Gail Carpenter

In recent years, Professor Gail Carpenter has defined a novel approach to information fusion, showing how a neural model based on cognitive learning principles can derive consistent knowledge from sources that are paradoxically both inconsistent and accurate, as when a young child hears the family pet variously called Spot, puppy, dog, Dalmatian, mammal, and animal. Even though no inter-class relationships, links, or probabilities are provided during training, a distributed learning system derives knowledge of relationship rules, confidence estimates, equivalence classes, and hierarchical structures. Other aspects of her research include the development, computational analysis, and application of neural models of vision, synaptic transmission, and circadian rhythms. Her work in vision has ranged from models of the retina to color processing and long-range figure completion.

• Applied mathematics and dynamical systems , behavioral and neural modeling, neuromorphic technology.