Neural network models of visual cortex to model neurological symptoms of migraine.
http://www.migraine-aura.org/EN/Markus_Dahlem.html

Dayan , Peter
Representation and learning in neural processing systems, unsupervised learning, reinforcement learning.
http://www.gatsby.ucl.ac.uk/~dayan/

de Freitas, Nando
Bayesian inference, Markov chain Monte Carlo simulation, machine learning.
http://www.cs.ubc.ca/~nando/

de Garis, Hugo
Evolvable neural network models, neural networks for programmable hardware, large neural networks.
http://www.iss.whu.edu.cn/degaris/

De vito, Saverio
Neural networks for sensor fusion, wireless sensor networks, software modeling, multimedia assets management architectures
http://www.afs.enea.it/devito/

De Wilde, Philippe
Brain inspired models of uncertainty, linguistic and fuzzy uncertainty, uncertainty in dynamic multi-user environments.
http://www.macs.hw.ac.uk/~pdw/

Dietterich, Thomas G.
Reinforcement learning, machine learning, supervised learning.
http://cs.oregonstate.edu/~tgd/

Dr Hooman Shadnia
Dedicated to artificial neural networks and their applications in medical research and computational chemistry. Offers a quick tutorial on theory on ANNs written in Persian.
http://ca.geocities.com/shadnia/

Freeman, William T.
Bayesian perception, computer vision, image processing.
http://people.csail.mit.edu/billf/wtf.html

Frey, Brendan J.
Iterative decoding, unsupervised learning, graphical models.
http://www.psi.utoronto.ca/~frey/

Friedman, Nir
Learning of probabilistic models, applications to computational biology.
http://www.cs.huji.ac.il/~nir/

Frohlich, Jochen
Overview of neural networks, and explanation of Java classes that implement backpropagation, and Kohonen feature maps.
http://rfhs8012.fh-regensburg.de/~saj39122/jfroehl/diplom/e-index.html

Garcia, Christophe
Computer vision, image analysis, neural networks.
http://www.csd.uoc.gr/~cgarcia

Ghahramani, Zoubin
Sensorimotor control, unsupervised learning, probabilistic machine learning.
http://www.gatsby.ucl.ac.uk/~zoubin

Hansen, Lars Kai
Neural network ensembles, adaptive systems and applications in neuroinformatics.
http://eivind.imm.dtu.dk/staff/lkhansen/lkhansen.html

Herbrich, Ralph
Statistical learning theory, support vector machines and kernel methods.
http://www.research.microsoft.com/users/rherb/

Heskes, Tom
Learning and generalization in neural networks.
http://www.cs.ru.nl/~tomh/

Hinton, Geoffrey E.
Unsupervised learning with rich sensory input. Most noted for being a co-inventor of back-propagation.
http://www.cs.toronto.edu/~hinton/

Honavar, Vasant
Constructive learning, computational learning theory, spatial learning, cognitive modelling, incremental learning.
http://www.cs.iastate.edu/~honavar/

Hughes, Nicholas
Automated Analysis of ECG.
http://www.robots.ox.ac.uk/~nph/

Jaakkola, Tommi S.
Graphical models, variational methods, kernel methods.
http://www.ai.mit.edu/people/tommi

Jensen, Finn Verner
Graphical models, belief propagation.
http://www.cs.auc.dk/~fvj

Jordan, Michael I.
Graphical models, variational methods, machine learning, reasoning under uncertainty.
http://www.cs.berkeley.edu/~jordan/

Joshi, Prashant
Computational motor control, biologically realistic circuits, humanoid robots, spiking neurons.
http://www.igi.tugraz.at/joshi

Kearns, Michael
Reinforcement learning, probabilistic reasoning, machine learning, spoken dialogue systems.
http://www.cis.upenn.edu/~mkearns/

Koller, Daphne
Probabilistic models for complex uncertain domains.
http://ai.stanford.edu/~koller/

Lafferty, John D.
Statistical machine learning, text and natural language processing, information retrieval, information theory.
http://www.cs.cmu.edu/~lafferty/

Lawrence, Neil
Probabilistic models, variational methods.
http://www.dcs.shef.ac.uk/~neil

Lawrence, Steve
Information dissemination and retrieval, machine learning and neural networks.
http://labs.google.com/people/lawrence/

