Milos Manic is a professor in the Department of Computer Science at Virginia Commonwealth University. Manic’s research interests include data mining and machine learning applied to cyber security, critical infrastructure protection, energy security, and resilient intelligent control. He has over 20 years of academic and industrial experience in applied research in computational intelligence algorithms, such as artificial neural networks, fuzzy logic systems, and unsupervised learning techniques. He applies these methods in the areas of energy, cyber security, human-machine interfacing, intelligent control systems, software defined networks, robotics, and visualizations.
His previous experience includes a tenured position with the University of Idaho; directorship of the Computer Science program at Idaho Falls, University of Nis, Serbia; and a fellowship with the Brain Korea 21 program. He has completed over 30 research projects in the area of data mining and machine learning applied to energy optimization, resilient control, and human-machine interaction.
Manic has given over 30 invited talks around the world, authored over 180 refereed articles in international journals, books, and conferences, holds several U.S. patents, and won a 2018 R&D 100 award. He is an IEEE Industrial Electronics Society officer and is a member of various IEEE standing and technical committees and boards. He is also involved in various capacities with technical committees on education, industrial informatics, factory automation, smart grids, standards, and web and information; is a co-founder and past chair of technical committees on resilience and security in industry; and a general chair of IEEE conferences in 2018 and 2019.
He earned a Ph.D. in computer science in 2003 from the University of Idaho; a master's in computer science in 1996 from the the University of Nis, Serbia; and an undergraduate degree in electrical engineering in 1991 from the University of Nis, Serbia.