World's Best Scientists 2026 revealed!
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Computer Science
UK
2025

D-Index & Metrics

Computer Science

D-Index
74
Citations
38093
World Ranking
1450
National Ranking
755

Research.com Recognitions

  • 2025 - Research.com Computer Science in United Kingdom Leader Award
  • 2023 - Research.com Computer Science in United Kingdom Leader Award
  • 2022 - Research.com Computer Science in United Kingdom Leader Award

Overview

Andrew W. Moore is affiliated with Carnegie Mellon University in the United States. Their work spans multiple fields within computer science and engineering, focusing particularly on network technologies and computational systems.

The researcher's recent papers cover a variety of topics and publication venues:

  • Network traffic classification via neural networks, 2022, CL Technical Reports
  • Measuring Network Conditions in Data Centers Using the Precision Time Protocol, 2021, IEEE Transactions on Network and Service Management
  • Thoughts about Artifact Badging, 2020, ACM SIGCOMM Computer Communication Review
  • Fostering the AR illusion: a study of how people interact with a shared artifact in collocated augmented reality, 2024, Frontiers in Virtual Reality
  • Optimisation of energy usage and carbon emissions monitoring using MILP for an advanced anaerobic digester plant, 2022, Energy

Their frequent co-authors include Diana Andreea Popescu, Jifan Yang, Steven Bednarski, Alison Bullock, and Robin Harrap. Collaborative efforts appear mainly in areas related to network measurement, augmented reality, and energy optimization.

Publication venues where they have contributed multiple works are:

  • Frontiers in Virtual Reality
  • IEEE Transactions on Network and Service Management
  • ACM SIGCOMM Computer Communication Review
  • Energy
  • CL Technical Reports

The main fields of study for Andrew W. Moore include:

  • Computer Science
  • Engineering

Within these fields, the scientist's subfields of study are:

  • Electrical and Electronic Engineering
  • Computer Networks and Communications
  • Information Systems
  • Artificial Intelligence
  • Computer Vision and Pattern Recognition

Their research covers several core topics, such as:

  • Software-Defined Networks and 5G
  • Cloud Computing and Resource Management
  • Advanced Optical Network Technologies
  • Augmented Reality Applications
  • Virtual Reality Applications and Impacts
  • Spatial Cognition and Navigation
  • Scientific Computing and Data Management

Best Publications

  • Reinforcement learning: a survey

    Leslie Pack Kaelbling;Michael L. Littman;Andrew W. Moore

  • X-means: Extending K-means with Efficient Estimation of the Number of Clusters

    Dan Pelleg;Andrew W. Moore

  • Locally Weighted Learning

    Christopher G. Atkeson;Andrew W. Moore;Stefan Schaal

  • Proceedings of the 23rd international conference on Machine learning

    William Cohen;Andrew Moore

  • Prioritized Sweeping: Reinforcement Learning with Less Data and Less Time

    Andrew W. Moore;Christopher G. Atkeson

  • Generalization in Reinforcement Learning: Safely Approximating the Value Function

    Justin A. Boyan;Andrew W. Moore

  • Locally weighted learning for control

    Christopher G. Atkeson;Andrew W. Moore;Stefan Schaal

  • Prioritized sweeping: Reinforcement learning with less data and less time

    Unknown

  • An Investigation of Practical Approximate Nearest Neighbor Algorithms

    Ting Liu;Andrew W. Moore;Ke Yang;Alexander G. Gray

  • Accelerating exact k-means algorithms with geometric reasoning

    Dan Pelleg;Andrew Moore

  • Dynamic social network analysis using latent space models

    Purnamrita Sarkar;Andrew W. Moore

  • Efficient memory-based learning for robot control

    Andrew William Moore

  • Variable Resolution Discretization in Optimal Control

    Rémi Munos;Andrew Moore

  • Hoeffding Races: Accelerating Model Selection Search for Classification and Function Approximation

    Oded Maron;Andrew W. Moore

  • The Parti-Game Algorithm for Variable Resolution Reinforcement Learning in Multidimensional State-Spaces

    Andrew W. Moore

  • Efficient algorithms for minimizing cross validation error

    Andrew W. Moore;Mary S. Lee

  • Gradient Descent for General Reinforcement Learning

    Leemon C. Baird;Andrew W. Moore

  • `N-Body' Problems in Statistical Learning

    Alexander G. Gray;Andrew W. Moore

  • Cached sufficient statistics for efficient machine learning with large datasets

    Andrew Moore;Mary Soon Lee

  • The racing algorithm: model selection for lazy learners

    Oden Maron;Andrew W. Moore

  • Algorithms for rapid outbreak detection: a research synthesis

    David L. Buckeridge;Howard Burkom;Murray Campbell;William R. Hogan

Frequent Co-Authors

Jeff Schneider
Jeff Schneider Carnegie Mellon University
Robert C. Nichol
Robert C. Nichol University of Surrey
Alexander G. Gray
Alexander G. Gray Georgia Institute of Technology
Larry Wasserman
Larry Wasserman Carnegie Mellon University
Paul Rayson
Paul Rayson Lancaster University
Weng-Keen Wong
Weng-Keen Wong Oregon State University
Alexander S. Szalay
Alexander S. Szalay Johns Hopkins University
Christopher G. Atkeson
Christopher G. Atkeson Carnegie Mellon University
Gregory F. Cooper
Gregory F. Cooper University of Pittsburgh
Gordon T. Richards
Gordon T. Richards Drexel University

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