Dr. Richard S. Segall is Professor of Information Systems & Business Analytics in the Neil Griffin College of Business at Arkansas State University in Jonesboro, AR where has also taught for ten years in the Master of Engineering Management (MEM) Program in the College of Engineering & Computer Science. He is also Affiliated Faculty at the University of Arkansas at Little Rock (UALR) where he serves on thesis committees. He holds a Bachelor of Science and Master of Science in Mathematics as well as a Master of Science in Operations Research and Statistics from Rensselaer Polytechnic Institute in Troy, New York. He also holds a PhD in Operations Research form University of Massachusetts at Amherst, He has served on the faculty of Texas Tech University, University of Louisville, University of New Hampshire, University of Massachusetts-Lowell, and West Virginia University. His research interests include data mining, Big Data, text mining, web mining, database management, and mathematical modeling.
Dr. Segall‘s publications have appeared in numerous journals including International Journal of Information Technology and Decision Making (IJITDM), International Journal of Information and Decision Sciences (IJIDS), Applied Mathematical Modelling (AMM), Kybernetes, Journal of the Operational Research Society (JORS), Journal of Systemics, Cybernetics and Informatics (JSCI), International Journal of Artificial Intelligence and Machine Learning (IJAIML), International Journal of Open Source Software and Processes (IJOSSP), and International Journal of Fog Computing (IJFC). He has published book chapters in Encyclopedia of Data Warehousing and Mining, Handbook of Computational Intelligence in Manufacturing and Production Management,Handbook of Research on Text and Web Mining Technologies, Encyclopedia of Information Science & Technology, and Encyclopedia of Business Analytics & Optimization.
Dr. Segall was a member of the former Arkansas Center for Plant-Powered-Production (P3), and is a member of the Center for No-Boundary Thinking (CNBT), and on the Editorial Board of theInternational Journal of Data Mining, Modelling and Management (IJDMMM)) and International Journal of Data Science (IJDS), and served as Local Arrangements Chair of the MidSouth Computational Biology & Bioinformatics Society (MCBIOS) Conference that was hosted at Arkansas State University.
His research has been funded by National Research Council (NRC), U.S. Air Force (USAF), National Aeronautical and Space Administration (NASA), Arkansas Biosciences Institute (ABI), and Arkansas Science & Technology Authority (ASTA). He is recipient of several Session Best Paper awards at World Multi-Conference on Systemics, Cybernetics and Informatics (WMSCI) conferences. Dr.Segall is Lead Editor of several IGI Global books of: Biomedical and Business Applications using Artificial Neural Networks and Machine Learning, Open Source Software for Statistical Analysis of Big Data, Handbook of Big Data Storage and Visualization Techniques (2 volumes), and Research and Applications in Global Supercomputing, and is co-editor of Visual Analytics and Interactive Technologies: Data, Text and Web Mining Applications. Dr. Segall is recipient of Arkansas State University, Neil Griffin College of Business Faculty Award for Excellence in Research in 2015 and 2019, and the 2020 University Award in Scholarship (Research) of Arkansas State University.
Gao Niu is an Assistant Professor in Actuarial Science and Program Coordinator of Actuarial Math Program at Bryant University. He also serves as the Faculty Consultant of the Janet & Mark L Goldenson Center for Actuarial Research at the University of Connecticut. He has a doctorate in actuarial science from the University of Connecticut, is an Associate of the Casualty Actuarial Society and a Member of the American Academy of Actuaries. Dr. Niu has years of experience in academic actuarial research and consulting practice. His research area includes but not limited to the following: big data analytics application in insurance industry, property and casualty insurance practice, predictive modeling, agent-based modeling, financial planning, life insurance and health insurance pricing, reserving and data mining.