Publication List

James Ahrens

Peer-reviewed publications for James Ahrens (Google Scholar, May 23, 2024)

    140 peer-reviewed publications

    h-index of 39, 8569 citations

Google Scholar results for paraview.org

    h-index of 80, 34989 citations 

    This metric documents citations in scientific publications to the website paraview.org. For comparison, the top cited    

    ParaView manuscript publication is Chapter 36, of the Visualization Handbook, by Ahrens, Geveci, Law, and is cited 2528   

    times. The 34989 website citations capture the much broader impact of ParaView for the scientific community.

Book Chapters and Journal Articles

52.) Wang, Daoce, Jesus Pulido, Pascal Grosset, Sian Jin, Jiannan Tian, Kai Zhao, James Ahrens, and Dingwen Tao. "TAC+: Optimizing Error-Bounded Lossy Compression for 3D AMR Simulations." IEEE Transactions on Parallel and Distributed Systems (2023).

51.) H. Rostyslav, J. Zhao, D. Perez, J. Ahrens, and R. Maciejewski. "MolSieve: A Progressive Visual Analytics System for Molecular Dynamics Simulations." IEEE Transactions on Visualization and Computer Graphics, 2023.

50.) T. Germann, M. Smith, L. Dauelsberg, G. Fairchild, T. Turton, M. Gorris, C. Ross, J. Ahrens, D. Hemphill, C. Manore, and S. Del Valle, "Assessing K-12 school reopenings under different COVID-19 Spread scenarios–United States, school year 2020/21: A retrospective modeling study." Epidemics, 41, 2022.

49.) S. Dutta, T. Turton, D. Rogers, J. Musser, J. Ahrens, and A. Almgren. "In situ feature analysis for large-scale multiphase flow simulations." Journal of Computational Science, 63, 2022.

48.) J. Ahrens, "Technology trends and challenges for large-scale scientific visualization." IEEE Computer Graphics and Applications 42, no. 4, pp. 114-119, 2022.

47.) A. Biswas, S. Dutta, T. Turton, and J. Ahrens. "Sampling for scientific data analysis and reduction." In In Situ Visualization for Computational Science, pp. 11-36. Cham: Springer International Publishing, 2022.

46.) G. Abram, P. Navrátil, D. Rogers, and J. Ahrens. "Distributed Multi-tenant In Situ Analysis Using Galaxy." In In Situ Visualization for Computational Science, pp. 421-438. Cham: Springer International Publishing, 2022.

45.) D. Rogers, S. Dutta, D. Banesh, T. Turton, E. Stam, and J. Ahrens. "In Situ Solutions with CinemaScience." In In Situ Visualization for Computational Science, pp. 307-328. Cham: Springer International Publishing, 2022.

44.) D. Banesh, M. Petersen, J. Ahrens, T. Turton, F. Samsel, J. Schoonover, and B. Hamann. "An image-based framework for ocean feature detection and analysis." Journal of Geovisualization and Spatial Analysis 5 (2021): 1-21.

43.) D. Francom, D. Walters, J. Barber, D. Luscher, E. Lawrence, A. Biswas, C. Biwer, D. Banesh, J. Lazarz, S. Vogel, K. Ramos, C. Bolme, R. Sandberg, J. Ahrens, "Simulation and emulation of X-ray diffraction from dynamic compression experiments." Journal of Dynamic Behavior of Materials 7 (2021): 170-187.

42.) H. Carr, O. Rübel, G. Weber, and J. Ahrens. "Optimization and augmentation for data parallel contour trees." IEEE transactions on visualization and computer graphics 28, no. 10 (2021): 3471-3485.

41.) S. Dutta, T. Turton, J. Ahrens, "A Confidence-Guided Technique for Tracking Time-Varying Features", Computing in Science & Engineering, 2020.

40.) A. Biswas , S. Dutta, E. Lawrence, J. Patchett, J. Calhoun, J. Ahrens, "Probabilistic Data-Driven Sampling via Multi-Criteria Importance Analysis", IEEE Transactions on Visualization and Computer Graphics, 2020. 

