Contributors

Ali E. Abbas (“ One-Switch Independence for Multiattribute Utility Functions ”) is an associate professor in the Department of Industrial and Enterprise Systems Engineering at the University of Illinois at Urbana–Champaign. He received an M.S. in electrical engineering (1998), an M.S. in engineering economic systems and operations research (2001), a Ph.D. in management science and engineering (2004), and a Ph.D. (minor) in electrical engineering, all from Stanford University. His research interests include utility theory, decision making with incomplete information and preferences, dynamic programming, and information theory. He is a senior member of the IEEE, a member of the Institute for Operations Research and the Management Sciences (INFORMS), a former council member of the Decision Analysis Society of INFORMS, an organizer of several decision analysis conferences, and has served on various committees of INFORMS including the decision analysis student paper award and the Junior Faculty Initiative Group. He is also an associate editor for the INFORMS journals Decision Analysis and Operations Research and coeditor of the DA column in education for Decision Analysis Today. Shipra Agrawal (“ A Unified Framework for Dynamic Prediction Market Design ”) is a Ph.D. student in the Department of Computer Science at Stanford University, working under the direction of Yinyu Ye. Her current research interests include online and stochastic optimization, prediction markets, and game theory. Sigrún Andradóttir (“ Queueing Systems with Synergistic Servers ”) is a professor in the H. Milton Stewart School of Industrial and Systems Engineering at the Georgia Institute of Technology. Her research interests are in the simulation and applied probability fields. More specifically, her research is focused on increasing the efficiency of stochastic simulations so that larger and more complex systems can be analyzed and optimized via simulation, and on determining how organizations can utilize flexible resources more effectively. U. Ayesta (“ Heavy-Traffic Analysis of a Multiple-Phase Network with Discriminatory Processor Sharing ”) is an IKERBASQUE researcher at the Basque Center for Applied Mathematics, Derio, Spain. Previously he was a CNRS researcher at LAAS, Toulouse, France and an ERCIM postdoc fellow at CWI, Amsterdam, The Netherlands. He received the Ph.D. degree in computer science from Universite de Nice–Sophia Antipolis (France). His Ph.D. research work was carried out at the research laboratories of INRIA (MAESTRO team) and France Telecom R&D. Urtzi Ayesta holds an M.Sc. degree in electrical engineering from Columbia University and a Diplome in telecommunication engineering from Nafarroako Unibertsitate Publikoa-Universidad Publica de Navarra (Spain). Hayriye Ayhan (“ Queueing Systems with Synergistic Servers ”) is a professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Institute of Technology. Her interests lie in the area of analysis and control of queueing systems. The paper in this issue, coauthored with S. Andradóttir and D. G. Down, is a result of the authors' common interest in developing dynamic server assignment policies that maximize throughput in queueing networks with flexible servers. David E. Bell (“ One-Switch Independence for Multiattribute Utility Functions ”) is a professor at Harvard Business School. Like the current paper, most of his work has centered on finding ways to assess multiattribute utility functions accurately but tractably. His first papers in Operations Research, on integer programming and on utility functions for time streams, appeared in 1977. His best known Operations Research paper, on regret, appeared in 1982. He was an early chair of the Decision Analysis Society, was the program chair of the 1976 ORSA-TIMS conference in Boston, and was awarded the 2001 Ramsey Medal. Bahar Biller (“ Accounting for Parameter Uncertainty in Large-Scale Stochastic Simulations with Correlated Inputs ”) is an assistant professor of operations management and manufacturing at Carnegie Mellon University. Her primary research interest lies in the area of computer simulation experiments for stochastic systems and, more specifically, in the simulation methodology for dependent input processes with applications to financial markets and global supply chains. Arnab Bisi (“ A Periodic-Review Base-Stock Inventory System with Sales Rejection ”) is an assistant professor at the Krannert School of Management of Purdue University. His research and teaching interests include stochastic models, statistics, inventory. and supply chain management. He received a Ph.D. in mathematics and statistics from Hong Kong University of Science and Technology, an M.Stat. degree from the Indian Statistical Institute, and a B.Sc. in statistics from the University of