The umbrella that covers our research efforts is the area of what we refer to as Applied Intelligence. The goal of this line of research is to study and develop engineering systems that have "brain-like" behavior. This general area brings together several other areas of research such as : Physical System Modeling, Nonlinear Control, Adaptive Control, Robust Control, System Identification, System Diagnostics, Neural Networks, Fuzzy Systems and Genetic Algorithms to name the most relevant.

Most of the recent efforts of our research have been towards Automated Modeling of physical systems (AMPS) , the representation of their dynamics, system identification (with generalized mapping of recurrent neural networks) , robust fault diagnostics (RFD) what we call optimally-robust adaptive control (ORACL, adaptive robust-optimal control with memory) and genetically engineered neural networks (GEN ²).

Next , we hope to explore the areas of knowledge representation, acquisition and generalization, as well as implementation issues in the realm of evolutionary programming.