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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/ Schein, Andrew I. -
Machine learning approaches to data mining focussing on text mining applications.
http://www.cis.upenn.edu/~ais Amari, Shun-ichi -
Neural network learning, information geometry.
http://www.brain.riken.jp/labs/mns/amari/home-E.html LeCun, Yann -
Handwritten recognition, convolutional networks, image compression. Noted for LeNet.
http://yann.lecun.com/ 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/ 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 Murray, Alan -
Neural networks and VLSI hardware.
http://www.ee.ed.ac.uk/~afm/ Saund, Eric -
Intermediate level structure in vision.
http://www2.parc.com/spl/members/saund/ Olshausen, Bruno -
Visual coding, statistics of images, independent components analysis.
http://redwood.berkeley.edu/bruno Yedidia, Jonathan S. -
Statistical methods for inference and learning.
http://www.merl.com/people/yedidia/ Pearlmutter, Barak -
Neural networks, machine learning, acoustic source separation and localisation, independent component analysis, brain imaging.
http://www-bcl.cs.may.ie/~barak/ De vito, Saverio -
Neural networks for sensor fusion, wireless sensor networks, software modeling, multimedia assets management architectures
http://www.afs.enea.it/devito/ Paccanaro, Alberto -
Learning distributed representation of concepts from relational data.
http://homes.gersteinlab.org/people/alberto/ Joshi, Prashant -
Computational motor control, biologically realistic circuits, humanoid robots, spiking neurons.
http://www.igi.tugraz.at/joshi Jordan, Michael I. -
Graphical models, variational methods, machine learning, reasoning under uncertainty.
http://www.cs.berkeley.edu/~jordan/ Williams, Christopher K. I. -
Gaussian processes, image interpretation, graphical models, pattern recognition.
http://www.dai.ed.ac.uk/homes/ckiw/ Smola, Alex J. -
Kernel methods for prediction and data analysis.
http://mlg.anu.edu.au/~smola/ Zemel, Richard -
Unsupervised learning, machine learning, computational models of neural processing.
http://www.cs.utoronto.ca/~zemel/ Friedman, Nir -
Learning of probabilistic models, applications to computational biology.
http://www.cs.huji.ac.il/~nir/ Russell, Stuart -
Many aspects of probabilistic modelling, identity uncertainty, expressive probability models.
http://www.cs.berkeley.edu/~russell/ de Freitas, Nando -
Bayesian inference, Markov chain Monte Carlo simulation, machine learning.
http://www.cs.ubc.ca/~nando/ Freeman, William T. -
Bayesian perception, computer vision, image processing.
http://people.csail.mit.edu/billf/wtf.html Zhou, Zhi-Hua -
Neural computing, data mining, evolutionary computing, ensemble networks.
http://cs.nju.edu.cn/zhouzh/ Caruana, Rich -
Multitask learning.
http://www.cs.cmu.edu/~caruana/ Rutkowski, Leszek -
Neural networks, fuzzy systems, computational intelligence.
http://www.kik.pcz.czest.pl/~rutkowski/ 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 Wallis, Guy -
Object recognition, cognitive neuroscience, interaction between vision and motor movements.
http://www.uq.edu.au/~uqgwalli/ Becker, Sue -
Neural network models of learning and memory, computational neuroscience, unsupervised learning in perceptual systems.
http://www.science.mcmaster.ca/Psychology/sb.html Jensen, Finn Verner -
Graphical models, belief propagation.
http://www.cs.auc.dk/~fvj Leow, Wee Kheng -
Computer vision, computational olfaction.
http://www.comp.nus.edu.sg/~leowwk Seung, Sebastian -
Short-term memory, learning and memory in the brain, computational learning theory.
http://hebb.mit.edu/people/seung/ Dayan , Peter -
Representation and learning in neural processing systems, unsupervised learning, reinforcement learning.
http://www.gatsby.ucl.ac.uk/~dayan/ Bartlett, Marian Stewart -
Image analysis with unsupervised learning, face recognition, facial expression analysis.
http://ergo.ucsd.edu/~marni/ Hansen, Lars Kai -
Neural network ensembles, adaptive systems and applications in neuroinformatics.
http://eivind.imm.dtu.dk/staff/lkhansen/lkhansen.html Versace, Massimiliano -
Neural networks applied to visual perception and computational modeling of mental disorders.
http://www.maxversace.com Anthony, Martin -
Computational learning theory, discrete mathematics.
http://www.maths.lse.ac.uk/Personal/martin/ Meila, Marina -
Graphical models, learning in high dimensions, tree networks.
http://www.stat.washington.edu/mmp/ Lawrence, Neil -
Probabilistic models, variational methods.
http://www.dcs.shef.ac.uk/~neil Sykacek, Peter -
Brain Computer Interface.
