RESEARCH INTERESTS

My primary academic interests are developing bio-inspired and nature-inspired techniques to Artificial Intelligence to gain insight into the optimization in the context of computational intelligence.

Over the past 4 years, I have studied meta-heuristics algorithms. Solving the real life problems is a challenging issue due to its complexity as the number of parameters to be optimized increases. This gives an opportunity for researchers to develop new techniques to address the issue. Thus, I have published a number of articles regarding the Meta-heuristics search to solve the optimization problems in the literature. Firstly, I started to improve a nature inspired algorithm and tested it in high dimensional problems successfully. Secondly, I employed the same algorithm in a real life problem, Supply Chain Cost. Although the problem was extremely difficult, the proposed algorithm performed superior to that of its competitors in terms of the solution quality and convergence rate to the optimal solution. Thirdly, I studied the large scale global optimization algorithms and developed a novel one to compete in this field. Therefore, I published a novel bio-inspired optimization algorithm.

Lately, I have been studying the Machine Learning algorithms.