Hyun-Soo Ahn (“ Dynamic Pricing of Limited Inventories When Customers Negotiate ”) is an associate professor of operations and management science at the Stephen M. Ross School of Business at the University of Michigan. His research interests include analysis of production and service operation systems, supply chain management, and revenue management in retailing and service systems. Daniel W. Apley (“ Efficient Nested Simulation for Estimating the Variance of a Conditional Expectation ”) is an associate professor of industrial engineering and management sciences at Northwestern University. His research interests lie at the interface of engineering and systems modeling, statistical analysis, and data mining. For his work in this area, he received the NSF CAREER award in 2001, the IIE Transactions Best Paper Award in 2003, and the Wilcoxon Prize for best practical application paper appearing in Technometrics in 2008. He currently serves as editor-in-chief for the Journal of Quality Technology and has served as chair of the Quality, Statistics, and Reliability Section of INFORMS, director of the Manufacturing and Design Engineering Program at Northwestern University, and associate editor for Technometrics. Göker Aydin (“ Dynamic Pricing of Limited Inventories When Customers Negotiate ”) is an associate professor of operations and decision technologies at the Kelley School of Business at Indiana University, Bloomington. His research interests include retail operations and supply chain management, with an emphasis on revenue management in retailing and its supply chain implications. Güzin Bayraksan (“ A Sequential Sampling Procedure for Stochastic Programming ”) is an assistant professor of systems and industrial engineering at the University of Arizona. She holds a B.S. degree in industrial engineering from Boğaziçi University and M.S. and Ph.D. degrees in operations research and industrial engineering from the University of Texas at Austin. Her research focuses on stochastic optimization, particularly simulation-based approximations in stochastic programming with applications in scheduling and water resources management. Massimiliano Caramia (“ An Economic Model for Resource Allocation in Grid Computing ”) is associate professor of operations research at the University of Rome “Tor Vergata.” He received his Ph.D. degree in operations research in 2000 from the University of Rome “La Sapienza” and was a researcher at the Istituto per le Applicazioni del Calcolo of the Italian National Research Council, 2001–2006. His main research interests are scheduling, graph theory, optimization, logistics, transportation, and production systems. He has published in journals such as Networks, Operations Research, Discrete Mathematics, Discrete Applied Mathematics, Journal of Heuristics, INFORMS Journal on Computing, SIAM Journal on Optimization, Computers & Operations Research, and Operations Research Letters. Li Chen (“ Tight Bounds for Some Risk Measures, with Applications to Robust Portfolio Selection ”) is a quantitative analyst in Société Générale CIB HK. She received her Ph.D. in operations research/optimization from the Department of Systems Engineering and Engineering Management at the Chinese University of Hong Kong and a bachelor's degree in mathematics from the University of Science and Technology of China. Her research interests are related to risk management and optimization. Arun Chockalingam (“ American Options Under Stochastic Volatility ”) is a visiting assistant professor in the School of Industrial Engineering at Purdue University. He obtained his doctoral degree in industrial engineering from Purdue University in 2008. His research interests lie in solving decision-making problems that arise in financial engineering and health-care systems utilizing stochastic control techniques. Wade D. Cook (“ Multiple Variable Proportionality in Data Envelopment Analysis ”) is the Gordon Charlton Shaw Professor of Management Science in the Schulich School of Business, York University, Toronto, Ontario, Canada, where he serves as department head of management science and as associate dean of research. He holds a doctorate in mathematics and operations research. He has published several books and more than 140 articles in a wide range of academic and professional journals, including Management Science, Operations Research, Journal of the Operational Research Society, European Journal of Operational Research, and IIE Transactions. His areas of specialty include data envelopment analysis and multicriteria decision modeling. He is a former editor of the Journal of Productivity Analysis and INFOR, and he is currently an associate editor of Operations Research. He has consulted widely with various companies and government agencies. Izak Duenyas (“ Purchasing Under Asymmetric Demand and Cost Information: When Is More Private Information Better? ”) is the John Psarouthakis Professor of Manufacturing Management and professor and chair of operations and management science at the Ross School of Business at the University of Michigan. His research interests are in supply chain coordination, capacity investments, and optimal control of production systems. Awi Federguen (“ Procurement Strategies with Unreliable Suppliers ”) is the Charles E. Exley Professor of Management at the Graduate School of Business at Columbia University. He is an expert in the development and implementation of planning models for supply chain management and logistical systems. Stefano Giordani (“ An Economic Model for Resource Allocation in Grid Computing ”) is associate professor of operations research at the University of Rome “Tor Vergata.” He received his Ph.D. degree in operations research in 1999 from the University of Rome “La Sapienza.” His main research interests are scheduling, graph theory, optimization, logistics, transportation, and production systems. He has published in journals such as Networks, Discrete Mathematics, Discrete Applied Mathematics, Journal of Heuristics, Annals of Operations Research, Computational Optimization and Applications, Information Processing Letters, and Computers & Operations Research. Peter W. Glynn (“ A Complementarity Framework for Forward Contracting Under Uncertainty ”) received his Ph.D. in operations research from Stanford University in 1982. He joined the faculty of the University of Wisconsin at Madison, where he held a joint appointment between the Industrial Engineering Department and Mathematics Research Center, and courtesy appointments in computer science and mathematics. In 1987 he returned to Stanford, where he joined the Department of Operations Research. He is the Thomas Ford Professor of Engineering in the Department of Management Science and Engineering and holds a courtesy appointment in the Department of Electrical Engineering. From 1999 to 2005 he served as deputy chair of the Department of Management Science and Engineering, and he was director of Stanford's Institute for Computational and Mathematical Engineering from 2006 until 2010. He is a Fellow of INFORMS and a Fellow of the Institute of Mathematical Statistics. He was a cowinner of Best Publication Awards from the INFORMS Simulation Society in 1993 and 2008, and was a cowinner of the Best (Biannual) Publication Award from the INFORMS Applied Probability Society in 2009. In 2010 he was awarded the John von Neumann Theory Prize by INFORMS. His research interests lie in computational probability, queueing theory, statistical inference for stochastic processes, and stochastic modeling. Joel Goh (“ Robust Optimization Made Easy with ROME ”) is a Ph.D. student in operations, information, and technology at the Stanford Graduate School of Business. He was formerly an instructor of decision sciences at the NUS Business School, National University of Singapore (NUS). Linda V. Green (“ Identifying Good Nursing Levels: A Queuing Approach ”) is the Armand G. Erpf Professor at Columbia Business School. Her research in recent years has focused on the development and application of stochastic models to identify operational policies to improve health-care delivery. Specific applications include emergency room (ER) physician staffing, physician panel sizing, hospital bed capacity planning, scheduling of imaging equipment, nurse staffing, stroke patient management, and burn disaster triage. Current projects include estimating primary physician capacity needs; studying the interrelationship of obstetrics bed capacity, delivery methods, and adverse clinical outcomes; and identifying policies for improving timely physician access in ERs. Pengfei Guo (“ Strategic Behavior and Social Optimization in Markovian Vacation Queues ”) is an assistant professor in the Department of Logistics and Maritime Studies at Hong Kong Polytechnic University. He received his Ph.D. from Duke University in 2007. His research mainly focuses on the design and control of queueing systems with customers' decentralized behavior considered. He is also conducting research on multitier supply chains. Refael Hassin (“ Strategic Behavior and Social Optimization in Markovian Vacation Queues ”) is a professor of operations research at Tel Aviv University. His main research interests are combinatorial optimization and queueing models that involve strategic decisions. Simai He (“ Tight Bounds for Some Risk Measures, with Applications to Robust Portfolio Selection ”) is an assistant professor in the Department of Management Sciences at the City University of Hong Kong. His research interests are related to optimization models, approximation algorithms, and game theory. Woonghee Tim Huh (“ Adaptive Data-Driven Inventory Control with Censored Demand