39.) A. Biswas, J. Ahrens, S. Dutta, J. Musser, A. Almgren, T. Turton,"Feature Analysis, Tracking, and Data Reduction: An Application to Multiphase Reactor Simulation MFiX-Exa for In-Situ Use Case", Computing in Science & Engineering, 2020.

38.) D. Francom, D.J. Walters, J.L. Barber, D.J. Luscher, E. Lawrence, A. Biswas, C.M. Biwer, D. Banesh, J. Lazarz, S.C. Vogel, K. Ramos, C. Bolme, R. Sandberg, J. Ahrens, “Simulation and Emulation of X-Ray Diffraction from Dynamic Compression Experiments”, Journal of Dynamic Behavior of Materials, Springer International Publishing, 1-18, 2020.

37.) H. Childs, S.D. Ahern, J. Ahrens, A.C. Bauer, J. Bennett, E.W. Bethel, P. Bremer, E. Brugger, J. Cottam, M. Dorier, and others, “A terminology for in situ visualization and analysis systems”, The International Journal of High Performance Computing Applications, 2020.

36.) D. Orban, D. Banesh, C. Tauxe, C. M. Biwer, A. Biswas, R. Saavedra, C. Sweeney, R. L. Sandberg, C. A. Bolme, J. Ahrens and D. Rogers, "Cinema:Bandit: a visualization application for beamline science demonstrated on XFEL shock physics experiments", Journal of Synchrotron Radiation, 27 (1), 2020.

35.) H. Carr, G. H. Weber, C. Sewell, O. Rübel, P. Fasel and J. Ahrens, "Scalable Contour Tree Computation by Data Parallel Peak Pruning," IEEE Transactions on Visualization and Computer Graphics, 2019.

34.) D. Banesh, M. Petersen, J. Wendelberger, J. Ahrens, B. Hamann, "Comparison of piecewise linear change point detection with traditional analytical methods for ocean and climate data", Environmental Earth Sciences, 78 (21) 623, 2019.

33.) S. Dutta, A. Biswas, J. Ahrens, "Multivariate Pointwise Information-Driven Data Sampling and Visualization", Entropy, 21 (7), 699, 2019

32.) G. Aldrich, J. Lukasczyk, J. Hyman, G. Srinivasan, H. Viswanathan, C. Garth, H. Leitte, J. Ahrens, B. Hamann, "A Query-based Framework for Searching, Sorting, and Exploring Data Ensembles", Computing in Science & Engineering, 2019.

31.) D. Orban, D. Keefe, A. Biswas, J. Ahrens, D. Rogers, “Drag and Track: A Direct Manipulation Interface for Contextualizing Data Instances within a Continuous Parameter Space”, IEEE Transactions on Visualization and Computer Graphics, 25 (1), 256-266, 2019.

30.) D. Walters, A Biswas, E Lawrence, D. Francom, D. Luscher, D. Fredenburg, K. Moran, C. Sweeney, R. Sandberg, J. Ahrens, C. Bolme, “Bayesian calibration of strength parameters using hydrocode simulations of symmetric impact shock experiments of Al-5083”, Journal of Applied Physics 124 (20), 2018.

29.) A.Biswas, C. Biwer, D. Walters, J. Ahrens, D. Francom, E. Lawrence, R. Sandberg, D. Fredenburg, C. Bolme, “An Interactive Exploration Tool for High-Dimensional Datasets: A Shock Physics Case Study”, Computing in Science & Engineering, 2018.

28.) J. Pulido, D. Livescu, K. Kanov, R. Burns, C. Canada, J. Ahrens, B. Hamann, “Remote visual analysis of large turbulence databases at multiple scales”, Journal of Parallel and Distributed Computing 120, 115-126, 2018.

27.) S. Vogel, C. Biwer, D. Rogers, J. Ahrens, R. Hackenberg, D. Onken, J. Zhang, “Interactive visualization of multi-data-set Rietveld analyses using Cinema: Debye-Scherrer”, Journal of applied crystallography 51 (3), 2018.

