History

Dr. Georgiopoulos, the Director of the Lab, joined the University of Central Florida (UCF) in December of 1986. His research interests, at that time, were in communications with special emphasis on performance evaluation of direct sequence and frequency hopping multiple-access communication networks. In the early 1990's, he collabortaed with other colleagues from UCF on research related to Hopfield neural networks and ART neural networks. Since then, his work has been mostly focused in the field of neural networks, with strong concentration on ART neural network architectures. Since 1991, Dr. Georgiopoulos and his students have contributed a number of important theoretical results, and innovative ART algorithms. In 2001, he received an important grant from NSF, in conjunction with a number of other colleagues at UCF, whose primary focus was to teach Machine Learning research to undergraduate students at UCF. This grant oriented some of the activities in the ML² towards undergraduate research experiences. In 2003, an important collaboration has started between Dr. Georgiopoulos and colleagues at FIT that extended the focus of undergraduate research experiences to students from a variety of US institutions, including UCF and FIT. The ML² has benefited from the hard work and contributions of many other colleagues at UCF, too many to be mentioned in this short historical note. Dr. Georgiopoulos has collaborated with these colleagues on challenging problems related to smart antenna design, manufacturing, computer vision, computer generated forces modeling, and many others.

The ML² owes its existence to the strong interest of its members to organize and disseminate the work of the laboratory in the filed of Machine Learning and data-mining to the wider research and professional community. This way, future generations of the laboratory members can learn from this knowledge, and most importantly advance this knowledge further with their own contributions and innovations.

Vision

The vision of the ML² (Machine Learning Laboratory) is to promote research and education in Machine Learning by creating a community of learners and scholars, consisting of faculty members, graduate students and undergraduate students, whose research and educational focus is the field of Machine Learning and its applications.

In the process of achieving this vision the ML² aspires to create from its student ranks leaders in the field of Machine Learning that will continue impacting the field with their contributions, long after they leave the laboratory in pursuit of their dreams and aspirations.

More details of the organizational structure of the ML², its current members, and the strategies that the laboratory proposes to achieve this vision is described, in detail, in the laboratory's vision document.