Biography

Dr. Charles Kim is a professor in Electrical Engineering and Computer Science at Howard University.  He has experienced in applying information entropy and Bayesian inference as an intelligent and machine learning system to discrete time-series data for diagnostic detection, classification, and pattern discovery.  He has applied the machine reasoning to deal with electronic component assessment for radiation impact and sensitivity.  Recently, the application area has further extended to social science and human-terrain related problems for decision-making and behavior classification.  His present research is focused on prediction and classification applying entropy minimum principle and on the location determination of incipient self-clearing cable faults in power distribution systems using least-squares error approaches.  Dr. Kim earned his Ph.D. in electrical Engineering at Texas A&M University.