My current research interests span several inter-related areas in the computer science and systems design engineering fields. The main area is the theory and the application of computational intelligence techniques, such as Fuzzy Logic, Artificial Neural Networks (ANN), Practical Swarm optimization, Artificial immune Systems (AIS) and evolutionary computing, to different real-life problems. In this field, my research focuses on the investigation of the impact of intelligent techniques and population based optimization algorithms on the performance of the data clustering. The application field of this research is mainly the health sector where our algorithms were applied to handle data clustering in different medical diseases such as diabetics and cancer. To handle this problem, an ensemble model integrating different artificial immune systems techniques was designed and implemented. The aim of this ensemble is to integrate different learning and adaptation algorithms to avoid the limitations of the individual algorithms and to achieve a synergistic effect through the combination of these techniques.
Another theme of my research is to investigate and apply the intelligent algorithms to problems that cannot be tackled by conventional methods. For example, several problems related to communication and high-speed networks such as topology design, resource management and multicasting are NP problems. Most of the algorithms proposed in the literature are heuristic based where it is usually difficult to estimate the convergence of the solution. The above computational intelligence techniques form an efficient alternative to conventional ones. They can be utilized to efficiently handle these NP problems. In this sense, we proposed and utilized an evolutionary algorithm that is based on population based incremental learning (PBIL) to tackle the several problems related to the communication networks such as the resource optimization of high-speed networks, topology design and wireless network design. In addition, a multicast solution based on the PBIL algorithm to generate the multicast tree in large network was proposed. The algorithm introduces an efficient trade-off between the delay on the network and the cost of the tree.
In addition to that, we have proposed several techniques to handle important issues related to robotics area. For example, a position/force control for cooperative manipulators was proposed based on Fuzzy Logic algorithm. This algorithm is efficient in compensating the inaccuracy experienced by two manipulators when dealing with a certain object. Another hybrid algorithm is proposed to enhance the first algorithm.
The second direction of my research interests, in addition to the computational intelligence ones, is the engineering of Technology-Enhanced Learning (TEL). Recently, TEL becomes of a vital importance in order to have an effective implementation of these technologies and systems in the different learning environments. The vast and rapid development in computer, communication and Internet technologies has significantly affected contemporary educational systems. The wide utilization of technology, the abundance of information and knowledge, and the use of multimedia applications, create challenges to present an efficient and attractive e-learning model that encompasses all these elements. This research theme is deduced to handle the real implementation of the national e-learning initiative in Kuwait. The research produced a unique blended e-learning model and implementation framework in both K12 environment and higher education. Kuwait Ministry of Education is following my model to implement the e-learning in all the schools. In addition, and based on these research activities, I have been selected by the Arab League Educational, Cultural and Scientific Organization (ALECSO) as one of the experts to present a study about 'The Open and Distant Education in the Arab World: Towards Development and Innovation', in the 14th conference of Arab Ministers of Higher Education, held in Riyadh, KSA in march 2014.