Rate My Professor Michael Georgiopoulos

Georgiopoulos's research expertise lies in machine learning, with special emphasis on neural network algorithms and related applications, encompassing artificial neural networks, decision trees, kernel-based methods, evolutionary computation, pattern recognition, and data mining. He has produced over 285 publications, including the book Applications of Neural Networks in Electromagnetics (Artech House, 2001), 79 refereed journal articles such as "A fast outlier detection strategy for distributed high dimensional datasets with mixed attributes" (Data Mining and Knowledge Discovery, 2010) and "Pareto-Path Multi-Task Multiple Kernel Learning" (IEEE Transactions on Neural Networks and Learning Systems, 2015), 195 conference papers, and 11 book chapters. His scholarship has earned more than 5,500 citations and an h-index of 36 (as of 2017). Among his honors are Outstanding Researcher of the Year (1991, 1993), Engineer of the Year by IEEE Orlando Section (1992, 1994), multiple Teaching Incentive Productivity Awards, Research Incentive Award (2005), UCF Pegasus Award (2010), and induction into the University of Connecticut Academy of Engineering (2014). As Dean, he has overseen substantial growth, including increased enrollment, record degrees awarded, research funding rising from $22.89 million (FY13) to $54.4 million (FY22), and programs like EXCEL, which boosted STEM graduation rates by 50% and served over 5,000 students.