LeCun, Yann
Handwritten recognition, convolutional networks, image compression. Noted for LeNet.
http://yann.lecun.com/

Leen, Todd
Online learning, machine learning, learning dynamics.
http://www.cse.ogi.edu/~tleen

Leow, Wee Kheng
Computer vision, computational olfaction.
http://www.comp.nus.edu.sg/~leowwk

Lerner, Uri N.
Hybrid and Bayesian networks.
http://ai.stanford.edu/~uri/

Li, Zhaoping
Non-linear neural dynamics, visual segmentation, sensory processing.
http://www.gatsby.ucl.ac.uk/~zhaoping

Maass, Wolfgang
Theory of computation, computation in spiking neurons.
http://www.igi.tugraz.at/maass/

MacKay, David
Bayesian theory and inference, error-correcting codes, machine learning.
http://www.inference.phy.cam.ac.uk/mackay/

Malchiodi, Dario
Machine learning, Learning from uncertain data.
http://homes.dsi.unimi.it/~malchiod/

McCallum, Andrew
Machine learning, text and information retrieval and extraction, reinforcement learning.
http://www.cs.umass.edu/~mccallum/

Meila, Marina
Graphical models, learning in high dimensions, tree networks.
http://www.stat.washington.edu/mmp/

Minka, Thomas P.
Machine learning, computer vision, Bayesian methods.
http://research.microsoft.com/~minka/

Muresan, Raul C.
Neural Networks, Spiking Neural Nets, Retinotopic Visual Architectures.
http://www.raulmuresan.home.ro/

Murphy, Kevin P.
Graphical models, machine learning, reinforcement learning.
http://www.cs.berkeley.edu/~murphyk

Murray, Alan
Neural networks and VLSI hardware.
http://www.ee.ed.ac.uk/~afm/

Murray-Smith, Roderick
Gesture recognition, Gaussian Process priors, control systems, probabilistic intelligent interfaces.
http://www.dcs.gla.ac.uk/~rod/

Neal, Radford
Bayesian inference, Markov chain Monte Carlo methods, evaluation of learning methods, data compression.
http://www.cs.toronto.edu/~radford

Oja, Erkki
Unsupervised learning, PCA, ICA, SOM, statistical pattern recognition, image and signal analysis.
http://www.cis.hut.fi/oja/

Olier, Ivan
Artificial intelligence, generative topographic map, missing data.
http://www.lsi.upc.edu/~iaolier/

Olshausen, Bruno
Visual coding, statistics of images, independent components analysis.
http://redwood.berkeley.edu/bruno

Opper, Manfred
Statistical physics, information theory and applied probability and applications to machine learning and complex systems.
http://www.ncrg.aston.ac.uk/People/opperm/Welcome.html

Paccanaro, Alberto
Learning distributed representation of concepts from relational data.
http://homes.gersteinlab.org/people/alberto/

Pearlmutter, Barak
Neural networks, machine learning, acoustic source separation and localisation, independent component analysis, brain imaging.
http://www-bcl.cs.may.ie/~barak/

Prashant, Joshi
Computational neuroscientist, with main areas of research interest being computational motor control, computational models of olfaction, computation with spiking neurons, neurocomputational basis of working memory and decision making, learning in biologically realistic circuits.
http://www.klab.caltech.edu/~joshi/

Rao, Rajesh P. N.
Models of human and computer vision.
http://www.cs.washington.edu/homes/rao/

Rasmussen, Carl Edward
Gaussian processes, non-linear Bayesian inference, evaluation and comparison of network models.
http://learning.eng.cam.ac.uk/carl/

Revow, Michael
Hand-written character recognition.
http://www.cs.toronto.edu/~revow/

Roberts, Stephen
Machine learning and medical data analysis, independent component analysis and information theory.
http://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.
http://www.disi.unige.it/person/RovettaS/

Roweis, Sam T.
Speech processing, auditory scene analysis, machine learning.
http://www.cs.toronto.edu/~roweis/

Russell, Stuart
Many aspects of probabilistic modelling, identity uncertainty, expressive probability models.
http://www.cs.berkeley.edu/~russell/

Rutkowski, Leszek
Neural networks, fuzzy systems, computational intelligence.
http://www.kik.pcz.czest.pl/~rutkowski/

