People :: Artificial Intelligence
People :: Cognitive

Adelson, Edward T. - Visual perception, machine vision, image processing.

Agakov, Felix - Probabilistic graphical modeling, statistical learning theory, pattern recognition, prediction, and causality.

Allan, Moray - Computer vision, probabilistic models for image sequences, invariant features.

Amari, Shun-ichi - Neural network learning, information geometry.

Andonie, Razvan - Data structures for computational intelligence.

Andrieu, Christophe - Particle filtering and Monte Carlo Markov Chain methods.
Meta Description: [ Vitaly Moroz∓apos;s Home Page ]

Anthony, Martin - Computational learning theory, discrete mathematics.

Attias, Hagai - Graphical models, variational Bayes, independent factor analysis.

404 Bach, Francis - Machine learning, kernel methods, kernel independent component analysis and graphical models

Ballard, Dana H. - Visual perception with neural networks.
Meta Description: [ My experiments examine the extent to which elemental visual representations are computed moment-by-moment explicitly for the immediate task, and the extent to which a more general-purpose visual representation is maintained and updated as the observer moves within a scene. ]

Bartlett, Marian Stewart - Image analysis with unsupervised learning, face recognition, facial expression analysis.

Beal, Matthew J. - Bayesian inference, variational methods, graphical models, nonparametric Bayes.
Meta Description: [ Course material for CSE SUNY at Buffalo ]

Becker, Sue - Neural network models of learning and memory, computational neuroscience, unsupervised learning in perceptual systems.

Bengio, Samy - Torch machine learning library, including SVMTorch support vector machine program. Research on mixture models, hidden markov models, multimodal fusion, speaker verification.

Beveridge, Ross - Computer vision, model-based object recognition, face recognition.

Bishop, Chris - Graphical models, variational methods, pattern recognition.
Meta Description: [ Christopher M. Bishop is Assistant Director at Microsoft Research, Cambridge ]

Boutilier, Craig - Decision making and planning under uncertainty, reinforcement learning, game theory and economic models.

Brody, Carlos D. - Somatosensory working memory, computation with action potentials, design of complex stimuli for sensory neurophysiology.
Meta Description: [ Cold Spring Harbor Laboratory is a research and educational institution. The Laboratory has research programs focusing on cancer, neurobiology, plant genetics, genomics and bioinformatics, and a broad educational mission, including the recently established Watson School of Biological Sciences. ]

404 Brown, Andrew - Machine learning of dynamic data, graphical models and Bayesian networks, neural networks.
Meta Description: [ Gatsby Computational Neuroscience Unit, University College London. Research interests: Machine Learning ]

Bulsari, A. - Neural networks and nonlinear modelling for process engineering.

Calvin, William H. - Theoretical neurophysiologist and author of The Cerebral Code, How Brains Think.

500 Caruana, Rich - Multitask learning.

Cheung, Vincent - Machine learning and probabilistic graphical models for computer vision and computational molecular biology.
Meta Description: [ Vincent Cheung is a researcher in machine learning and probabilistic graphical models for computer vision and computational molecular biology. ]

Chu, Selina - Artificial intelligence, machine learning, data mining.

Coolen, Ton - Physics of disordered systems. Working on dynamic replica theory for recurrent neural networks.

Cottrell, Garrison W. - An artrificial intelligence researcher who is an expert on neural networks.

Dahlem, Markus A. - Neural network models of visual cortex to model neurological symptoms of migraine.
Meta Description: [ Information about migraine with aura for practicing neurologists and patients. ]

Dayan , Peter - Representation and learning in neural processing systems, unsupervised learning, reinforcement learning.
Meta Description: [ Gatsby Computational Neuroscience Unit, University College London. Research interests: Reinforcement Learning, Computational Neuroscience, Machine Learning ]

de Freitas, Nando - Bayesian inference, Markov chain Monte Carlo simulation, machine learning.

de Garis, Hugo - Evolvable neural network models, neural networks for programmable hardware, large neural networks.

