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Timothy Wood

  • Assistant Professor
  • Assistant Professor
  • George Washington University School of Engineering and Applied Science
  • 11PublicationsNumber of items in Timothy's My Publications folder on Mendeley.
  • 1Followers

Recent publications

  • CloudNet : Dynamic Pooling of Cloud Resources by Live WAN Migration of Virtual Machines

    • Wood T
    • Ramakrishnan K
    • Shenoy P
    • et al.
    Get full text
  • ZZ and the art of practical BFT execution

    • Wood T
    • Singh R
    • Venkataramani A
    • et al.
    Get full text

Professional experience

Assistant Professor

School of Engineering and Applied Science, The George Washington University

August 2011 - Present


PhD in Computer Science

University of Massachusetts - Amherst

September 2005 - June 2011(6 years)

BS in Computer & Electrical Engineering

Rutgers - State University of New Jersey at New Brunswick

September 2001 - May 2005(4 years)

Research interests

fault tolerancedata center managementvirtualization


I am a computer science faculty member at The George Washington University. I teach and do research in the general areas of operating systems and distributed systems. I am particularly interested in how new virtualization technologies can provide application agnostic tools that improve performance, efficiency, and reliability in cloud computing data centers. Prior to joining GW I was a Ph.D. student at the University of Massachusetts Amherst working with Prashant Shenoy. Before that I was an ECE undergraduate at Rutgers University and did research with Yanyong Zhang in the WINLAB. I primarily work in the fields of operating systems and networking; my recent work has focused on topics such as: - Cloud Computing: Pooling computing and storage resources from multiple data centers and connecting them back to users - Virtualization: Using the virtualization layer to build application agnostic tools that improve performance and reliability of data center applications - Automation: Building intelligent systems that dynamically manage large server clusters with minimal need for human administrators - Modeling: Designing statistical modeling techniques that characterize application or system behavior to guide decision making processes


Followers (1)