Contributors

Abstract

Shipra Agrawal (“ Price of Correlations in Stochastic Optimization ”) graduated from Stanford University with a Ph.D. in computer science under the supervision of Yinyu Ye. Her thesis explores the robustness of assuming statistical independence when solving optimization problems under uncertainty. Her research interests include algorithms, online and stochastic optimization, prediction markets, and algorithmic game theory. Augusto Aguayo (“ Optimizing Long-Term Production Plans in Underground and Open-Pit Copper Mines ”) has a degree in mining engineering from the University of Chile. He is the director of engineering for underground projects at Codelco Andina Division. Frédéric Babonneau (“ Design and Operations of Gas Transmission Networks ”) is a scientific consultant in operations research for the company ORDECSYS. He received a Ph.D. in operations research from the University of Geneva and has made contributions in the optimization of nondifferentiable and large-scale models, in the optimization of transportation problems, and in robust optimization. Ning Cai (“ Pricing Asian Options Under a Hyper-Exponential Jump Diffusion Model ”) is an assistant professor in the Department of Industrial Engineering and Logistics Management at the Hong Kong University of Science and Technology. His research interests include financial engineering and applied probability. He received both M.S. and Ph.D. degrees in operations research in the Department of Industrial Engineering and Operations Research at Columbia University and both B.S. and M.S. degrees in probability and statistics in the School of Mathematical Sciences at Peking University. Raúl Cancino (“ Optimizing Long-Term Production Plans in Underground and Open-Pit Copper Mines ”) has a degree in mining engineering from the University of Chile. He is director of engineering at Codelco North Division. Felipe Caro (“ Optimizing Long-Term Production Plans in Underground and Open-Pit Copper Mines ”) is an assistant professor of decisions, operations, and technology management at the UCLA Anderson School of Management. He is interested in decisions made under uncertainty with a strong emphasis on practical applications. He holds a Ph.D. in operations management from Massachusetts Institute of Technology and earned an industrial engineering degree from the University of Chile. He has ongoing projects with his Chilean colleagues, now mostly in the retail sector. Jaime Catalán (“ Optimizing Long-Term Production Plans in Underground and Open-Pit Copper Mines ”) is a computational engineer educated at the University of Chile with an MBA degree from ESADE, Barcelona. Since 1995, he has been working as an engineer in the design and implementation of several mathematical and computational systems, mainly in projects directed by Rafael Epstein. Hong Chen (“ Asymptotic Optimality of Balanced Routing ”) was Alumni Professor in Supply Chain Management at the Sauder School of Business, the University of British Columbia. He joined Shanghai Institute of Finance, Shanghai Jiaotong University, as a professor in August 2011. His research interests include modeling, optimization, and empirical analysis of manufacturing and service operations and supply chain management. Shaojie Deng (“ Sequential Importance Sampling and Resampling for Dynamic Portfolio Credit Risk ”) is an applied researcher at Microsoft. He obtained his Ph.D. in statistics at Stanford University in 2010. His research interests include rare-event simulation, sequential Monte Carlo, hidden Markov models and particle filters, quantitative finance, risk management, probability theory and stochastic processes, controlled experiment, and data mining on Web data. Yichuan Ding (“ Price of Correlations in Stochastic Optimization ”) is a fourth year Ph.D. candidate in the Department of Mangement Science and Engineering at Stanford University. He holds a B.S. from Zhejiang University and an M.Math from the University of Waterloo. His research is focused on operations research methodology and its application in healthcare management. Xuan Vinh Doan (“ On the Complexity of Non-Overlapping Multivariate Marginal Bounds for Probabilistic Combinatorial Optimization Problems ”) was a postdoctoral fellow in the Combinatorics and Optimization Department of the University of Waterloo, Canada. He joined the Operational Research and Management Sciences Group in Warwick Business School, UK, in September 2011 as an assistant professor. His research interests include optimization under uncertainty and sparse optimization. James S. Dyer (“ A Copulas-Based Approach to Modeling Dependence in Decision Trees ”) holds the Fondren Centennial Chair in Business in the McCombs