Research
Operations research combines the use of optimization, probability and statistics to solve problems in contextual domains such as business, energy systems, health services, financial services, telecommunications and transportation. Active areas of research often work at the intersection of these disciplines, such as the use of optimization in the estimation of large scale statistical models, optimal collection of information, and stochastic optimization.
Faculty Research Interests
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stochastic models and queuing theory, renewals, martingales, Markov processes, stochastic differential equations, dynamic point processes, mass transport by stochastic flows, applications to mathematics of insurance and finance, reliability of complex systems, modelling and estimation of natural hazards
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dynamic resource management, traveler information and decision support, automated vehicle control systems, traveler information systems, personal rapid transit
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stochastic models and queuing theory, performance and pricing models for telecommunications systems, asymptotic analysis and stochastic bounds for queueing networks, theories of queues with time-varying rates, stochastic networks
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financial optimization models and associated algorithms, asset management strategies for global pension plans, (re)insurance companies, and other long-term investors, dynamic portfolio tactics for hedge funds, replicating performance of active managers
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approximate dynamic programming and optimal learning, with applications in energy, homeland security, health and complex resource allocation problems
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convex optimization, interior-point methods, efficient frontiers associated with L¹ risk measures, optimal stopping and related differential equations, high-contrast imaging, celestial mechanics, stability of Saturn's rings, political mapping
© 2011 The Trustees of Princeton University • Department of Operations Research and Financial Engineering • Princeton, NJ 08544