http://www.robots.ox.ac.uk/~psyk/ Bulsari, A. -
Neural networks and nonlinear modelling for process engineering.
http://www.abo.fi/~abulsari Dahlem, Markus A. -
Neural network models of visual cortex to model neurological symptoms of migraine.
http://www.migraine-aura.org/EN/Markus_Dahlem.html Roweis, Sam T. -
Speech processing, auditory scene analysis, machine learning.
http://www.cs.toronto.edu/~roweis/ 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/ Sahani, Maneesh -
Statistical analysis of neural data, experimental design in neuroscience.
http://www.gatsby.ucl.ac.uk/~maneesh/ Allan, Moray -
Computer vision, probabilistic models for image sequences, invariant features.
http://www.morayallan.com/ Jaakkola, Tommi S. -
Graphical models, variational methods, kernel methods.
http://www.ai.mit.edu/people/tommi Chu, Selina -
Artificial intelligence, machine learning, data mining.
http://www-scf.usc.edu/~selinach Herbrich, Ralph -
Statistical learning theory, support vector machines and kernel methods.
http://www.research.microsoft.com/users/rherb/ McCallum, Andrew -
Machine learning, text and information retrieval and extraction, reinforcement learning.
http://www.cs.umass.edu/~mccallum/ Muresan, Raul C. -
Neural Networks, Spiking Neural Nets, Retinotopic Visual Architectures.
http://www.raulmuresan.home.ro/ Honavar, Vasant -
Constructive learning, computational learning theory, spatial learning, cognitive modelling, incremental learning.
http://www.cs.iastate.edu/~honavar/ 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 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/ Lawrence, Steve -
Information dissemination and retrieval, machine learning and neural networks.
http://labs.google.com/people/lawrence/ Brown, Andrew -
Machine learning of dynamic data, graphical models and Bayesian networks, neural networks.
http://www.ecs.soton.ac.uk/people/adb Malchiodi, Dario -
Machine learning, Learning from uncertain data.
http://homes.dsi.unimi.it/~malchiod/ Li, Zhaoping -
Non-linear neural dynamics, visual segmentation, sensory processing.
http://www.gatsby.ucl.ac.uk/~zhaoping Beveridge, Ross -
Computer vision, model-based object recognition, face recognition.
http://www.cs.colostate.edu/~ross/ Ballard, Dana H. -
Visual perception with neural networks.
http://www.cs.rochester.edu/users/faculty/dana Simard, Patrice -
Machine learning and generalization.
http://www.research.microsoft.com/~patrice/ MacKay, David -
Bayesian theory and inference, error-correcting codes, machine learning.
http://www.inference.phy.cam.ac.uk/mackay/ Hughes, Nicholas -
Automated Analysis of ECG.
http://www.robots.ox.ac.uk/~nph/ Garcia, Christophe -
Computer vision, image analysis, neural networks.
http://www.csd.uoc.gr/~cgarcia Bach, Francis -
Machine learning, kernel methods, kernel independent component analysis and graphical models
http://www.di.ens.fr/~fbach/ Saul, Lawrence K. -
Machine learning, pattern recognition, neural networks, voice processing, auditory computation.
http://www.cs.ucsd.edu/~saul/ Coolen, Ton -
Physics of disordered systems. Working on dynamic replica theory for recurrent neural networks.
http://www.mth.kcl.ac.uk/~tcoolen/ Wiskott, Laurenz -
Face recognition, Invariances in learning and vision.
http://itb.biologie.hu-berlin.de/~wiskott/homepage.html Kearns, Michael -
Reinforcement learning, probabilistic reasoning, machine learning, spoken dialogue systems.
http://www.cis.upenn.edu/~mkearns/ Welling, Max -
Unsupervised learning, probabilistic density estimation, machine vision.
http://www.cs.utoronto.ca/~welling Cottrell, Garrison W. -
An artrificial intelligence researcher who is an expert on neural networks.
http://charlotte.ucsd.edu/~gary/ Revow, Michael -
Hand-written character recognition.
http://www.cs.toronto.edu/~revow/ Heskes, Tom -
Learning and generalization in neural networks.
http://www.cs.ru.nl/~tomh/ Koller, Daphne -
Probabilistic models for complex uncertain domains.
http://ai.stanford.edu/~koller/ de Garis, Hugo -
Evolvable neural network models, neural networks for programmable hardware, large neural networks.
http://www.iss.whu.edu.cn/degaris/ 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/ Wiegerinck, Wim -
Inference in graphical models, mean field and variational approaches.
http://www.mbfys.ru.nl/mbfys/people/wimw/ Sallans, Brian -
Decision making under uncertainty, reinforcement learning, unsupervised learning.
http://members.chello.at/hoebertz-sallans/sallans/index.html Tishby, Naftali -
Machine learning; applications to human-computer interaction, vision,neurophysiology, biology and cognitive science.
