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David I. Ferguson

David I. Ferguson

D-Index & Metrics

Engineering and Technology

D-Index
58
Citations
12712
World Ranking
2485
National Ranking
762

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Electrical engineering

David I. Ferguson focuses on Artificial intelligence, Computer vision, Real-time computing, Object and Automotive engineering. David I. Ferguson mostly deals with Representation in his studies of Artificial intelligence. His Real-time computing research is multidisciplinary, relying on both Tracking, Simulation, Embedded system and IVMS.

His Simulation study combines topics in areas such as Lidar, Light detection and Point cloud. His study in the field of Object type is also linked to topics like Degree of confidence and Mode. As part of the same scientific family, he usually focuses on Automotive engineering, concentrating on Trajectory and intersecting with Data mining.

His most cited work include:

  • System and method for predicting behaviors of detected objects (634 citations)
  • Modifying behavior of autonomous vehicle based on predicted behavior of other vehicles (242 citations)
  • Construction zone object detection using light detection and ranging (212 citations)

What are the main themes of his work throughout his whole career to date?

His main research concerns Computer vision, Artificial intelligence, Object, Simulation and Real-time computing. His work in Computer vision tackles topics such as Brightness which are related to areas like Object detection and Signal. The Field of view and Vision based research David I. Ferguson does as part of his general Artificial intelligence study is frequently linked to other disciplines of science, such as Obstacle and Range, therefore creating a link between diverse domains of science.

His Object course of study focuses on Control and Control engineering. His studies in Simulation integrate themes in fields like Mode, Automotive engineering and State. His study in Real-time computing is interdisciplinary in nature, drawing from both Point cloud, Embedded system and Identification.

He most often published in these fields:

  • Computer vision (48.15%)
  • Artificial intelligence (48.15%)
  • Object (30.86%)

What were the highlights of his more recent work (between 2014-2020)?

  • Computer vision (48.15%)
  • Artificial intelligence (48.15%)
  • Object (30.86%)

In recent papers he was focusing on the following fields of study:

David I. Ferguson mostly deals with Computer vision, Artificial intelligence, Object, Automotive engineering and Real-time computing. His work on Reference image and Image as part of general Computer vision research is often related to Obstacle and Range, thus linking different fields of science. David I. Ferguson has included themes like Signal and Laser in his Artificial intelligence study.

His work on Driving mode is typically connected to School bus as part of general Automotive engineering study, connecting several disciplines of science. His Real-time computing study frequently draws connections between related disciplines such as Simulation. Identification is closely connected to Point cloud in his research, which is encompassed under the umbrella topic of Simulation.

Between 2014 and 2020, his most popular works were:

  • Construction zone object detection using light detection and ranging (212 citations)
  • Controlling a vehicle having inadequate map data (104 citations)
  • Construction Zone Sign Detection (77 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Computer vision
  • Electrical engineering

His primary scientific interests are in Real-time computing, Simulation, Sign detection, Block cipher mode of operation and IVMS. The study incorporates disciplines such as Point cloud, Identification, Object detection and Lidar, Light detection in addition to Simulation. A majority of his Block cipher mode of operation research is a blend of other scientific areas, such as Control engineering, Vehicle tracking system and Remotely operated vehicle.

Best Publications

  • System and method of providing recommendations to users of vehicles

    Christopher Paul Urmson;Dmitri A. Dolgov;Andrew Hughes Chatham;Philip Nemec

  • Planning Long Dynamically Feasible Maneuvers for Autonomous Vehicles

    Maxim Likhachev;Dave Ferguson

  • Using interpolation to improve path planning: The Field D* algorithm

    Dave Ferguson;Anthony Stentz

  • HERB: a home exploring robotic butler

    Siddhartha S. Srinivasa;Dave Ferguson;Casey J. Helfrich;Dmitry Berenson

  • A system for volumetric robotic mapping of abandoned mines

    S. Thrun;D. Hahnel;D. Ferguson;M. Montemerlo

  • Manipulation planning on constraint manifolds

    Dmitry Berenson;Siddhartha S. Srinivasa;Dave Ferguson;James J. Kuffner

  • Replanning with RRTs

    D. Ferguson;N. Kalra;A. Stentz

  • Object recognition and full pose registration from a single image for robotic manipulation

    Alvaro Collet;Dmitry Berenson;Siddhartha S. Srinivasa;Dave Ferguson

  • Field D*: An Interpolation-Based Path Planner and Replanner

    Dave Ferguson;Anthony Stentz

  • Autonomous exploration and mapping of abandoned mines

    S. Thrun;S. Thayer;W. Whittaker;C. Baker

  • Anytime path planning and replanning in dynamic environments

    J. van den Berg;D. Ferguson;J. Kuffner

  • Anytime search in dynamic graphs

    Maxim Likhachev;Dave Ferguson;Geoff Gordon;Anthony Stentz

  • Robotic modeling of voids

    William Lawrence Whittaker;Warren Charles Whittaker;Scott Mason Thayer;Zachary Meyer Omohundro

  • Modifying behavior of autonomous vehicle based on predicted behavior of other vehicles

    David Ian Franklin Ferguson;Dmitri A. Dolgov

  • Construction zone object detection using light detection and ranging

    David Ian Ferguson;Dirk Haehnel;Ian Mahon

  • System and method for predicting behaviors of detected objects through environment representation

    Jiajun Zhu;David I. Ferguson

  • Hoplites: A Market-Based Framework for Planned Tight Coordination in Multirobot Teams

    N. Kalra;D. Ferguson;A. Stentz

  • Manipulation planning with Workspace Goal Regions

    Dmitry Berenson;Siddhartha S. Srinivasa;Dave Ferguson;Alvaro Collet

  • Detection, prediction, and avoidance of dynamic obstacles in urban environments

    D. Ferguson;M. Darms;C. Urmson;S. Kolski

  • State space sampling of feasible motions for high-performance mobile robot navigation in complex environments: Howard et al.: Mobile Robot Navigation in Complex Environments

    Thomas M. Howard;Colin J. Green;Alonzo Kelly;Dave Ferguson

  • System and method for automatically detecting key behaviors by vehicles

    Jiajun Zhu;David Ian Franklin Ferguson;Dmitri A. Dolgov

  • Controlling a vehicle having inadequate map data

    David I. Ferguson;Dmitri A. Dolgov

Frequent Co-Authors

David Silver
David Silver DeepMind (United Kingdom)
Anthony Stentz
Anthony Stentz Carnegie Mellon University
Sebastian Thrun
Sebastian Thrun Stanford University
William Whittaker
William Whittaker Carnegie Mellon University
Wolfram Burgard
Wolfram Burgard University of Technology Nuremberg
Michael Montemerlo
Michael Montemerlo Google (United States)
Clifford Nass
Clifford Nass Stanford University
John M. Dolan
John M. Dolan Carnegie Mellon University
James J. Kuffner
James J. Kuffner Toyota Motor Corporation (United States)

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