Dr. Julian Allagan is a Full Professor of Mathematics and Director of Graduate Studies at Elizabeth City State University. He holds a M.S. degree in Applied Mathematics from Auburn University, Alabama, and a Ph.D. degree in Mathematics from Auburn University. He is currently Director of Graduate Studies and Full Professor in the Department of Mathematics, Computer Science, and Engineering Technology at Elizabeth City State University, North Carolina. His research expertise spans educational data mining, machine learning applications in mathematics education, psychometric analysis, graph theory, combinatorics, and cybersecurity applications. He serves as a peer reviewer for several mathematical, computer science, and statistical journals, including IEEE. His work includes graph and hypergraph polynomials, investigations of network vulnerabilities using graph theory techniques, the development of predictive models for complex systems analysis, and the integration of artificial intelligence with traditional psychometric methods for educational assessment optimization.
Dr. Julian Allagan is a Full Professor of Mathematics and Director of Graduate Studies at Elizabeth City State University. He holds a M.S. degree in Applied Mathematics from Auburn University, Alabama, and a Ph.D. degree in Mathematics from Auburn University. He is currently Director of Graduate Studies and Full Professor in the Department of Mathematics, Computer Science, and Engineering Technology at Elizabeth City State University, North Carolina. His research expertise spans educational data mining, machine learning applications in mathematics education, psychometric analysis, graph theory, combinatorics, and cybersecurity applications. He serves as a peer reviewer for several mathematical, computer science, and statistical journals, including IEEE. His work includes graph and hypergraph polynomials, investigations of network vulnerabilities using graph theory techniques, the development of predictive models for complex systems analysis, and the integration of artificial intelligence with traditional psychometric methods for educational assessment optimization.