404 de Sa, Virginia - Supervised and unsupervised learning, cross-modal learning.

De vito, Saverio - Neural networks for sensor fusion, wireless sensor networks, software modeling, multimedia assets management architectures
Meta Description: [ Research HP of Saverio De Vito ]

De Wilde, Philippe - Brain inspired models of uncertainty, linguistic and fuzzy uncertainty, uncertainty in dynamic multi-user environments.
Meta Description: [ top-level home page ]

Dietterich, Thomas G. - Reinforcement learning, machine learning, supervised learning.

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.
Meta Description: [ Home Page of Dr Hooman Shadnia, Contact Info, ANN, ANN2, Isfahan, Panorama, Molecular Modeling, Computational Chemistry, Free Download, 3D Chem, Art, FDIN, Food & Diet Info Network ]

404 Freeman, William T. - Bayesian perception, computer vision, image processing.
Meta Description: [ MERL - Mitsubishi Electric Research Laboratories ]

Frey, Brendan J. - Iterative decoding, unsupervised learning, graphical models.

Friedman, Nir - Learning of probabilistic models, applications to computational biology.

Frohlich, Jochen - Overview of neural networks, and explanation of Java classes that implement backpropagation, and Kohonen feature maps.

404 Fujita, Hajime - Partially observable markov decision processes (POMDP), reinforcement learning, multi-agent systems.

Garcia, Christophe - Computer vision, image analysis, neural networks.
Meta Description: [ home page, greece, computer vision, image processing, neural networks, face detection, text detection, stereo vision, hand-eye, camera calibration, Janus, Matis3D, DiVAN, PISTE, Nemesis ]

Ghahramani, Zoubin - Sensorimotor control, unsupervised learning, probabilistic machine learning.

Hansen, Lars Kai - Neural network ensembles, adaptive systems and applications in neuroinformatics.

Herbrich, Ralph - Statistical learning theory, support vector machines and kernel methods.

Heskes, Tom - Learning and generalization in neural networks.

Hinton, Geoffrey E. - Unsupervised learning with rich sensory input. Most noted for being a co-inventor of back-propagation.
Meta Description: [ Geoffrey Hinton : index ]

Honavar, Vasant - Constructive learning, computational learning theory, spatial learning, cognitive modelling, incremental learning.
Meta Description: [ ISU Computer Science Department ]

500 Hopfield, John J. - Neural networks, collective behaviour of systems of simple processors. Most noted for Hopfield networks.

Hughes, Nicholas - Automated Analysis of ECG.

Jaakkola, Tommi S. - Graphical models, variational methods, kernel methods.

Jensen, Finn Verner - Graphical models, belief propagation.

Jordan, Michael I. - Graphical models, variational methods, machine learning, reasoning under uncertainty.

Joseph Wakeling's Neural Systems Research Page - Research papers and information on biologically inspired neural networks, brain modelling, AI and related topics. A cross-disciplinary site mixing information from physics, neuroscience, cognitive science and other fields.
Meta Description: [ Neuro research by Joseph Wakeling, including research papers and information on biologically inspired neural networks, brain modelling, AI and related topics. A cross-disciplinary site mixing information from physics, neuroscience, cognitive science and other fields. ]

Joshi, Prashant - Computational motor control, biologically realistic circuits, humanoid robots, spiking neurons.
Meta Description: [ Prashant Joshi - Homepage ]

Kakade, Sham - Reinforcement learning and conditioning, mathematical models of neural processing.

Kali, Szabolcs - Learning and memory in the brain, hippocampus.
Meta Description: [ Gatsby Computational Neuroscience Unit, University College London. Research interests: Sensorimotor Control, Computational Neuroscience, Machine Learning ]

404 Kappen, Bert - Boltzmann machines, computational neurobiology, online learning.

Kearns, Michael - Reinforcement learning, probabilistic reasoning, machine learning, spoken dialogue systems.

404 Keysers, Daniel - Pattern recognition and statistical modelling for object recognition.

Koller, Daphne - Probabilistic models for complex uncertain domains.

