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Although my formal training is in physics, my research is at the intersection of computer science, cognitive science and neuroscience, engineering, and applied mathematics. I am particularly interested in developing new learning and classification models. In developing these models I use methods from computer science (e.g. artificial neural networks and Bayesian inference), mathematics (e.g. statistical pattern recognition), engineering (e.g. signal processing), and physics (e.g. statistical mechanics). In addition, the inspiration for constructing learning algorithms comes from human perception and the way information is processed by the human visual system.

Download Predrag (Pedja) Neskovic's Curriculum Vitae in PDF Format