School of Business at the University of Texas at Austin. He served as chair of the Department of Information, Risk, and Operations Management for nine years (1988–1997). He is the former Chair of the Decision Analysis Society of the Operations Research Society of America (now INFORMS). He received the Frank P. Ramsey Award for outstanding career achievements from the Decision Analysis Society of INFORMS in 2002. He was named a Fellow of INFORMS in 2006 and also received the MCDM Society's Edgeworth-Pareto Award in 2006. His research interests include the valuation of risky investment decisions and risk management. Faramroze G. Engineer (“ A Branch-Price-and-Cut Algorithm for Single-Product Maritime Inventory Routing ”) is a lecturer at the University of Newcastle, Australia. His research interests include the development and application of optimization methods to solve problems in logistics and supply chain management, transportation, network design, and healthcare. He participated in this research project while he was a Ph.D. student in the School of Industrial and Systems Engineering at Georgia Institute of Technology. Rafael Epstein (“ Optimizing Long-Term Production Plans in Underground and Open-Pit Copper Mines ”) is an associate professor at the Industrial Engineering Department of the University of Chile. His research interests include applications of operations research in the areas of forestry, mining, logistics, and combinatorial auctions. He is a former winner of the INFORMS Edelman Award for Achievement in Operations Research and the Management Sciences for work with the forest industries and the IFORS OR for Development Prize for the improvement of the auction of school meals in Chile. Peter I. Frazier (“ The Knowledge Gradient Algorithm for a General Class of Online Learning Problems ”) is an assistant professor in the School of Operations Research and Information Engineering at Cornell University. He received a Ph.D. in operations research and financial engineering from Princeton University in 2009. In 2010 he received the AFOSR Young Investigator Award. His research interest is in the optimal acquisition of information with applications in simulation, medicine, and operations management. Kevin C. Furman (“ A Branch-Price-and-Cut Algorithm for Single-Product Maritime Inventory Routing ”) has led programs and teams related to optimization and logistics research and software application development across multiple ExxonMobil affiliates. He received his Ph.D. in chemical engineering from the University of Illinois at Urbana–Champaign. His nine years at ExxonMobil have been focused on research, development, and leadership in the areas of operations research and process systems engineering. Sergio Gaete (“ Optimizing Long-Term Production Plans in Underground and Open-Pit Copper Mines ”) has a degree in mathematical engineering from the University of Chile. He is director of business plan development at El Teniente, Codelco. Kay Giesecke (“ Sequential Importance Sampling and Resampling for Dynamic Portfolio Credit Risk ”) is assistant professor of management science and engineering at Stanford University. His research interests include stochastic simulation, stochastic modeling, approximation algorithms, stochastic processes, inference and hypothesis testing for stochastic processes and applications in financial engineering, including derivatives pricing and hedging, and risk management. Peter W. Glynn (“ Consistency of Multidimensional Convex Regression ”) is the Thomas Ford Professor of Engineering in the Department of Management Science and Engineering at Stanford University, and also holds a courtesy appointment in the Department of Electrical Engineering. He was Director of Stanford's Institute for Computational and Mathematical Engineering from 2006 until 2010. He is a Fellow of INFORMS, a Fellow of the Institute of Mathematical Statistics, has been cowinner of Best Publication Awards from the INFORMS Simulation Society in 1993 and 2008, was a cowinner of the Best (Biannual) Publication Award from the INFORMS Applied Probability Society in 2009, and was the cowinner of the John von Neumann Theory Prize from INFORMS in 2010. His research interests lie in computational probability, queuing theory, statistical inference for stochastic processes, and stochastic modeling. Marcel Goic (“ Optimizing Long-Term Production Plans in Underground and Open-Pit Copper Mines ”) is an assistant professor at the Industrial Engineering Department of the University of Chile. He received a Ph.D. in industrial administration from the Tepper School of Business, Carnegie Mellon University. His research interests include database marketing, decision support