Development of intelligent systems and discovering mechanisms for intelligent behavior is one of the most exciting research areas in science and engineering. With the recent development of brain research and modern technologies, scientists and engineers will hopefully find efficient ways to build complex systems that are highly robust, adaptive, and fault tolerant to uncertain environments. However, although tremendous progress have been made, there is still no clear picture about how to design brain-like general-purpose intelligent machines. One of the key challenges is how to develop general models, algorithms, and architectures that are able to adaptively learn and accumulate knowledge, make predictions in an uncertain and unstructured environment, and adjust actions to maximize some kind of utility function over time to achieve goals (goal-oriented behaviors). Toward this long-term objective, our group focuses on the fundamental research on computational intelligence, with a particular focus on neural networks, deep learning, reinforcement learning, and data mining.