Prof. Panos M. PardalosUniversity of Florida, USA
Panos M. Pardalos serves as distinguished professor of industrial and systems engineering at the University of Florida. Additionally, he is the Paul and Heidi Brown Preeminent Professor of industrial and systems engineering. He is also an affiliated faculty member of the computer and information science Department, the Hellenic Studies Center, and the biomedical engineering program. He is also the director of the Center for Applied Optimization. Pardalos is a world leading expert in global and combinatorial optimization. His recent research interests include network design problems, optimization in telecommunications, e-commerce, data mining, biomedical applications, and massive computing.
Prof. Jin WangValdosta State University, USA
Jin Wang is a Professor of Operations Research in the Department of Mathematics at Valdosta State University, USA. He received his Ph.D. degree from the School of Industrial Engineering at Purdue University in 1994. His research interests include Operations Research, Stochastic Modeling and Optimization, Supply Chain Management, Monte Carlo Simulation, Computational Finance, Portfolio Management, and Applied Probability and Statistics. Currently, he is working on Big Data and Data Mining fields. He has more than 28 years collegiate teaching experience in the field of quantitative methods and statistics at Purdue University, Florida State University, Auburn University, and Valdosta State University. Dr. Wang has been active in professional research activities. He has authored articles for publication in referred journals and conference proceedings. He has been active in INFORMS, IIE, and the Winter Simulation Conference and invited to give presentations, organize and chair sessions at national meetings. He has participated as a principal investigator in several research projects funded by federal and industrial agencies, including the National Science Foundation, General Motors, and the National Science Foundation of P.R. China. He was invited as a panel member at the National Science Foundation Workshop. Dr. Wang also served as a consultant for financial firms. His analytical Monte Carlo method using a multivariate mixture of normal distributions to simulate market data has made a great impact in education and the finance industry. This algorithm was selected as a graduate-level research project topic for many schools, such as, Columbia University Management Department, Carnegie Mellon University Economics and Finance Department, Tilburg University in Holland, Technische Universitaet Munich in Germany, Imperial College in London. This method was also implemented in many financial companies, such as, Zurcher Kantonal Bank, IRQ, Zurich Switzerland, Klosbachstrasse, Zurcher, Switzerland, Norsk Regnesentral in Norway, Cutler Group, L.P., Altis Partners (Jersey) Limited, Windham Capital Management, LLC..
Assoc. Prof. Jianping WangWebster University, USA
Dr. JiangPing Wang has a BA in Electrical Engineering from Chongqing University, Chongqing, China, a MS in Information Systems from the University of Leeds, Leeds, United Kingdom and a PhD in Engineering Management from the Missouri University of Science and Technology, Rolla, Missouri. Dr. Wang's areas of teaching include database design, database applications, data warehousing, web databases, database in web services, distributed application development, computer programming, operating systems and computer architecture. His areas of research include database management systems, decision support systems, business intelligence, e-commerce data processing, and software project management. Dr. Wang has been published in Web Enabled Online Analytical Processing for Intelligent Business Decision-Making and the proceedings of 10th Wuhan International Conference on E-Business.