systems, and retail management, with a focus on pricing, assortment, and promotion decisions. Boaz Golany (“ Network Optimization Models for Resource Allocation in Developing Military Countermeasures ”) is the Dean of the Faculty of Industrial Engineering and Management (IE&M) and the holder of the Samuel Gorney Chair in Engineering at the Technion–Israel Institute of Technology. He has a B.Sc. (summa cum laude) in IE&M from the Technion (1982) and a Ph.D. from the McCombs School of Business at the University of Texas at Austin (1985). He has served as an area editor and member of the editorial board for the Journal of Productivity Analysis, IIE Transactions, Omega, and Operations Research. He has published over 80 papers in refereed journals and over 15 book chapters. His publications are in the areas of industrial engineering, operations research, and management science. He has served as a consultant to various companies and agencies in Israel and the U.S. including governmental agencies (in the areas of transportation, education and defense); energy companies (oil, electricity); financial sector (banks); manufacturing (plastics, consumer goods, measurement devices); services (food chains); and information technologies (Internet platforms). Anupam Gupta (“ Approximation Algorithms for VRP with Stochastic Demands ”) is an associate professor in the Computer Science Department at Carnegie Mellon University. He received the B.Tech degree in computer science from Indian Institute of Technology, Kanpur, in 1996, and his Ph.D. in computer science from the University of California, Berkeley, in 2000. He spent two years at Lucent Bell Labs in Murray Hill, New Jersey, before joining Carnegie Mellon University in 2003. His research interests are in the area of theoretical computer science, primarily in developing approximation algorithms for NP-hard optimization problems and understanding the algorithmic properties of metric spaces. He is the recipient of an Alfred P. Sloan Research Fellowship and the NSF CAREER award. Simai He (“ Polymatroid Optimization, Submodularity, and Joint Replenishment Games ”) is an assistant professor at the Department of Management Sciences, City University of Hong Kong. His research interests include optimization, algorithm design and analysis, and game theory. Yuval Heller (“ Sequential Correlated Equilibria in Stopping Games ”) is a Ph.D. candidate in the Department of Statistics and Operations Research at Tel Aviv University. His research interests are in the areas of game theory, microeconomic theory, and decision theory. Steven Kou (“ Pricing Asian Options Under a Hyper-Exponential Jump Diffusion Model ”) is a professor in the Department of Industrial Engineering and Operations Research at Columbia University. Prior to joining Columbia in 1998, he taught at Rutgers University and the University of Michigan. His research interests include financial engineering and applied probability. He was awarded the Erlang Prize by the Applied Probability Society of INFORMS in 2002. Moshe Kress (“ Network Optimization Models for Resource Allocation in Developing Military Countermeasures ”) is professor of operations research at the Naval Postgraduate School (NPS), where he teaches and conducts research in combat modeling and related areas. His current research interests are counterinsurgency modeling, sensor deployment and operations, homeland security problems, and UAV employment in IW situations. His research has been sponsored by DARPA, ONR, USSOCOM, JIEDDO, and TRADOC. He is the Military and Homeland Security Editor of the OR flagship journal Operations Research. He published four books (one of which has been translated into Hebrew and Korean) and over 65 papers in refereed journals. He has been awarded twice the Koopman Prize for military operations research (2005 and 2009) and the 2009 MOR Journal Award. Prior to joining NPS, he was a senior analyst at the Center for Military Analyses in Israel and an adjunct professor at the Technion–Israel Institute of Technology. Tze Leung Lai (“ Sequential Importance Sampling and Resampling for Dynamic Portfolio Credit Risk ”) is professor of statistics at Stanford University. His present research areas include sequential experimentation, adaptive design and control, stochastic optimization, time series analysis and forecasting, change-point detection, hidden Markov models and particle filters, empirical Bayes modeling, multivariate survival analysis, probability theory and stochastic processes, biostatistics, econometrics, quantitative finance, and risk management. His methodological research in these areas has been motivated by and is closely related to his applied interests in engineering, finance, and