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Computer Science

D-Index
31
Citations
6364
World Ranking
13416
National Ranking
5368

Overview

James Ahrens is a researcher affiliated with Los Alamos National Laboratory in the United States, with a primary focus within Computer Science. Their work spans multiple subfields including Computer Networks and Communications, Computer Vision and Pattern Recognition, Information Systems and Management, Artificial Intelligence, and Computer Graphics and Computer-Aided Design.

Their research contributions are particularly associated with topics such as Scientific Computing and Data Management, Advanced Data Storage Technologies, Distributed and Parallel Computing Systems, Data Visualization and Analytics, Computer Graphics and Visualization Techniques, Cell Image Analysis Techniques, and Data Management and Algorithms.

James Ahrens has published extensively in various academic venues, with notable frequent publication outlets including:

  • IEEE Transactions on Visualization and Computer Graphics
  • arXiv (Cornell University)
  • Computing in Science & Engineering
  • The International Journal of High Performance Computing Applications
  • IEEE Computer Graphics and Applications

Several recent papers featuring their contributions are:

  • A terminology for in situ visualization and analysis systems, 2020, The International Journal of High Performance Computing Applications
  • Probabilistic Data-Driven Sampling via Multi-Criteria Importance Analysis, 2020, IEEE Transactions on Visualization and Computer Graphics
  • Assessing K-12 school reopenings under different COVID-19 Spread scenarios - United States, school year 2020/21: A retrospective modeling study, 2022, Epidemics
  • Using an Agent-Based Model to Assess K-12 School Reopenings Under Different COVID-19 Spread Scenarios - United States, School Year 2020/21, 2020, bioRxiv (Cold Spring Harbor Laboratory)
  • An Image-Based Framework for Ocean Feature Detection and Analysis, 2021, Journal of Geovisualization and Spatial Analysis

Their research collaborations include frequent coauthors such as Terece L. Turton, Soumya Dutta, Ayan Biswas, Pascal Grosset, and Miriah Meyer. This indicates a diverse network of colleagues contributing to interdisciplinary aspects of their scientific studies.

Best Publications

  • 36 – ParaView: An End-User Tool for Large-Data Visualization

    James P. Ahrens;Berk Geveci

  • An image-based approach to extreme scale in situ visualization and analysis

    James Ahrens;Sébastien Jourdain;Patrick O'Leary;John Patchett

  • In situ methods, infrastructures, and applications on high performance computing platforms

    A. C. Bauer;H. Abbasi;J. Ahrens;H. Childs

  • Large-scale data visualization using parallel data streaming

    J. Ahrens;K. Brislawn;K. Martin;B. Geveci

  • The cosmic code comparison project

    Katrin Heitmann;Zarija Lukić;Patricia Fasel;Salman Habib

  • Interactive texture-based volume rendering for large data sets

    J. Kniss;P. McCormick;A. McPherson;J. Ahrens

  • Remote large data visualization in the paraview framework

    Andy Cedilnik;Berk Geveci;Kenneth Moreland;James Ahrens

  • A Parallel Approach for Efficiently Visualizing Extremely Large, Time-Varying Datasets

    James Ahrens;Will Schroeder;Michael Papka

  • SLIC: scheduled linear image compositing for parallel volume rendering

    A. Stompel;K.-L. Ma;E.B. Lum;J. Ahrens

  • The Good, the Bad, and the Ugly: A Theoretical Framework for the Assessment of Continuous Colormaps

    Roxana Bujack;Terece L. Turton;Francesca Samsel;Colin Ware

  • The ALPINE In Situ Infrastructure: Ascending from the Ashes of Strawman

    Matthew Larsen;James Ahrens;Utkarsh Ayachit;Eric Brugger

  • Scout: A Hardware-Accelerated System for Quantitatively Driven Visualization and Analysis

    Patrick S. McCormick;Jeff Inman;James P. Ahrens;Charles Hansen

  • Adaptive Extraction and Quantification of Geophysical Vortices

    S. Williams;M. Petersen;P.-T Bremer;M. Hecht

  • In-situ sampling of a large-scale particle simulation for interactive visualization and analysis

    J. Woodring;J. Ahrens;J. Figg;J. Wendelberger

  • PISTON: A Portable Cross-Platform Framework for Data-Parallel Visualization Operators

    Li-Ta Lo;Christopher M. Sewell;James P. Ahrens

  • In Situ Eddy Analysis in a High-Resolution Ocean Climate Model

    Jonathan Woodring;Mark Petersen;Andre Schmeiber;John Patchett

  • Revisiting wavelet compression for large-scale climate data using JPEG 2000 and ensuring data precision

    Jonathan Woodring;Susan Mniszewski;Christopher Brislawn;David DeMarle

  • VisMashup: Streamlining the Creation of Custom Visualization Applications

    E. Santos;L. Lins;J. Ahrens;J. Freire

  • A terminology for in situ visualization and analysis systems

    Hank Childs;Sean Ahern;James P. Ahrens;Andrew C. Bauer

  • Jitter-free co-processing on a prototype exascale storage stack

    John Bent;Sorin Faibish;Jim Ahrens;Gary Grider

  • Data-Intensive Science in the US DOE: Case Studies and Future Challenges

    James P. Ahrens;Bruce Hendrickson;Gabrielle Long;Steve Miller

  • Scout: a data-parallel programming language for graphics processors

    Patrick McCormick;Jeff Inman;James Ahrens;Jamaludin Mohd-Yusof

Frequent Co-Authors

Bernd Hamann
Bernd Hamann University of California, Davis
Hans Hagen
Hans Hagen Technical University of Kaiserslautern
Charles Hansen
Charles Hansen University of Utah
Kwan-Liu Ma
Kwan-Liu Ma University of California, Davis
Han-Wei Shen
Han-Wei Shen The Ohio State University
Colin Ware
Colin Ware University of New Hampshire
Valerio Pascucci
Valerio Pascucci University of Utah
Wu-chun Feng
Wu-chun Feng Virginia Tech
Scott Klasky
Scott Klasky Oak Ridge National Laboratory
Mathew E. Maltrud
Mathew E. Maltrud Los Alamos National Laboratory

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