Based on Kaplan-Meier Estimator ” and “ Inventory Systems with a Generalized Cost Model ”) is an assistant professor in the Sauder School of Business at the University of British Columbia. His current research interests include supply chain management, inventory control, and dynamic pricing. He received a B.A. in sociology, B.Math in computer science, and M.Math in combinatorics and optimization from the University of Waterloo. He holds an M.Sc. and a Ph.D. in operations research from Cornell University. He was previously an associate professor in the Department of Industrial Engineering and Operations Research at Columbia University. Gerd Infanger (“ A Complementarity Framework for Forward Contracting Under Uncertainty ”) received his master's degree in electrical engineering and economics at Graz University of Technology in 1983, and his Ph.D. at Vienna University of Technology in energy economics and operations research with honors in 1986. He is CEO of Infanger Investment Technology, LLC, an investment advisor company founded in 1998 that has the goal of managing mutual and hedge funds based on its state-of-the-art mathematical techniques. Infanger Investment Technology also provides risk optimization software based on stochastic optimization, asset allocation, and equity portfolio optimization software. As a consulting professor at Stanford, he teaches and conducts research in stochastic optimization and its applications with a focus in finance. Ganesh Janakiraman (“ Inventory Systems with a Generalized Cost Model ”) is an associate professor of operations management at the School of Management in the University of Texas at Dallas. He obtained his B.Tech degree in mechanical engineering from the Indian Institute of Technology, Madras, and his M.S. and Ph.D. degrees in operations research from Cornell University. His research interests are broadly in the area of supply chain management with a special emphasis on inventory theory. An underlying theme of his research in inventory theory is mathematical analysis that directly or indirectly aids in the development of optimal or near-optimal algorithms to determine inventory levels in supply chains. Roman Kapuściński (“ Managing a Noncooperative Supply Chain with Limited Capacity ”) is an associate professor of operations and management science at the Stephen M. Ross School of Business and the Goff-Smith Co-Director of the Tauber Institute for Global Operations at the University of Michigan. His research interests include capacity management, integration of pricing and production decisions in supply chain settings, and management of innovations. Dimitris Kostamis (“ Purchasing Under Asymmetric Demand and Cost Information: When Is More Private Information Better? ”) is assistant professor of operations, technology, and innovation management at the Kenan-Flagler Business School at the University of North Carolina at Chapel Hill. His research interests include the study of incentives in capacity investment and procurement in supply chains. Chia-Wei Kuo (“ Dynamic Pricing of Limited Inventories When Customers Negotiate ”) is an assistant professor of business administration in the College of Management at National Taiwan University. His research interests include pricing and revenue management, supply chain management, and service and operations systems. Retsef Levi (“ Adaptive Data-Driven Inventory Control with Censored Demand Based on Kaplan-Meier Estimator ”) is an associate professor of management at the Sloan School of Management at the Massachusetts Institute of Technology. He is a member of the Operations Management Group at Sloan and is affiliated with the Operations Research Center and the Computation for Design and Optimization program. His current research is focused on the design and the performance analysis of efficient algorithms for fundamental stochastic and deterministic optimization models arising in the context of supply chain and inventory management, revenue management, logistics, and health-care management. Yuri Levin (“ Network Cargo Capacity Management ”) is an associate professor and Distinguished Faculty Fellow in Operations Management at the School of Business, Queen's University, Kingston, Ontario, Canada. His current research interests include revenue management, dynamic pricing, numerical optimization, and machine learning applications. Tatsiana Levina (“ Network Cargo Capacity Management ”) is an assistant professor at the School of Business, Queen's University in Kingston, Ontario, Canada. Her research focuses on online learning algorithms for portfolio analysis, revenue management, and dynamic pricing. Yunan Liu (“ A Network of Time-Varying Many-Server Fluid Queues with Customer Abandonment ”) is working toward his Ph.D. degree in the Department of Industrial Engineering and Operations Research at Columbia