Artificial Intelligence: Neural Networks: People

Visual perception, machine vision, image processing.

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

Computer vision, probabilistic models for image sequences, invariant features.

Data structures for computational intelligence.

Particle filtering and Monte Carlo Markov Chain methods.

Computational learning theory, discrete mathematics.

Machine learning, kernel methods, kernel independent component analysis and graphical models

Visual perception with neural networks.

Image analysis with unsupervised learning, face recognition, facial expression analysis.

Bayesian inference, variational methods, graphical models.