INFORMS Open Forum

STOCHASTIC SYSTEMS ADDS FIVE NEW ASSOCIATE EDITORS

  • 1.  STOCHASTIC SYSTEMS ADDS FIVE NEW ASSOCIATE EDITORS

    Posted 05-19-2021 18:22
    The INFORMS Journal Stochastic Systems has added five new associate editors to the journal.  We encourage you to submit your work to the journal to keep them very busy.  

    Ayalvadi Ganesh is an Associate Professor in the School of Mathematics at the University of Bristol.  His research centers around the mathematical modelling of communication and computer networks, and the design of decentralized algorithms for such networks. He is also an author of the well known book "Big Queues". 

    Karthyek Murthy is an Assistant Professor in the Department of Engineering Systems and Design at Singapore University of Technology and Design. His research centers around building models and methods for navigating the trade-offs between efficiency and competing considerations, such as risk, robustness, and fairness in large-scaled decision problems. 

    Jamol Pender is an Assistant Professor in the School of Operations Research and Information Engineering at Cornell University.  His research centers around understanding how information dissemination affects the underlying dynamics of stochastic service systems.  He is also interested in self-exciting point processes that arise in a variety of applications and will also serve as the Stochastic Systems Publicity Editor. 

    Daniel Russo is an Assistant Professor at Columbia Business School at Columbia University.  His research centers around statistical machine learning and online decision making in the context of reinforcement learning.  His work has laid the foundation for understanding the performance advantages of posterior sampling. 

    Mengdi Wang is an Associate Professor in the Center for Statistics and Machine Learning  and  the Department of Electrical and Computer Engineering at Princeton University.  Her research centers around data-driven stochastic optimization and applications in machine and reinforcement learning.  Her work has provided new complexity benchmarks for solving stochastic dynamic programs and new methods for state aggregation in Markov chains. 

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    Jamol Pender
    Professor
    Cornell University
    Ithaca NY
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