404 Lafferty, John D. - Statistical machine learning, text and natural language processing, information retrieval, information theory.

500 Lawrence, Neil - Probabilistic models, variational methods.

Lawrence, Steve - Information dissemination and retrieval, machine learning and neural networks.

LeCun, Yann - Handwritten recognition, convolutional networks, image compression. Noted for LeNet.

Leen, Todd - Online learning, machine learning, learning dynamics.

Leow, Wee Kheng - Computer vision, computational olfaction.

Lerner, Uri N. - Hybrid and Bayesian networks.

Li, Zhaoping - Non-linear neural dynamics, visual segmentation, sensory processing.
Meta Description: [ Li Zhaoping, Psychology Department, Gatsby Computational Neuroscience Unit, University College London. Research interests: Natural intelligence, Computational Vision, Olfaction, neural networks, Computational Neuroscience ]

404 Maass, Wolfgang - Theory of computation, computation in spiking neurons.

MacKay, David - Bayesian theory and inference, error-correcting codes, machine learning.

McCallum, Andrew - Machine learning, text and information retrieval and extraction, reinforcement learning.

Meila, Marina - Graphical models, learning in high dimensions, tree networks.

500 Mika, Sebastian - Machine learning and explorative data analysis: support vector machines, kernel principal component analysis and kernel Fisher discriminant analysis.

Minka, Thomas P. - Machine learning, computer vision, Bayesian methods.

404 Morris, Quaid - Machine learning for medical diagnosis and biological data analysis.

500 Muresan, Raul C. - Neural Networks, Spiking Neural Nets, Retinotopic Visual Architectures.

Murphy, Kevin P. - Graphical models, machine learning, reinforcement learning.

Murray, Alan - Neural networks and VLSI hardware.

500 Murray-Smith, Roderick - Gesture recognition, Gaussian Process priors, control systems, probabilistic intelligent interfaces.

Neal, Radford - Bayesian inference, Markov chain Monte Carlo methods, evaluation of learning methods, data compression.

404 Ng, Andrew - Reinforcement learning, machine learning.

Oja, Erkki - Unsupervised learning, PCA, ICA, SOM, statistical pattern recognition, image and signal analysis.

Olier, Ivan - Artificial intelligence, generative topographic map, missing data.

500 Olshausen, Bruno - Visual coding, statistics of images, independent components analysis.

Opper, Manfred - Statistical physics, information theory and applied probability and applications to machine learning and complex systems.

Paccanaro, Alberto - Learning distributed representation of concepts from relational data.
Meta Description: [ Gatsby Computational Neuroscience Unit, University College London. Research interests: Neural Networks, Machine Learning, Computational Neuroscience, Artificial Intelligence, Vision ]

500 Pathegama, Mahinda - Intelligent information systems, physiological sciences systems.

Pearlmutter, Barak - Neural networks, machine learning, acoustic source separation and localisation, independent component analysis, brain imaging.

404 Phillips, Jonathon - Face recognition.

Rao, Rajesh P. N. - Models of human and computer vision.

Rasmussen, Carl Edward - Gaussian processes, non-linear Bayesian inference, evaluation and comparison of network models.

Revow, Michael - Hand-written character recognition.

Roberts, Stephen - Machine learning and medical data analysis, independent component analysis and information theory.

Rovetta, Stefano - Research on Machine Learning/Neural Networks/Clustering. Applications to DNA microarray data analysis/industrial automation/information retrieval. Teaching activities.
Meta Description: [ Stefano Rovetta's home page at the Department of Computer and Information Science of the University of Genova, Italy. Research in machine learning, neural networks, electronic engineering, computer science. Stefano Rovetta also studies applications of these technologies in bio... ]

Roweis, Sam T. - Speech processing, auditory scene analysis, machine learning.
Meta Description: [ sam roweis : index ]

Russell, Stuart - Many aspects of probabilistic modelling, identity uncertainty, expressive probability models.

Rutkowski, Leszek - Neural networks, fuzzy systems, computational intelligence.