the biomedical sciences. As director of the Financial Mathematics Program and codirector of the Biostatistics Core at the Stanford Cancer Center, he is involved in several research projects in these fields. Eunji Lim (“ Consistency of Multidimensional Convex Regression ”) is an assistant professor in the Department of Industrial Engineering at the University of Miami. Her research interests include function estimation under shape restrictions, simulation optimization, and stochastic modeling. Johan Marklund (“ Lower Bounds and Heuristics for Supply Chain Stock Allocation ”) is professor of production management at Lund University, Sweden. Previously he held positions at the Leeds School of Business, University of Colorado, Boulder, and the Boston Consulting Group. He holds degrees from Linköping University (M.Sc.) and Lund University (B.Sc. and Ph.D.). His research interests include inventory theory, supply chain management, and logistics, with a special focus on stochastic multiechelon inventory problems. Viswanath Nagarajan (“ Approximation Algorithms for VRP with Stochastic Demands ”) is a research staff member in mathematical sciences at the IBM T. J. Watson Research Center. He received a bachelor's degree in computer science from Indian Institute of Technology, Bombay, and a Ph.D. in algorithms, combinatorics, and optimization from Carnegie Mellon University. His research interests are in combinatorial optimization and approximation algorithms, particularly as applied to vehicle routing, network design, and scheduling. Karthik Natarajan (“ On the Complexity of Nonoverlapping Multivariate Marginal Bounds for Probabilistic Combinatorial Optimization Problems ”) is an associate professor at the Department of Management Sciences, City University of Hong Kong. His primary research interest is in optimization under uncertainty, and this paper forms part of this area of work. George L. Nemhauser (“ A Branch-Price-and-Cut Algorithm for Single-Product Maritime Inventory Routing ”) is an Institute Professor and the Chandler Professor in the School of Industrial and Systems Engineering at Georgia Institute of Technology. His research interests are in integer programming and its applications. His participation in this paper resulted from a research project funded by a large oil company. Yurii Nesterov (“ Design and Operations of Gas Transmission Networks ”) is professor at the Center for Operations Research and Econometrics (CORE), Catholic University of Louvain, Belgium. He is the author of four monographs and more than 70 refereed papers in the leading optimization journals. He is the winner of the triennial Dantzig Prize 2000 awarded by SIAM and the Mathematical Programming Society for research having a major impact on the field of mathematical programming. In 2009 he was awarded the John von Neumann Theory Prize by INFORMS. The main direction of his research is the development of efficient numerical methods for convex and nonconvex optimization problems supported by global complexity analysis. The most important results are obtained for general interior-point methods (theory of self-concordant functions), fast gradient methods (smoothing technique), and global complexity analysis of the second-order schemes (cubic regularization of the Newton's method). Michal Penn (“ Network Optimization Models for Resource Allocation in Developing Military Countermeasures ”) is a professor in the Faculty of Industrial Engineering and Management (IE&M) at the Technion–Israel Institute of Technology. She has a B.A. in mathematics and statistics from the Hebrew University of Jerusalem (1975), and M.Sc. (1982) and Ph.D. (1988) in operations research from IE&M at the Technion. Her interests are in discrete and combinatorial optimization, mainly in scheduling, routing, and algorithmic game theory. Her research was supported by the Israel Ministry of Science, Gordon Center, GIF, TASP, and others. She also serves as the president of the Operations Research Society of Israel (ORSIS). She has published over 40 papers in refereed journals and supervised 25 students towards master’s and doctoral degrees. Warren B. Powell (“ The Knowledge Gradient Algorithm for a General Class of Online Learning Problems ”) is a professor in the Department of Operations Research and Financial Engineering at Princeton University and director of CASTLE Laboratory. He has coauthored over 150 refereed publications in stochastic optimization, stochastic resource allocation, and related applications. He is the author of the book Approximate Dynamic Programming: Solving the Curses of Dimensionality, published by John Wiley & Sons. He is involved in applications in energy, transportation, finance, and