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David H. Laidlaw

David H. Laidlaw

D-Index & Metrics

Computer Science

D-Index
50
Citations
12096
World Ranking
5549
National Ranking
2535

Research.com Recognitions

  • 2014 - IEEE Fellow For contributions to data visualization and analytics

Overview

David H. Laidlaw is affiliated with Brown University in the United States. Their research intersects the fields of Computer Science and Medicine, with particular emphasis on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Cognitive Neuroscience, Molecular Biology, and Human-Computer Interaction.

The scientist's work covers several main topics, including:

  • Advanced Neuroimaging Techniques and Applications
  • Functional Brain Connectivity Studies
  • Data Visualization and Analytics
  • Advanced MRI Techniques and Applications
  • Visual and Cognitive Learning Processes
  • Multimodal Machine Learning Applications
  • Robotics and Automated Systems

David H. Laidlaw is noted for contributions published in leading venues such as:

  • IEEE Transactions on Visualization and Computer Graphics
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Journal of Morphology
  • Neuroinformatics
  • Microscopy

Frequent collaborators include Johannes Novotny, Ryan P. Cabeen, Arthur W. Toga, Atishay Jain, and Fumeng Yang.

Selected recent publications highlight the scope of the scientist's work:

  • "A Virtual Reality Memory Palace Variant Aids Knowledge Retrieval from Scholarly Articles", 2020, IEEE Transactions on Visualization and Computer Graphics
  • "Virtual and augmented reality: New tools for visualizing, analyzing, and communicating complex morphology", 2021, Journal of Morphology
  • "Tractography Processing with the Sparse Closest Point Transform", 2020, Neuroinformatics
  • "Visualization of 3D Stress Tensor Fields Using Superquadric Glyphs on Displacement Streamlines", 2020, IEEE Transactions on Visualization and Computer Graphics
  • "Evaluating Text Reading Speed in VR Scenes and 3D Particle Visualizations", 2024, IEEE Transactions on Visualization and Computer Graphics

In 2014, David H. Laidlaw was awarded the IEEE Fellow distinction for contributions to data visualization and analytics.

Best Publications

  • The application visualization system: a computational environment for scientific visualization

    C. Upson;T.A. Faulhaber;D. Kamins;D. Laidlaw

  • Immersive VR for scientific visualization: a progress report

    A. van Dam;A.S. Forsberg;D.H. Laidlaw;J.J. LaViola

  • CavePainting: a fully immersive 3D artistic medium and interactive experience

    Daniel F. Keefe;Daniel Acevedo Feliz;Tomer Moscovich;David H. Laidlaw

  • Fluorine-19 MRI for visualization and quantification of cell migration in a diabetes model.

    Mangala Srinivas;Penelope A. Morel;Lauren A. Ernst;David H. Laidlaw

  • Partial-volume Bayesian classification of material mixtures in MR volume data using voxel histograms

    D.H. Laidlaw;K.W. Fleischer;A.H. Barr

  • Visualizing diffusion tensor MR images using streamtubes and streamsurfaces

    Song Zhang;C. Demiralp;D.H. Laidlaw

  • Thoughts on User Studies: Why, How and When

    R Kosara;C G Healey;Interrante;D H Laidlaw

  • Visualizing multivalued data from 2D incompressible flows using concepts from painting

    R. M. Kirby;H. Marmanis;David H. Laidlaw

  • Constructive solid geometry for polyhedral objects

    David H. Laidlaw;W. Benjamin Trumbore;John F. Hughes

  • User Studies: Why, How, and When?

    Robert Kosara;Christopher G. Healey;Victoria Interrante;David H. Laidlaw

  • Quantifying the complexity of bat wing kinematics.

    Daniel K. Riskin;David J. Willis;José Iriarte-Díaz;Tyson L. Hedrick

  • Comparing 2D vector field visualization methods: a user study

    D.H. Laidlaw;R.M. Kirby;C.D. Jackson;J.S. Davidson

  • Cellular texture generation

    Kurt W. Fleischer;David H. Laidlaw;Bena L. Currin;Alan H. Barr

  • Three-dimensional, time-resolved (4D) relative pressure mapping using magnetic resonance imaging.

    J. Michael Tyszka;J. Michael Tyszka;David H. Laidlaw;David H. Laidlaw;Joseph W. Asa;Jeffrey M. Silverman

  • Drawing on Air: Input Techniques for Controlled 3D Line Illustration

    C.C.L. Wang

  • Colorgorical: Creating discriminable and preferable color palettes for information visualization

    Connor C. Gramazio;David H. Laidlaw;Karen B. Schloss

  • Experiments in Immersive Virtual Reality for Scientific Visualization

    Andries van Dam;David H Laidlaw;Rosemary Michelle Simpson

  • CAVE and fishtank virtual-reality displays: a qualitative and quantitative comparison

    C. Demiralp;C.D. Jackson;D.B. Karelitz;S. Zhang

  • Identifying White-Matter Fiber Bundles in DTI Data Using an Automated Proximity-Based Fiber-Clustering Method

    Song Zhang;S. Correia;D.H. Laidlaw

  • Chronic cigarette smoking and the microstructural integrity of white matter in healthy adults: a diffusion tensor imaging study.

    Robert H. Paul;Stuart M. Grieve;Raymond Niaura;Sean P. David

  • Visualizing diffusion tensor images of the mouse spinal cord

    David H. Laidlaw;Eric T. Ahrens;David Kremers;Matthew J. Avalos

Frequent Co-Authors

Joseph J. Crisco
Joseph J. Crisco Brown University
Sharon M. Swartz
Sharon M. Swartz Brown University
George Em Karniadakis
George Em Karniadakis Brown University
Peter R. Schofield
Peter R. Schofield Neuroscience Research Australia
Mark E. Bastin
Mark E. Bastin University of Edinburgh
Daphne Koller
Daphne Koller insitro Inc.
Amy J. Wagers
Amy J. Wagers Harvard University
Christophe Benoist
Christophe Benoist Harvard University
Diane Mathis
Diane Mathis Harvard University

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