26.) J Patchett, J Ahrens, “Optimizing scientist time through in situ visualization and analysis”, IEEE computer graphics and applications 38 (1), 119-127, 2018.

25.) R. Bujack, T. Turton, F. Samsel, C. Ware, D. Rogers, J. Ahrens, “The good, the bad, and the ugly: A theoretical framework for the assessment of continuous colormaps”, IEEE transactions on visualization and computer graphics 24 (1), 923-933, 2018.

24.) P. O’Leary, J. Ahrens, S. Jourdain, S. Wittenburg, D. Rogers, M. Petersen, "Cinema image-based in situ analysis and visualization of MPAS-ocean simulations", Parallel Computing 55, pgs. 43-48, 2016.

23.) A. Bauer, H. Abbasi, J. Ahrens, et al, "In situ methods, infrastructures, and applications on high performance computing platforms", Computer Graphics Forum 35 (3), pgs. 577-597, 2016.

22.) K. Myers, E. Lawrence, M. Fugate, C. Bowen, L. Ticknor, J. Woodring, J. Wendelberger, J. Ahrens, "Partitioning a Large Simulation as It Runs", Technometrics, 58, 3, pgs. 329–340, 2016.

21.) J. Pulido, D. Livescu, J. Woodring, J. Ahrens, B. Hamann, "Survey and analysis of multiresolution methods for turbulence data", Computers & Fluids 125, pgs. 39-58, 2016.

20.) J. Ahrens, “Increasing Scientific Data Insights about Exascale Class Simulations under Power and Storage Constraints”, IEEE Computer Graphics and Applications, March/April 2015.

19.) J. Woodring, M. Petersen, A. Schmeier, J. Patchett, J. Ahrens, H. Hagen, “In Situ Eddy Analysis in a High- Resolution Ocean Climate Model”, IEEE Transactions on Visualization and Computer Graphics & IEEE Visualization Conference, Chicago, Illinois, October 2015.

18.) Y. Su, G. Agrawal, J. Woodring, K. Myers, J. Wendelberger, J. Ahrens, "Effective and efficient data sampling using bitmap indices", Cluster Computing (2014).

17.) S. Williams, M. Petersen, M. Hecht, M. Maltrud, J. Patchett, J. Ahrens, B. Hamann, "Interface Exchange as an Indicator for Eddy Heat Transport", Computer Graphics Forum 31(3): 1125-1134 (2012).

16.) S. Williams, M. Hecht, M. Petersen, R. Strelitz, M. Maltrud, J. Ahrens, M. Hlawitschka, B. Hamann, "Visualization and Analysis of Eddies in a Global Ocean Simulation", Computer Graphics Forum 30(3): 991-1000 (2011).

15.) J. Woodring, J. Ahrens, J. Figg, J. Wendelberger, S. Habib, K. Heitmann, "In-situ Sampling of a Large- Scale Particle Simulation for Interactive Visualization and Analysis", Computer Graphics Forum 30(3): 1151-1160 (2011).

14.) S. Williams, M. Petersen, P.T. Bremer, M. Hecht, V. Pascucci, J. Ahrens, M. Hlawitschka, B. Hamann, "Adaptive Extraction and Quantification of Geophysical Vortices", IEEE Transactions on Visualization and Computer Graphics 17(12): 2088-2095 (2011)

13.) J. Ahrens, B. Hendrickson, G. Long, S. Miller, R. Ross, D. Williams: Data-Intensive Science in the US DOE: Case Studies and Future Challenges. Computing in Science & Engineering, 13, 14-24 (2011)

12.) J. Ahrens, K. Heitmann, M. Petersen, J. Woodring, S. Williams, P. Fasel, C. Ahrens, C.H. Hsu, B. Geveci, "Verifying Scientific Simulations via Comparative and Quantitative Visualization". IEEE Computer Graphics and Applications 30(6): 16- 28 (2010).