homeland security. R. Ravi (“ Approximation Algorithms for VRP with Stochastic Demand ”) is Carnegie Bosch Professor of Operations Research and Computer Science at Carnegie Mellon University. He earned his bachelor's degree from the Indian Institute of Management, Madras, and master's and doctoral degrees from Brown University, all in computer science. He has been at the Tepper School of Business since 1995 where he served as Associate Dean for Intellectual Strategy from 2005–2008. His main research interests are in combinatorial optimization (particularly in approximation algorithms), computational molecular biology, and electronic commerce. He serves on the editorial boards of Management Science and the ACM Transactions on Algorithms. Kaj Rosling (“ Lower Bounds and Heuristics for Supply Chain Stock Allocation ”) is professor of production economics at Linnæus University, Sweden. He holds M.Sc. and Ph.D. degrees from University of California, Berkeley, and Linköping University, Sweden, respectively. His major publications appear in Management Science and Operations Research. He has served as associate editor for Management Science and Manufacturing & Service Operations Management, and he serves presently for Operations Research and Naval Research Logistics. Supply chain management is his primary research interest. Uriel G. Rothblum (“ Network Optimization Models for Resource Allocation in Developing Military Countermeasures ”) is a professor of operations research at the Faculty of Industrial Engineering and Management of the Technion in Haifa, Israel, holding the Alexander Goldberg Chair in Management Science. He earned his bachelor’s and master’s degrees in mathematics at Tel Aviv University (in 1969 and 1971, respectively) and his Ph.D. in the Department of Operations Research at Stanford University (in 1974). His research interests focus on the identification of properties of optimal solutions/policies in a variety of (structured) optimization problems and the insight such result offers in the design of algorithms that solve these problems. He has published over 150 papers in refereed journals and over 20 publications in edited volumes. He joined the Technion in 1984 and served as Dean of the Faculty of Industrial Engineering and Management (1992–1995), Deputy Provost (1998–2000), and Vice President for Academic Affairs (2000–2002). He served as the president of the Operations Research Society of Israel (2006–2008) and was elected an INFORMS Fellow in 2003 (in the first elected cohort). He has served on the editorial boards of Linear Algebra and Its Applications (1982–present), Mathematics of Operations Research (1979–2008), Operations Research (1996–1999), SIAM Journal on Matrix Analysis and Applications (1988–1993), SIAM Journal on Algebraic and Discrete Mathematics (1983–1987), and Letters in Linear Algebra and Its Applications (1980–1981). Since 2009, he has been editor in chief of Mathematics of Operations Research. Ilya O. Ryzhov (“ The Knowledge Gradient Algorithm for a General Class of Online Learning Problems ”) is an assistant professor in the Robert H. Smith School of Business at the University of Maryland. He received a Ph.D. in operations research and financial engineering from Princeton University in 2011. His research seeks to bridge the gap between optimal learning and stochastic optimization by developing efficient decision-making strategies for many broad classes of optimization problems, and incorporating optimal learning concepts into fundamental operations research models such as network problems, linear programs, and Markov decision processes. Amin Saberi (“ Price of Correlations in Stochastic Optimization ”) is an assistant professor at Stanford University. He received his B.Sc. in computer science from Sharif Institute of Technology in 2000 and his Ph.D. in computer science from Georgia Institute of Technology in 2004. His research interests include algorithms, and algorithmic aspects of games, markets, and information networks. Pablo Santibáñez (“ Optimizing Long-Term Production Plans in Underground and Open-Pit Copper Mines ”) is an operations research scientist at the British Columbia Cancer Agency. His work is focused on applications in operations and strategic planning, especially in healthcare. He received his B.S. and industrial engineering degrees from the University of Chile, and his master’s in operations research from the University of British Columbia. The paper in this issue is part of the author's work in the mining sector. Martin W. P. Savelsbergh (“ A Branch-Price-and-Cut Algorithm for Single-Product Maritime Inventory Routing ”) leads the business and services analytics research program at CSIRO Mathematics