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Dr. David Vengerov

 David Vengerov

Dr. David Vengerov
Consulting Member of Technical Staff
Adaptive Optimization Project
Oracle Labs



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David Vengerov is a researcher at Oracle Labs. He is the Principal Investigator for the Adaptive Optimization project. His research interests include Cloud Computing, Reinforcement Learning and Multi-Agent Systems. His current projects concern application of these techniques to Dynamic Scheduling, Load Balancing, Resource Allocation and Data Migration.

David's publications are available at his personal home page

Education:

* Ph.D. in Management Science and Engineering, Stanford University, 2004.

* M.S. in Engineering Economic Systems and Operations Research, Stanford University, 2000.

* M.S. in Electrical Engineering and Computer Science, MIT, 1998.

* B.S. in Mathematics, MIT, 1997..

Latest Publications

  • Adaptive Optimization of the Sun Java Real-Time System Garbage Collector
    Qian Zhu and David Vengerov, Technical Report, (Sep 10, 2009)
  • Dynamic Adaptation of User Migration Policies in Distributed Virtual Environments
    David Vengerov, Technical Report, (Jul 30, 2009)
  • Modeling, Analysis and Throughput Optimization of a Generational Garbage Collector
    David Vengerov, Technical Report, (Jan 16, 2009)
  • A Gradient-Based Reinforcement Learning Approach to Dynamic Pricing in Partially-Observable Environments
    David Vengerov, Technical Report, (Sep 24, 2007)
  • Adaptive Data-Aware Utility-Based Scheduling in Resource-Constrained Systems
    David Vengerov, Lykomidis Mastroleon, Declan Murphy and Nick Bambos, Technical Report, (Apr 23, 2007)
     See all 

    Latest Patents

  • Adaptive triggering of garbage collection
    (Apr 24, 2012)
  • Method and system for scheduling a thread in a multiprocessor system
    (Oct 4, 2011)
  • Method and apparatus for distributed state-based load balancing between task queues
    (Feb 16, 2010)
  • Facilitating distributed thread migration within an array of computing nodes
    (Feb 16, 2010)
  • Dynamic routing of I/O requests in a multi-tier storage environment
    (Oct 20, 2009)
     See all  


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