11.) E. Santos, L. Lins. J. Ahrens, J. Freire, C. Silva, "VISMASHUP: Streamlining the Creation of Custom Visualization Applications", IEEE Transactions on Visualization and Computer Graphics, Volume 15, Issue 6, pp. 1539-46, November-December 2009.

10.) S. Habib, A. Pope, Z. Lukic, D. Daniel, P. Fasel, N. Desai, K. Heitmann, C. Hsu, L. Ankeny, G. Mark, S. Bhattacharya, J. Ahrens, "Hybrid petacomputing meets cosmology: the Roadrunner Universe project”, Journal of Physics: Conference Series - Scientific Discovery Through Advanced Computing, Volume 180, 2009.

9.) M. Graf, J. Ahrens, J. Patchett, H. Dahal, A. Balatsky, D. Modl, L. Monroe, N. Brown, E. Akhadov, “Integrated Nanotechnologies: To See is to Know: Visualization”, SciDAC Review, Issue 10, Winter 2008.

8.) E. Anderson, J. Ahrens, K. Heitmann, S. Habib, C. SIlva, "Provenance in Comparative Analysis: A Study in Cosmology", Computing in Science and Engineering, Volume 10, Issue 3, pgs. 30-37, May-June 2008.

7.) K. Heitmann, Z. Lukic, P. Fasel, S. Habib, M. Warren, M. White, J. Ahrens, L. Ankeny, R. Armstrong, B. O'Shea, P.M. Ricker, V. Springel, J. Stadel, and H. Trac, "The Cosmic Code Comparison Project", Computational Science and Discovery, Volume 1, Issue 1, 2008.

6.) P. McCormick, J. Inman, J. Ahrens, J. Mohd-Yusof, G. Roth, S. Cummings, "Scout: A Data Parallel Programming Environment for Graphics Processors", Parallel Computing, 33(10-11), pgs. 648- 662, 2007.

5.) J. Ahrens, K. Heitmann, S. Habib, L. Ankeny, P. McCormick, J. Inman, R. Armstrong and K.L. Ma, "Quantitative and comparative visualization applied to cosmological simulations", Journal of Physics: Conference Series - Scientific Discovery Through Advanced Computing, Volume 46, 2006.

4. ) J. Ahrens, B. Geveci, C. Law, "ParaView: An End User Tool for Large Data Visualization", Visualization Handbook, Academic Press, 2005.

3.) P. McCormick, J. Ahrens, "Large Data Visualization and Rendering: A Problem Driven Approach", Visualization Handbook, Academic Press, 2005.

2.) J. Ahrens, K. Brislawn, K. Martin, B. Geveci, C. Law, M. Papka, "Large Scale Data Visualization Using Parallel Data Streaming", IEEE Computer Graphics and Applications, July-August 2001.

1.) J. Kniss, P. McCormick, A. McPherson, J. Ahrens, J. Painter, A. Keahey, C. Hansen, "TRex: Interactive Texture Based Volume Rendering for Extremely Large Datasets", IEEE Computer Graphics and Applications, July-August 2001.

Conference and Workshop Publications

88.) D. Wang, J. Pulido, P. Grosset, J. Tian, J. Ahrens, and D. Tao. "Analyzing impact of data reduction techniques on visualization for AMR applications using AMREX framework." In 2023 IEEE/ACM 9th International Workshop on Data Analysis and Reduction for Big Scientific Data (DRBSD), pp. 263-271. 2023.

87.) D. Wang, J. Pulido, P. Grosset, J. Tian, S. Jin, H. Tang, J. Sexton, S. Di, K. Zhao, b. Fang, Z. Lukic, F. Cappello, J Ahrens, D. Tao. "Amric: A novel in situ lossy compression framework for efficient I/O in adaptive mesh refinement applications." In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, pp. 1-15. 2023.

86.) M. Booher, J. Ahrens, and A. Biswas. "Explainable machine learning approaches for understanding fire outcomes." In Applications of Machine Learning 2023, vol. 12675, pp. 258-262. SPIE, 2023.