http://www.cs.huji.ac.il/~tishby/ Rasmussen, Carl Edward -
Gaussian processes, non-linear Bayesian inference, evaluation and comparison of network models.
http://learning.eng.cam.ac.uk/carl/ Shuurmans, Dale -
Computational learning, complex probability modelling.
http://www.lpaig.uwaterloo.ca/~dale/ 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/ Olier, Ivan -
Artificial intelligence, generative topographic map, missing data.
http://www.lsi.upc.edu/~iaolier/ 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/ Murray-Smith, Roderick -
Gesture recognition, Gaussian Process priors, control systems, probabilistic intelligent interfaces.
http://www.dcs.gla.ac.uk/~rod/ Oja, Erkki -
Unsupervised learning, PCA, ICA, SOM, statistical pattern recognition, image and signal analysis.
http://www.cis.hut.fi/oja/ Attias, Hagai -
Graphical models, variational Bayes, independent factor analysis.
http://research.goldenmetallic.com/ Leen, Todd -
Online learning, machine learning, learning dynamics.
http://www.cse.ogi.edu/~tleen Wainwright, Martin -
Statistical signal and image processing, natural image modelling, graphical models.
http://www.eecs.berkeley.edu/~martinw/ Shkolnik, Alexander -
Neurally controlled robotics.
http://web.mit.edu/shkolnik/www/ Ghahramani, Zoubin -
Sensorimotor control, unsupervised learning, probabilistic machine learning.
http://www.gatsby.ucl.ac.uk/~zoubin Xing, Eric -
Statistical learning, machine learning approaches to computational biology, pattern recognition and control.
http://www.cs.cmu.edu/~epxing/ Roberts, Stephen -
Machine learning and medical data analysis, independent component analysis and information theory.
http://www.robots.ox.ac.uk/~sjrob/ Frey, Brendan J. -
Iterative decoding, unsupervised learning, graphical models.
http://www.psi.utoronto.ca/~frey/ Weiss, Yair -
Vision, Bayesian methods, neural computation.
http://www.cs.huji.ac.il/~yweiss/ Andrieu, Christophe -
Particle filtering and Monte Carlo Markov Chain methods.
http://www.stats.bris.ac.uk/~maxca/ Lerner, Uri N. -
Hybrid and Bayesian networks.
http://ai.stanford.edu/~uri/ Beal, Matthew J. -
Bayesian inference, variational methods, graphical models, nonparametric Bayes.
http://www.cse.buffalo.edu/faculty/mbeal 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 Minka, Thomas P. -
Machine learning, computer vision, Bayesian methods.
http://research.microsoft.com/~minka/ Teh, Yee Whye -
Learning and inference in complex probabilistic models.
http://www.cs.utoronto.ca/~ywteh Murphy, Kevin P. -
Graphical models, machine learning, reinforcement learning.
http://www.cs.berkeley.edu/~murphyk Neal, Radford -
Bayesian inference, Markov chain Monte Carlo methods, evaluation of learning methods, data compression.
http://www.cs.toronto.edu/~radford Adelson, Edward T. -
Visual perception, machine vision, image processing.
http://web.mit.edu/persci/people/adelson/ Lafferty, John D. -
Statistical machine learning, text and natural language processing, information retrieval, information theory.
http://www.cs.cmu.edu/~lafferty/ 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 Maass, Wolfgang -
Theory of computation, computation in spiking neurons.
http://www.igi.tugraz.at/maass/ Cheung, Vincent -
Machine learning and probabilistic graphical models for computer vision and computational molecular biology.
http://www.psi.toronto.edu/~vincent/ Boutilier, Craig -
Decision making and planning under uncertainty, reinforcement learning, game theory and economic models.
http://www.cs.toronto.edu/~cebly/ Bishop, Chris -
Graphical models, variational methods, pattern recognition.
http://research.microsoft.com/~cmbishop/ 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 Rao, Rajesh P. N. -
Models of human and computer vision.
http://www.cs.washington.edu/homes/rao/ Wu, Yingnian -
Stochastic generative models for complex visual phenomena.
http://www.stat.ucla.edu/~ywu/ Andonie, Razvan -
Data structures for computational intelligence.
http://www.cwu.edu/~andonie/ Dietterich, Thomas G. -
Reinforcement learning, machine learning, supervised learning.
http://cs.oregonstate.edu/~tgd/ Calvin, William H. -
Theoretical neurophysiologist and author of The Cerebral Code, How Brains Think.
http://faculty.washington.edu/wcalvin/ 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 Sutton, Richard S. -
Reinforcement learning.
http://www-anw.cs.umass.edu/~rich/sutton.html Agakov, Felix -
Probabilistic graphical modeling, statistical learning theory, pattern recognition, prediction, and causality.
http://www.inf.ed.ac.uk/people/staff/Felix_Agakov.html
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