My current research are within the area of machine learning and data analytics. In previous years my research was concerned with developing nonlinear models that describe the complex relationship between the solar magnetic field and the Earths magnetic field. Building computational models of this relationship can lead to the development of advanced warning systems for geomagnetic storms. This is of critical importance to technological systems that society heavily depends on. The main focus was on Computational Intelligence based models ofgeomagnetic storms. One of the main computational intelligence based model in use in geomagnetic storm modeling is the recurrent neural network (RNN). I, along with my research collaborator (Dr Derrick Mirikitani) have developed sophisticated training algorithms for the RNN which allow for optimization of model priors and parameters for accurate prediction of Dst index , and the ability to forecast Dst and update model parameters online. Previously, I have done work in the areas of program slicing, the semantics of program slicing and program transformation. I was part of the Program Transformation and Analysis Group .