Saad, David - Neural computing, error-correcting codes and cryptography using statistical and statistical mechanics techniques.

Sahani, Maneesh - Statistical analysis of neural data, experimental design in neuroscience.

404 Sallans, Brian - Decision making under uncertainty, reinforcement learning, unsupervised learning.
Meta Description: [ Gatsby Computational Neuroscience Unit, University College London. Research interests: Machine Learning ]

404 Saul, Lawrence K. - Machine learning, pattern recognition, neural networks, voice processing, auditory computation.

Saund, Eric - Intermediate level structure in vision.

Schein, Andrew I. - Machine learning approaches to data mining focussing on text mining applications.

Schetinin, Vitaly - Biomedical data mining, diagnostic rule extraction and quality control in industry using a variety of techniques.

Sejnowski, Terry - Sensory representation in visual cortex, memory representation and adaptive organization of visuo-motor transformations.

Seung, Sebastian - Short-term memory, learning and memory in the brain, computational learning theory.

Shkolnik, Alexander - Neurally controlled robotics.
Meta Description: [ Alec Shkolnik: current projects in Artificial Intelligence and Neuroscience, CV, and links to family and friends. ]

Shuurmans, Dale - Computational learning, complex probability modelling.

Simard, Patrice - Machine learning and generalization.

Smola, Alex J. - Kernel methods for prediction and data analysis.

Storkey, Amos - Belief networks, dynamic trees, image models, image processing, probabilistic methods in astronomy, scientific data mining, Gaussian processes and Hopfield neural networks.
Meta Description: [ Storkey: Amos Storkey information pages. Amos Storkey is a lecturer (assistant professor) in Informatics at the University of Edinburgh. ]

Sutton, Richard S. - Reinforcement learning.

Sykacek, Peter - Brain Computer Interface.

Teh, Yee Whye - Learning and inference in complex probabilistic models.
Meta Description: [ Yee, Whye, Teh, ywteh, tehyw ]

Tipping, Mike - Bayesian learning, relevance vector machine, probabilistic principal component analysis.

Tishby, Naftali - Machine learning; applications to human-computer interaction, vision,neurophysiology, biology and cognitive science.

Versace, Massimiliano - Neural networks applied to visual perception and computational modeling of mental disorders.
Meta Description: [ Home page of Massimiliano Versace. I received my BA in Experimental Psychology from the University of Trieste, Italy. I am currently a PhD candidate at the Department of Cognitive and Neural Systems at Boston University. My research interests are focused on neural networks - in particular applied... ]

Wainwright, Martin - Statistical signal and image processing, natural image modelling, graphical models.

Wallis, Guy - Object recognition, cognitive neuroscience, interaction between vision and motor movements.

Weiss, Yair - Vision, Bayesian methods, neural computation.

Welling, Max - Unsupervised learning, probabilistic density estimation, machine vision.

Wiegerinck, Wim - Inference in graphical models, mean field and variational approaches.

Williams, Christopher K. I. - Gaussian processes, image interpretation, graphical models, pattern recognition.

Winther, Ole - Variational algorithms for Gaussian processes, neural networks and support vector machines. Also work on belief propagation and protein structure prediction.

Wiskott, Laurenz - Face recognition, Invariances in learning and vision.

Wu, Yingnian - Stochastic generative models for complex visual phenomena.

404 Wunsch II, Donald C. - Reinforcement Learning, Adaptive Critic Designs, Control, Optimization, Graph Theory, Bioinformatics, Intrusion Detection.

Xing, Eric - Statistical learning, machine learning approaches to computational biology, pattern recognition and control.
Meta Description: [ Eric Poe Xing's homepage at Carnegie Mellon University ]

Yedidia, Jonathan S. - Statistical methods for inference and learning.
Meta Description: [ MERL - Mitsubishi Electric Research Laboratories ]

Zemel, Richard - Unsupervised learning, machine learning, computational models of neural processing.

404 Zhou, Zhi-Hua - Neural computing, data mining, evolutionary computing, ensemble networks.
Meta Description: [ Personal Homepage ]