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Computer Science

D-Index
35
Citations
8860
World Ranking
11461
National Ranking
4707

Overview

Peter Lindstrom is affiliated with the Lawrence Livermore National Laboratory in the United States. Their research primarily focuses on computer science, with significant contributions to subfields including computer networks and communications, artificial intelligence, computational theory and mathematics, computer graphics and computer-aided design, and computer vision and pattern recognition.

The scientist's work encompasses multiple main topics, which include:

  • Advanced Data Storage Technologies
  • Algorithms and Data Compression
  • Computer Graphics and Visualization Techniques
  • Distributed and Parallel Computing Systems
  • Numerical Methods and Algorithms
  • Parallel Computing and Optimization Techniques
  • Advanced Data Compression Techniques

Frequent publication venues for Peter Lindstrom's work are as follows:

  • IEEE Transactions on Visualization and Computer Graphics
  • arXiv (Cornell University)
  • The International Journal of High Performance Computing Applications
  • SIAM Journal on Scientific Computing
  • E3S Web of Conferences

Selected recent papers authored or co-authored by Lindstrom include:

  • "Efficient and Flexible Hierarchical Data Layouts for a Unified Encoding of Scalar Field Precision and Resolution", 2020, IEEE Transactions on Visualization and Computer Graphics
  • "AMM: Adaptive Multilinear Meshes", 2022, IEEE Transactions on Visualization and Computer Graphics
  • "A General Framework for Progressive Data Compression and Retrieval", 2023, IEEE Transactions on Visualization and Computer Graphics
  • "ZFP: A compressed array representation for numerical computations", 2024, The International Journal of High Performance Computing Applications
  • "Progressive Tree-Based Compression of Large-Scale Particle Data", 2023, IEEE Transactions on Visualization and Computer Graphics

Peter Lindstrom frequently collaborates with several co-authors, among them are:

  • Harsh Bhatia
  • Valerio Pascucci
  • Duong Thi Anh Hoang
  • Peer-Timo Bremer
  • Victor A. P. Magri

The body of work represented by Peter Lindstrom reflects a consistent engagement with algorithms and techniques for data compression, hierarchical data layouts, and numerical methods aimed at improving storage and computational efficiency for scientific data. The scientist's contributions have appeared largely in venues dedicated to visualization, high-performance computing, and computational science.

Best Publications

  • Real-time, continuous level of detail rendering of height fields

    Peter Lindstrom;David Koller;William Ribarsky;Larry F. Hodges

  • Fixed-rate compressed floating-point arrays

    Peter Lindstrom

  • Fast and Efficient Compression of Floating-Point Data

    P. Lindstrom;M. Isenburg

  • Fast and memory efficient polygonal simplification

    Peter Lindstrom;Greg Turk

  • Out-of-core simplification of large polygonal models

    Peter Lindstrom

  • Visualization of large terrains made easy

    Peter Lindstrom;Valerio Pascucci

  • Terrain simplification simplified: a general framework for view-dependent out-of-core visualization

    P. Lindstrom;V. Pascucci

  • Image-driven simplification

    Peter Lindstrom;Greg Turk

  • Virtual GIS: a real-time 3D geographic information system

    David Koller;Peter Lindstrom;William Ribarsky;Larry F. Hodges

  • Streaming meshes

    M. Isenburg;P. Lindstrom

  • Evaluation of memoryless simplification

    P. Lindstrom;G. Turk

  • Cache-oblivious mesh layouts

    Sung-Eui Yoon;Peter Lindstrom;Valerio Pascucci;Dinesh Manocha

  • Out-Of-Core Algorithms for Scientific Visualization and Computer Graphics

    Yuh-Min Chiang;Jihad El-sana;Peter Lindstrom;Renato Pajarola

  • Out-of-core compression and decompression of large n-dimensional scalar fields

    Lorenzo Ibarria;Peter Lindstrom;Jaroslaw R. Rossignac;Andrzej Szymczak

  • Large mesh simplification using processing sequences

    M. Isenburg;P. Lindstrom;S. Gumhold;J. Snoeyink

  • A memory insensitive technique for large model simplification

    Peter Lindstrom;Cláudio T. Silva

  • TTHRESH: Tensor Compression for Multidimensional Visual Data

    Rafael Ballester-Ripoll;Peter Lindstrom;Renato Pajarola

  • Out-of-core construction and visualization of multiresolution surfaces

    Peter Lindstrom

  • Lossless compression of predicted floating-point geometry

    Martin Isenburg;Peter Lindstrom;Jack Snoeyink

  • Interactive view-dependent rendering of large isosurfaces

    Benjamin Gregorski;Mark Duchaineau;Peter Lindstrom;Valerio Pascucci

  • Image-driven simplification

    Peter Lindstrom;Greg Turk

Frequent Co-Authors

Valerio Pascucci
Valerio Pascucci University of Utah
Cláudio T. Silva
Cláudio T. Silva New York University
Bernd Hamann
Bernd Hamann University of California, Davis
Kenneth I. Joy
Kenneth I. Joy University of California, Davis
Charles Hansen
Charles Hansen University of Utah
Jarek Rossignac
Jarek Rossignac Georgia Institute of Technology
Peer-Timo Bremer
Peer-Timo Bremer Lawrence Livermore National Laboratory
Greg Turk
Greg Turk Georgia Institute of Technology
Jack Snoeyink
Jack Snoeyink University of North Carolina at Chapel Hill
Steven G. Parker
Steven G. Parker Nvidia (United States)

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