University. He has a master's degree in operations research from Columbia University and a bachelor's degree in electrical engineering from Tsinghua University. His research interests include queueing theory, stochastic modeling, applied probability, and their applications in call centers, health care, inventory management, and energy harvesting. Jeff McGill (“ Network Cargo Capacity Management ”) is a Distinguished Professor of Operations Management at the School of Business, Queen's University in Kingston, Ontario, Canada. He has maintained a research interest in revenue management and related areas for many years with a particular focus on statistical problems and adaptive approaches to optimization in revenue management systems. David P. Morton (“ A Sequential Sampling Procedure for Stochastic Programming ”) received his Ph.D. in operations research from Stanford University. He then joined the Operations Research Department at the Naval Postgraduate School as a National Research Council Postdoctoral Fellow. He is now an Engineering Foundation Professor in the Graduate Program in Operations Research at the University of Texas at Austin. He has research interests in computational stochastic optimization, Monte Carlo approximations for stochastic programs, and interdiction modeling. Alp Muharremoglu (“ Inventory Systems with a Generalized Cost Model ”) is an assistant professor of decision, risk, and operations at the Columbia University Graduate School of Business. He received his Ph.D. in operations research from the Massachusetts Institute of Technology. His research focuses on supply chain management and revenue management. Kumar Muthuraman (“ American Options Under Stochastic Volatility ”) is an associate professor with the McCombs School of Business at the University of Texas at Austin. After obtaining his doctoral degree in 2003 from Stanford University, he worked as an assistant professor of industrial engineering at Purdue University. In 2007, he joined the University of Texas. His research interests include quantitative finance, stochastic control, and health-care operations. Mikhail Nediak (“ Network Cargo Capacity Management ”) is an assistant professor at the School of Business, Queen's University in Kingston, Ontario, Canada. His current research focuses on revenue management and dynamic pricing. James B. Orlin (“ Adaptive Data-Driven Inventory Control with Censored Demand Based on Kaplan-Meier Estimator ”) is the Edward Pennell Brooks Professor of Operations Research in the Sloan School of Management at the Massachusetts Institute of Technology. His research focuses on optimization methods, especially in combinatorial and network optimization. He is a coauthor of Network Flows: Theory, Algorithms, and Applications, for which he was awarded the Lanchester Prize in 1993. He is an INFORMS Fellow. Rodney P. Parker (“ Managing a Noncooperative Supply Chain with Limited Capacity ”) is an assistant professor of operations management at the University of Chicago, Booth School of Business. He received his Ph.D. from the Ross School of Business at the University of Michigan. His research interests include the application of dynamic game theory to operations, inventory theory, and capacity constrained systems. Paat Rusmevichientong (“ Adaptive Data-Driven Inventory Control with Censored Demand Based on Kaplan-Meier Estimator ”) is an associate professor in the School of Operations Research and Information Engineering at Cornell University. His research interests include data mining, information technology, and nonparametric algorithms for stochastic optimization problems, with applications to supply chain and revenue management. Uday V. Shanbhag (“ A Complementarity Framework for Forward Contracting Under Uncertainty ”) has been an assistant professor in industrial and enterprise systems engineering at the University of Illinois at Urbana–Champaign since 2006. He received a Ph.D. from Stanford University's Department of Management Science and Engineering in 2006 and also holds S.M. and B.Tech degrees from the Massachusetts Institute of Technology and IIT, Mumbai, respectively. His research awards include the triennial A. W. Tucker Prize by the Mathematical Programming Society (MPS) in 2006 and the Computational Optimization and Applications (COAP) annual best paper award (jointly with Walter Murray) in 2007. He was also selected as one of 11 finalists for the Microsoft New Faculty Fellowship (2008). More recently, his doctoral students have been recognized for their research through a best paper student prize at the 12th Conference on Stochastic Programming in 2010 (Uma Ravat) and a finalist for the best student paper prize (Huibing Yin) in the American Control Conference, 2010. His interests lie in development of theory and algorithms for optimization and game-theoretic