My work is, in general, about fundamental research on Machine Learning and Optimization, two most important problems in Artificial Intelligence. I'm also frequently attracted by other relevant domains, such as Smart Logistics, Structural and Multi-Disciplinary Optimization and Computational Finance, for which applied research is required to produce application-oriented learning and optimization techniques.

More specifically, most of my research could also be viewed as arising from Evolutionary Computation, which is essentially a distributed heuristic search framework widely applicable for modelling, learning and optimization problems, especially for hard problems such as Black-Box Optimization, Multi-Objective Optimization and Dynamic Optimization.

Details regarding my research could be found at NICAL