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Computer Science
UK
2025

D-Index & Metrics

Computer Science

D-Index
74
Citations
27571
World Ranking
1467
National Ranking
84

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

Paul Newman is affiliated with the University of Oxford in the United Kingdom. Their research spans multiple domains within computer science and engineering, with a notable emphasis on robotics and sensor-based localization.

Their recent publications include the following works:

  • Real-time Kinematic Ground Truth for the Oxford RobotCar Dataset, 2020, published in arXiv (Cornell University)
  • Listening for Sirens: Locating and Classifying Acoustic Alarms in City Scenes, 2022, published in IEEE Transactions on Intelligent Transportation Systems
  • kRadar++: Coarse-to-Fine FMCW Scanning Radar Localisation, 2020, published in Sensors
  • Self-supervised learning for using overhead imagery as maps in outdoor range sensor localization, 2021, published in The International Journal of Robotics Research
  • Fast-MbyM: Leveraging Translational Invariance of the Fourier Transform for Efficient and Accurate Radar Odometry, 2022, published in 2022 International Conference on Robotics and Automation (ICRA)

Frequent co-authors collaborating with Paul Newman include:

  • Matthew Gadd
  • Daniele De Martini
  • Luke Robinson
  • Valentina Muşat
  • Letizia Marchegiani

Paul Newman publishes regularly in several venues, including:

  • arXiv (Cornell University)
  • IEEE Transactions on Intelligent Transportation Systems
  • The International Journal of Robotics Research
  • 2022 International Conference on Robotics and Automation (ICRA)
  • IEEE Robotics and Automation Letters

The primary fields of study associated with Paul Newman's work are:

  • Computer Science
  • Engineering

More specific subfields they contribute to include:

  • Computer Vision and Pattern Recognition
  • Aerospace Engineering
  • Electrical and Electronic Engineering
  • Environmental Engineering
  • Artificial Intelligence

The main research topics addressed by their publications are:

  • Robotics and Sensor-Based Localization
  • Advanced Vision and Imaging
  • Indoor and Outdoor Localization Technologies
  • Advanced Image and Video Retrieval Techniques
  • Remote Sensing and LiDAR Applications
  • 3D Surveying and Cultural Heritage
  • Advanced Neural Network Applications

Best Publications

  • A solution to the simultaneous localization and map building (SLAM) problem

    M.W.M.G. Dissanayake;P. Newman;S. Clark;H.F. Durrant-Whyte

  • FAB-MAP: Probabilistic Localization and Mapping in the Space of Appearance

    Mark Cummins;Paul Newman

  • 1 year, 1000 km: The Oxford RobotCar dataset:

    Will Maddern;Geoffrey Pascoe;Chris Linegar;Paul Newman

  • Visual Place Recognition: A Survey

    Stephanie Lowry;Niko Sunderhauf;Paul Newman;John J. Leonard

  • Robust Mapping and Localization in Indoor Environments Using Sonar Data

    Juan D. Tardós;José Neira;Paul M. Newman;John J. Leonard

  • Appearance-only SLAM at large scale with FAB-MAP 2.0

    Mark Cummins;Paul Newman

  • An Atlas framework for scalable mapping

    M. Bosse;P. Newman;J. Leonard;M. Soika

  • Simultaneous Localization and Map Building in Large-Scale Cyclic Environments Using the Atlas Framework

    Michael Bosse;Paul M. Newman;John J. Leonard;Seth J. Teller

  • Using laser range data for 3D SLAM in outdoor environments

    D.M. Cole;P.M. Newman

  • Outdoor SLAM using visual appearance and laser ranging

    P. Newman;D. Cole;K. Ho

  • The Oxford Radar RobotCar Dataset: A Radar Extension to the Oxford RobotCar Dataset

    Dan Barnes;Matthew Gadd;Paul Murcutt;Paul Newman

  • Highly scalable appearance-only SLAM - FAB-MAP 2.0

    Mark Cummins;Paul Newman

  • The New College Vision and Laser Data Set

    Mike Smith;Ian Baldwin;Winston Churchill;Rohan Paul

  • A comparison of loop closing techniques in monocular SLAM

    Brian Williams;Mark Cummins;José Neira;Paul Newman

  • Cooperative concurrent mapping and localization

    J.W. Fenwick;P.M. Newman;J.J. Leonard

  • SLAM-Loop Closing with Visually Salient Features

    P. Newman;Kin Ho

  • On the Structure and Solution of the Simultaneous Localisation and Map Building Problem

    Paul Michael Newman

  • Detecting Loop Closure with Scene Sequences

    Kin Leong Ho;Paul Newman

  • Experience-based navigation for long-term localisation

    Winston Churchill;Paul Newman

  • Nested Autonomy for Unmanned Marine Vehicles with MOOS-IvP

    Michael R. Benjamin;Henrik Schmidt;Paul M. Newman;John J. Leonard

  • RSLAM: A System for Large-Scale Mapping in Constant-Time Using Stereo

    Christopher Mei;Gabe Sibley;Mark Cummins;Paul Newman

Frequent Co-Authors

Ingmar Posner
Ingmar Posner University of Oxford
Peter Corke
Peter Corke Queensland University of Technology
Ian Reid
Ian Reid University of Adelaide
Hugh Durrant-Whyte
Hugh Durrant-Whyte University of Sydney
Juan D. Tardós
Juan D. Tardós University of Zaragoza
José Neira
José Neira University of Zaragoza
Michael Bosse
Michael Bosse ETH Zurich
Marta Kwiatkowska
Marta Kwiatkowska University of Oxford

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