Calcutta. Chien-Ming Chen (“ Efficient Resource Allocation via Efficiency Bootstraps: An Application to R&D Project Budgeting ”) is an assistant professor of operations management at the Nanyang Business School (NBS) of Nanyang Technological University in Singapore. Prior to his position at NBS, he was a postdoctoral scholar and lecturer at the UCLA Institute of the Environment and Sustainability. His main research interests include environmental issues in operations and management, as well as theories and applications of production economics. His research work has been published in Production and Operations Management, the European Journal of Operational Research, and other publications. Yihsu Chen (“ Economic and Emissions Implications of Load-Based, Source-Based, and First-Seller Emissions Trading Programs Under California AB32 ”) is an assistant professor in environmental economics at the University of California, Merced, with a joint appointment between the School of Social Sciences, Humanities and Arts and the School of Engineering. He is also an affiliated researcher with PSERC (Power Systems Engineering Research Center), UCE3 (University of California Center for Energy and Environmental Economics) and SNRI (Sierra Nevada Research Institute.) His research focuses on understanding industry's response to energy and environmental regulations. His current research also explores the impacts of transportation infrastructure on the local air quality and human health. Sofie Coene (“ Charlemagne's Challenge: The Periodic Latency Problem ”) is a postdoctoral student at the Faculty of Business and Economics at the University of Leuven, Belgium. She obtained her Ph.D. with a thesis entitled “Routing Problems with Profits and Periodicity” at the Katholieke Universiteit Leuven in 2009. Her research interests are in combinatorial optimization and its applications in routing and logistics. Michele Conforti (“ A Geometric Perspective on Lifting ”) is a professor of operations research in the Mathematics Department of the University of Padua. He holds a Ph.D. from Carnegie Mellon University. His research interests are in graph theory, integer programming and combinatorial optimization. He is a recipient of the Fulkerson Prize. Canan G. Corlu (“ Accounting for Parameter Uncertainty in Large-Scale Stochastic Simulations with Correlated Inputs ”) is a Ph.D. candidate in the Tepper School of Business at Carnegie Mellon University. Her research interests include the design of large-scale simulations with applications to inventory management and the applications of operations research techniques to nonprofit organizations. Gérard Cornuéjols (“ A Geometric Perspective on Lifting ”) is IBM Professor of Operations Research at the Tepper School of Business at Carnegie Mellon University. He has a Ph.D. from the School of OR and IE at Cornell University. His research interests are in integer programming and combinatorial optimization. He received the Lanchester Prize, the Fulkerson Prize, and the Dantzig Prize. Maqbool Dada (“ A Periodic-Review Base-Stock Inventory System with Sales Rejection ”) is a professor in operations management at the Johns Hopkins Carey Business School. His research and teaching interests include inventory theory, pricing models, and service operations. He received a Ph.D. in management from Massachusetts Institute of Technology and a B.S. in industrial engineering and operations management from the University of California. Evrim Dalkiran (“ Selecting Optimal Alternatives and Risk Reduction Strategies in Decision Trees ”) is a Ph.D. candidate in the Grado Department of Industrial and Systems Engineering at Virginia Polytechnic Institute and State University. Her research areas include polynomial programming, reformulation-linearization technique (RLT), and global optimization. This paper relates to her interest in decision analysis and mixed-integer programming. Erick Delage (“ A Unified Framework for Dynamic Prediction Market Design ”) graduated from Stanford University with a Ph.D. in electrical engineering under the supervision of Yinyu Ye. His thesis explores tractable methods that account for risks related to parameter and distribution uncertainty in continuous stochastic optimization problems. In June 2009, he joined the Department of Management Sciences at HEC Montréal as an assistant professor. Douglas G. Down (“ Queueing Systems with Synergistic Servers ”) is a professor in the Department of Computing and Software at McMaster University. One of his current interests is how one may exploit flexibility to construct effective scheduling schemes in distributed server systems. The paper in this issue, coauthored with S. Andradóttir and H. Ayhan, is the result of the authors' common interest in developing dynamic

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