Dr. Victoria Chen
Dr. Victoria Chen is a Professor of IMSE at UT Arlington. From 1993-2001, she was on the Industrial and Systems Engineering faculty at the Georgia Institute of Technology. She holds a B.S. in Mathematical Sciences from The Johns Hopkins University, and M.S. and Ph.D. in Operations Research and Industrial Engineering from Cornell University. Dr. Chen is actively involved with the Institute for Operations Research and Management Science (INFORMS), serving as cluster chair, session organizer/chair, and officers for the Informs Section on Data Mining and for the Forum for Women in OR/MS.
Dr. Chen’s research utilizes statistical perspectives to create new methodologies for operations research problems appearing in engineering and science. She has expertise in the design of experiments, statistical modeling, and data mining, particularly for computer experiments and stochastic optimization. She has studied applications in inventory forecasting, airline optimization, water reservoir networks, wastewater treatment, and air quality. Through her statistics-based approach, she has developed computationally tractable methods for stochastic dynamic programming, airline planning, and environmental decision-making. Her methods have provided solutions to previously unsolvable problems.
Dr. Bill Corley
Dr. Bill Corley is Professor of IMSE at UT Arlington, where he has been a faculty member since 1971. Prior to UT Arlington, Dr. Corley worked for IBM at Cape Kennedy in the space program, where he developed the computerized pre-launch checkout of the Saturn V rocket and for McDonnell Douglas in the defense industry, where he wrote computer simulations of anti-aircraft missiles. Dr. Corley holds a B.S. in Electrical Engineering and an M.S. in Information Science from the Georgia Institute of Technology, a Ph.D. in Systems Engineering from the University of Florida, and a Ph.D. in Mathematics from UT Arlington. He is a member of the Institute for Operations Research and Management Science (INFORMS) and a registered professional engineer in the State of Texas.
Dr. Corley's areas of expertise include systems engineering, mathematical modeling, network analysis, abstract optimization theory, functional analysis, statistics, game theory, fuzzy sets, discrete mathematics, and stochastic processes. His research interests range from the abstract to the applied. For example, he has developed abstract optimization theories for set-valued functions and for functions whose variables are sets, both which are now studied widely. In functional analysis, he has established a new type of hybrid fixed-point theorem.
In statistics, he has defined multivariate order statistics and, with Dr. Kim, developed a general family of recursive probability distributions subsuming various standard ones. He has discovered a new equilibrium for game theory, applied multiple criteria to network analysis, and used fuzzy sets to assess customer satisfaction. With Dr. Rosenberger, he has also developed an analytical method for constructing “small world” networks and the Constraint Optimal Selection Technique (COST) approach for linear programming, which is significantly more efficient for large-scale problems than present methods. He won the 2005 UT Arlington College of Engineering Lockheed Martin Award for teaching and was awarded a faculty research leave during 2006-2007.
Dr. Jay Rosenberger
Dr. Jay Rosenberger joined UTA in 2003, and he is the Director of the Center on Stochastic Modeling, Optimization, & Statistics (COSMOS). He is also the Founder and Director of the Healthcare Enterprise Research Center (HERC). He has a B.S. in Mathematics from Harvey Mudd College, an M.S. in Industrial Engineering from the University of California at Berkeley, and a Ph.D. in Industrial Engineering from the Georgia Institute of Technology. His research interests include mathematical optimization and simulation in transportation, defense, and health care. He is the original developer of SimAir, a simulation of airline operations, which is currently used by many airlines and airline consulting firms around the world. Dr. Rosenberger's graduate research on airlines won the First Place 2003 Pritsker Doctoral Dissertation award. Prior to joining the faculty at UTA, Dr. Rosenberger worked in the Operations Research and Decision Support Department at American Airlines, where he researched inventory control and revenue management for cargo operations. At UTA, Dr. Rosenberger teaches courses in engineering probability, operations research, linear programming, introduction to statistics and operations research, and combinatorial optimization. He is the former chair and cluster chair of the Institute for Operations Research and Management Science (INFORMS) Section on Health Applications. He has been a member of the Institute of Industrial Engineers since 2003. He is currently an associate editor of Omega: The International Journal of Management Science.
Dr. Shouyi Wang
Dr. Shouyi Wang is an Assistant Professor of IMSE Department at UT Arlington. Before joining the faculty at UT Arlington, Dr. Wang worked as a research associate in the Department of Industrial and Systems Engineering and the Integrated Brain Imaging Center (IBIC) at the University of Washington from 2011-2013. He earned his B.S. degree in Systems and Control Engineering from Harbin Institute of Technology, Harbin, China, M.S. degree in Systems and Control Engineering from Delft University of Technology, Delft, Netherlands, and Ph.D. degree in Industrial and Systems Engineering from Rutgers University, New Brunswick, New Jersey. Dr. Wang has interests in data mining, machine learning, pattern recognition, multivariate process monitoring and prediction, applied operation research, human-centered computing, and interactive intelligent human-machine systems. He has developed mathematical theories and algorithms to frame, model and optimize complex systems, and solve large-scale data mining and knowledge discovery problems in engineering and science. He has conducted research projects on intelligent learning control systems for humanoid walking robots, personalized healthcare online monitoring and decision-making systems using multivariate physiological signals, functional and diagnostic brain imaging analysis and brain network modeling, decision models for optimizing personalized motion management during PET/CT imaging for radiation therapy planning, real-time prediction/detection of mental states and cognitive activities using brain-computer interfaces. He is a member of Institute of Industrial Engineers (IIE), Institute for Operations Research and the Management Sciences (INFORMS), and Institute of Electrical and Electronics Engineers (IEEE).
Dr. Li Zeng
Dr. Li Zeng is Assistant Professor of IMSE at UT Arlington. She received a B.S. in Optical Engineering from Tsinghua University, Beijing, China, and an M.S. in Statistics and Ph.D. in Industrial Engineering from the University of Wisconsin, Madison. Before joining the faculty at UT Arlington, she worked in the Department of Industrial and Systems Engineering at UW-Madison as a research associate. Dr. Zeng’s research interest is mainly on statistical modeling and analysis of complex production and service systems, with specific focus on three types of problems, i.e., performance/quality measurement, monitoring and diagnosis. The goal is to characterize baseline system performance, detect changes and identify root causes for changes. She has applied her methodologies to various complex systems including manufacturing systems such as automobile assembly processes and nanocomposite fabrication processes, and health service delivery systems such as cardiac surgeries and nurse telephone triage services. She is a member of the Institute of Industrial Engineers (IIE) and the Institute for Operations Research and Management Science (INFORMS).