Over the past 20 years, we have demonstrated experience in building collaborations between academia, industry and government agencies as well as developed road maps for implementing new technologies at National and International levels. Fostering cooperation between Academia, Industries and Goverment agencies in different disciplines and the ability to lead projects across multiple disciplines are among our greatest strengths in leveraging relationships.

Our main scientific focus is in advances in science and innovation through disruptive and transformative technologies. During the past ~20 years, our research has been focused on development of novel algorithms for advanced data analytics and machine learning including state of the art neuro computing-deep learning and such deep neural networks, convolutional deep neural networks, deep belief networks and recurrent neural networks. Our main focus was on applications of Machine Learning and soft computing  for data fusion and mining with uncertain and incomplete information, predictive analytic, modeling forecasting and predicting future behaviors. 

We have applied computational intelligence techniques (existing tools, software, algorithms and our developed advanced systems) in a wide variety of fields  such as intelligent data and decision analysis and support systems, fault diagnosis and anomaly detection such as automated sensory inspection system with application to medical diagnosis and prognosis, fraud detection, and detection and analysis of the rare events, expert system, improvement of capabilities of internet and search engines and personalization to name a few. our computational intelligence includes neuro-fuzzy-gentic, decision trees, graph analytics, and deep learning architectures such as deep neural networks, deep Boltzmann and Restricted Boltzmann machine, convolutional deep neural networks, deep belief networks and recurrent neural networks.