problems, particularly in online, uncertain, and dynamic settings. Anshul Sheopuri (“ Inventory Systems with a Generalized Cost Model ”) is a researcher at the IBM T. J. Watson Research Center. His research is focused on the development of consumable analytics by developing rigorous mathematical techniques for practical problems. A key aspect of his work is the characterization of optimal or near-optimal policies or methods in pricing, financial services, and inventory management. His work has been accepted or published in Operations Research, the European Journal of Operations Research, and Interfaces. He has served as an adjunct assistant professor with New York University's Leonard N. Stern School of Business. He was featured in Fortune CNN as IBM's Face of the Future. He received his Ph.D. in operations management from New York University's Leonard N. Stern School of Business and a B.Tech in mechanical engineering from the Indian Institute of Technology, Madras. Melvyn Sim (“ Robust Optimization Made Easy with ROME ”) is an associate professor of decision sciences at the NUS Business School, National University of Singapore (NUS). He is affiliated with the NUS Risk Management Institute. His research interests fall broadly under the categories of decision making and optimization under uncertainty with applications ranging across finance, supply chain management, and engineered systems. Jeremy Staum (“ Efficient Nested Simulation for Estimating the Variance of a Conditional Expectation ”) is an associate professor of industrial engineering and management sciences and holds the Pentair-Nugent Chair at Northwestern University. His research interests include risk management, simulation in financial engineering, and simulation metamodeling. He serves as department editor for financial engineering at IIE Transactions. Yunpeng Sun (“ Efficient Nested Simulation for Estimating the Variance of a Conditional Expectation ”) is a Ph.D. candidate in industrial engineering and management sciences at Northwestern University. His research interests include credit risk modeling and efficient simulation in risk management and derivatives pricing. Ward Whitt (“ A Network of Time-Varying Many-Server Fluid Queues with Customer Abandonment ”) is a professor in the Department of Industrial Engineering and Operations Research at Columbia University and a long-time member of INFORMS. His paper with Yunan Liu is part of an ongoing research project on stochastic models for service systems. Nan Yang (“ Procurement Strategies with Unreliable Suppliers ”) is assistant professor of operations and manufacturing management at Washington University in St. Louis. She earned a Ph.D. in decision, risk, and operations from Columbia University and taught at the Johnson School of Management at Cornell University. She joined Olin Business School in 2010. Her research addresses a number of fundamental risk factors regarding the supply mechanisms in general supply chains—especially yield uncertainty and lead-time uncertainty. Her research has been published in Management Science and Operations Research. Natalia Yankovic (“ Identifying Good Nursing Levels: A Queuing Approach ”) is assistant professor in the Production, Technology, and Operations Management Department at IESE Business School, University of Navarra, Spain. Her current research is focused on improving health-care delivery efficiency and effectiveness using operations research techniques such as stochastic modeling. Her consulting engagements and case studies developments maintained her connection with the issues faced by health-care providers. Shuzhong Zhang (“ Tight Bounds for Some Risk Measures, with Applications to Robust Portfolio Selection ”) is a full professor in the Department of Systems Engineering and Engineering Management at the Chinese University of Hong Kong. His research interests are related to optimization models, approximation algorithms, and risk analysis. Joe Zhu (“ Multiple Variable Proportionality in Data Envelopment Analysis ”) is professor of operations at the School of Business, Worcester Polytechnic Institute. His research interests include productivity and benchmarking, and applications of data envelopment analysis. He has published over 80 articles in peer-reviewed journals such as Management Science, Operations Research, IIE Transactions, Naval Research Logistics, European Journal of Operational Research, Journal of the Operational Research Society, Annals of Operations Research, Computers & Operations Research, OMEGA, and the Journal of Portfolio Management. He has authored and coauthored several books on performance evaluation and DEA. He serves as an area editor for OMEGA and associate editor for INFOR, and he is a member of the Computers & Operations Research editorial board.
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