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Costis Maglaras

David and Lyn Silfen Professor of Business at Decision, Risk and Operations Division, Columbia Graduate School of Business

About Me

Costis Maglaras is the David and Lyn Silfen Professor of Business at Columbia University, and currently serves as the chair of the Decision, Risk & Operations division of the school. His research lies on the interface of stochastic modeling with operations management, with emphasis on stochastic networks, financial engineering, and quantitative pricing and revenue management. Some of his recent work has focused on: high-frequency market microstructure; the design of portfolio trading systems and algorithms; the interface between social learning and revenue optimization; the economics and control of queueing systems with strategic agents; and the application of quantitative pricing in the residential real-estate market. Professor Maglaras received his BS in Electrical Engineering from Imperial College, London, in 1990, and his MS and PhD in Electrical Engineering from Stanford University in 1991 and 1998, respectively. From 1991 to 1993 he served as a research scientist at Canon Research Center America. He joined Columbia Business School in 1998. His work has been recognized through several research awards, and he has also received the Dean's award at Columbia Business School for teaching excellence for the core course Managerial Statistics. He currently serves as the Department Editor for "Stochastic Models" for the journal of Operations Research. During his sabbatical in 2007, he was involved in starting Mismi Inc., a financial services broker-dealer firm that introduced innovative quantitative portfolio trading tools to the marketplace. He served as Mismi's Head of Research and part of its management team through 2014. He has also been a frequent consultant to industry, primarily in areas of quantitative finance and electronic trading, and in revenue management.

Courses and Programs taught by Costis Maglaras

ColumbiaX

Business Analytics

MicroMasters® Program
4 courses