Saad, David
Neural computing, error-correcting codes and cryptography using statistical and statistical mechanics techniques.
http://www.ncrg.aston.ac.uk/People/saadd/Welcome.html

Sahani, Maneesh
Statistical analysis of neural data, experimental design in neuroscience.
http://www.gatsby.ucl.ac.uk/~maneesh/

Sallans, Brian
Decision making under uncertainty, reinforcement learning, unsupervised learning.
http://members.chello.at/hoebertz-sallans/sallans/index.html

Saul, Lawrence K.
Machine learning, pattern recognition, neural networks, voice processing, auditory computation.
http://www.cs.ucsd.edu/~saul/

Saund, Eric
Intermediate level structure in vision.
http://www2.parc.com/spl/members/saund/

Schein, Andrew I.
Machine learning approaches to data mining focussing on text mining applications.
http://www.cis.upenn.edu/~ais

Sejnowski, Terry
Sensory representation in visual cortex, memory representation and adaptive organization of visuo-motor transformations.
http://www.salk.edu/faculty/faculty_details.php?id=48

Seung, Sebastian
Short-term memory, learning and memory in the brain, computational learning theory.
http://hebb.mit.edu/people/seung/

Shkolnik, Alexander
Neurally controlled robotics.
http://web.mit.edu/shkolnik/www/

Shuurmans, Dale
Computational learning, complex probability modelling.
http://www.lpaig.uwaterloo.ca/~dale/

Simard, Patrice
Machine learning and generalization.
http://www.research.microsoft.com/~patrice/

Smola, Alex J.
Kernel methods for prediction and data analysis.
http://mlg.anu.edu.au/~smola/

Storkey, Amos
Belief networks, dynamic trees, image models, image processing, probabilistic methods in astronomy, scientific data mining, Gaussian processes and Hopfield neural networks.
http://www.anc.ed.ac.uk/~amos/

Sutton, Richard S.
Reinforcement learning.
http://www-anw.cs.umass.edu/~rich/sutton.html

Sykacek, Peter
Brain Computer Interface.
http://www.robots.ox.ac.uk/~psyk/

Teh, Yee Whye
Learning and inference in complex probabilistic models.
http://www.cs.utoronto.ca/~ywteh

Tipping, Mike
Varied machine learning and data analysis topics, including Bayesian inference, relevance vector machine, probabilistic principal component analysis and visualisation methods.
http://www.miketipping.com

Tishby, Naftali
Machine learning; applications to human-computer interaction, vision,neurophysiology, biology and cognitive science.
http://www.cs.huji.ac.il/~tishby/

Versace, Massimiliano
Neural networks applied to visual perception and computational modeling of mental disorders.
http://www.maxversace.com

Wainwright, Martin
Statistical signal and image processing, natural image modelling, graphical models.
http://www.eecs.berkeley.edu/~martinw/

Wallis, Guy
Object recognition, cognitive neuroscience, interaction between vision and motor movements.
http://www.uq.edu.au/~uqgwalli/

Weiss, Yair
Vision, Bayesian methods, neural computation.
http://www.cs.huji.ac.il/~yweiss/

Welling, Max
Unsupervised learning, probabilistic density estimation, machine vision.
http://www.cs.utoronto.ca/~welling

Wiegerinck, Wim
Inference in graphical models, mean field and variational approaches.
http://www.mbfys.ru.nl/mbfys/people/wimw/

Williams, Christopher K. I.
Gaussian processes, image interpretation, graphical models, pattern recognition.
http://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.
http://eivind.imm.dtu.dk/staff/winther/

Wiskott, Laurenz
Face recognition, Invariances in learning and vision.
http://itb.biologie.hu-berlin.de/~wiskott/homepage.html

Wu, Yingnian
Stochastic generative models for complex visual phenomena.
http://www.stat.ucla.edu/~ywu/

Xing, Eric
Statistical learning, machine learning approaches to computational biology, pattern recognition and control.
http://www.cs.cmu.edu/~epxing/

Yedidia, Jonathan S.
Statistical methods for inference and learning.
http://www.merl.com/people/yedidia/

Zemel, Richard
Unsupervised learning, machine learning, computational models of neural processing.
http://www.cs.utoronto.ca/~zemel/

Zhou, Zhi-Hua
Neural computing, data mining, evolutionary computing, ensemble networks.
http://cs.nju.edu.cn/zhouzh/