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Subject to: Warren Powell

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Manage episode 314865595 series 3000652
Content provided by Anand Subramanian. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Anand Subramanian or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Warren B. Powell is Professor Emeritus at Princeton University, where he taught for 39 years, and is currently the Chief Analytics Officer at Optimal Dynamics. He is the founder and director of CASTLE Labs, which spans contributions to models and algorithms in stochastic optimization, with applications to energy systems, transportation, health, e-commerce, and the laboratory sciences (see www.castlelab.princeton.edu). He has pioneered the use of approximate dynamic programming for high-dimensional applications, and the knowledge gradient for active learning problems. His recent work has focused on developing a unified framework for sequential decision problems under uncertainty, spanning active learning to a wide range of dynamic resource allocation problems. He has authored books on Approximate Dynamic Programming and Optimal Learning, and he has a new book coming up entitled "Reinforcement Learning and Stochastic Optimization: A unified framework for sequential decisions". Dr. Powell is an INFORMS fellow and a recipient of numerous prizes including the prestigious Robert Herman Lifetime Achievement Award in Transportation Science.

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95 episodes

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Manage episode 314865595 series 3000652
Content provided by Anand Subramanian. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Anand Subramanian or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Warren B. Powell is Professor Emeritus at Princeton University, where he taught for 39 years, and is currently the Chief Analytics Officer at Optimal Dynamics. He is the founder and director of CASTLE Labs, which spans contributions to models and algorithms in stochastic optimization, with applications to energy systems, transportation, health, e-commerce, and the laboratory sciences (see www.castlelab.princeton.edu). He has pioneered the use of approximate dynamic programming for high-dimensional applications, and the knowledge gradient for active learning problems. His recent work has focused on developing a unified framework for sequential decision problems under uncertainty, spanning active learning to a wide range of dynamic resource allocation problems. He has authored books on Approximate Dynamic Programming and Optimal Learning, and he has a new book coming up entitled "Reinforcement Learning and Stochastic Optimization: A unified framework for sequential decisions". Dr. Powell is an INFORMS fellow and a recipient of numerous prizes including the prestigious Robert Herman Lifetime Achievement Award in Transportation Science.

  continue reading

95 episodes

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