Informatics and Statistics. His research interests are in discrete optimization and transportation and logistics. He participated in this research project while he was Schneider Professor in the School of Industrial and Systems Engineering at Georgia Institute of Technology before moving to Australia in 2010. Jin-Hwa Song (“ A Branch-Price-and-Cut Algorithm for Single-Product Maritime Inventory Routing ”) received his Ph.D. from the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Institute of Technology. At ExxonMobil, he has worked on various projects related to optimization and decision science, as well as science-build research programs with several universities. John Turner (“ The Planning of Guaranteed Targeted Display Advertising ”) is an assistant professor of operations and decision technologies at the Paul Merage School of Business, University of California at Irvine. His research interests include advertising planning, media management, applied optimization, revenue management, and problems that lie at the interface of operations and marketing. Rodolfo Urrutia (“ Optimizing Long-Term Production Plans in Underground and Open-Pit Copper Mines ”) is an industrial engineer from the University of Chile with a master’s in management and globalization from the same university. As part of his graduate degree, he spent six months at the University of South Wales in Australia. He is a full-time researcher working on operations research models applied to mining problems. Jean-Philippe Vial (“ Design and Operations of Gas Transmission Networks ”) is Emeritus Professor in Operations Research. He has been professor at the Catholic University of Louvain (Belgium), the University Louis Pasteur in Strasbourg (France), and the University of Geneva (Switzerland). He has contributed in optimization methods, logistics, and environmental assessments modeling. He holds a Ph.D. in operations research (Louvain) and a Doctorat d'Etat in Mathematics (Paris). Tianyang Wang (“ A Copulas-Based Approach to Modeling Dependence in Decision Trees ”) is an assistant professor in the Department of Finance and Real Estate at Colorado State University. He earned his Ph.D. from the University of Texas at Austin and is an Associate of the Society of Actuaries. His research is primarily in real options valuation, modeling multivariate uncertainties, enterprise risk management, and quantitative methods in financial risk management. He was finalist in the Decision Analysis Society student paper competition in 2009 and 2010. He has received research funds from the Center for Petroleum Asset Risk Management at the University of Texas at Austin. Andrés Weintraub (“ Optimizing Long-Term Production Plans in Underground and Open-Pit Copper Mines ”) is a professor in the Industrial Engineering Department of the University of Chile. His research interests include operations research in the areas of forestry and mining, logistics, and applied combinatorics. He is a former winner of the INFORMS Edelman Award for Achievement in Operations Research and the Management Sciences for work with forest industries. He served as INFORMS vice president for education and outreach. Heng-Qing Ye (“ Asymptotic Optimality of Balanced Routing ”) is an associate professor in the Department of Logistics and Maritime Studies at the Faculty of Business, the Hong Kong Polytechnic University. His research interests include the modeling and analysis of stochastic network and maritime studies. Yinyu Ye (“ Price of Correlations in Stochastic Optimization ”) is professor of management science and engineering, Stanford University. He holds a Ph.D. in engineering economic systems and operations research from Stanford University. He is the recipient or corecipient of numerous international and national awards, including the 2009 INFORMS John von Neumann Theory Prize for fundamental sustained contributions to theory in operations research and the management sciences. Jiawei Zhang (“ Polymatroid Optimization, Submodularity, and Joint Replenishment Games ”) is an associate professor of operations management at the Stern School of Business, New York University. His research interests include approximation algorithms, deterministic and stochastic optimization, logistics and supply chain management, and production planning and scheduling. Shuzhong Zhang (“ Polymatroid Optimization, Submodularity, and Joint Replenishment Games ”) is a professor in the Industrial and Systems Engineering Program, University of Minnesota. He is on leave from the Department of Systems Engineering & Engineering Management, Chinese University of Hong Kong. His research interests include optimization techniques, approximation algorithms, and risk analysis.