85.) Q. Wofford, J. Hurd, H. Greenberg, P. Bridges, and J. Ahrens. "Complete Provenance for Application Experiments with Containers and Hardware Interface Metadata." In 2022 IEEE/ACM 4th International Workshop on Containers and New Orchestration Paradigms for Isolated Environments in HPC (CANOPIE-HPC), pp. 12-24. IEEE, 2022.

84.) J. Wang, P. Grosset, T. Turton, and J. Ahrens. "Analyzing the Impact of Lossy Data Reduction on Volume Rendering of Cosmology Data." In 2022 IEEE/ACM 8th International Workshop on Data Analysis and Reduction for Big Scientific Data (DRBSD), pp. 11-20. IEEE, 2022.

83.) D. Wang, J. Pulido, P. Grosset, S. Jin, J. Tian, J. Ahrens, and D. Tao. "TAC: Optimizing error-bounded lossy compression for three-dimensional adaptive mesh refinement simulations." In Proceedings of the 31st International Symposium on High-Performance Parallel and Distributed Computing, pp. 135-147. 2022.

82.) S. Dutta, D. Lipsa, T. Turton, B. Geveci, and J. Ahrens. "In Situ Analysis and Visualization of Extreme-Scale Particle Simulations." In International Conference on High Performance Computing, pp. 283-294. Cham: Springer International Publishing, 2022.

81.) Dutta, Soumya, Humayra Tasnim, Terece L. Turton, and James Ahrens. "In Situ Adaptive Spatio-Temporal Data Summarization." In 2021 IEEE International Conference on Big Data (Big Data), pp. 315-321. IEEE, 2021.

80.) P. Grosset, and J. Ahrens. "Lightweight interface for in situ analysis and visualization of particle data." In ISAV'21: In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization, pp. 12-17. 2021.

79.) S. Jin, J. Pulido, P. Grosset, J. Tian, D. Tao, and J. Ahrens. "Adaptive configuration of in situ lossy compression for cosmology simulations via fine-grained rate-quality modeling." In Proceedings of the 30th International Symposium on High-Performance Parallel and Distributed Computing, pp. 45-56. 2021.

78.) J. Pulido, J. Patchett, M. Bhattarai, B. Alexandrov, and J. Ahrens. "Selection of Optimal Salient Time Steps by Non-negative Tucker Tensor Decomposition." In EuroVis (Short Papers), pp. 55-59. 2021.

77.) N. Marshak, P. Grosset, A. Knoll, J. Ahrens, and C. Johnson. "Evaluation of PyTorch as a Data-Parallel Programming API for GPU Volume Rendering." In EGPGV@ EuroVis, pp. 31-35. 2021.

76.) P. Grosset, J. Pulido, J. Ahrens, "Personalized In Situ Steering for Analysis and Visualization", ISAV'20 In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization, 2020.

75.) S. Sjue, J. Ahrens, Ayan Biswas, Devin Francom, E. Lawrence, D. Luscher, D.Walters, "Fast Strength Model Charecterization using Bayesian Statistics", AIP Conference Proceedings, Volume 2272, Issue 1, 2020. 

74.) P. Grosset, C. Biwer, J. Pulido, A. Mohan, A. Biswas, J. Patchett, T. Turton, D. Rogers, D. Livescu, J. Ahrens, "Foresight: Analysis That Matters for Data Reduction", Supercomputing 2020.

73.) P. Hristov, G. Weber, H. Carr, O. Rübel, J. Ahrens, "Data Parallel Hypersweeps for In Situ Topological Analysis", 2020 IEEE 10th Symposium on Large Data Analysis and Visualization (LDAV), 12-21, 2020.

72.) J. Lukasczyk, C. Garth, M. Larsen, W. Engelke, I. Hotz, D. Rogers, J. Ahrens, R. Maciejewski, "Cinema Darkroom: A Deferred Rendering Framework for Large-Scale Datasets", 2020 IEEE 10th Symposium on Large Data Analysis and Visualization (LDAV), 37-41, 2020.

71.) [Best Paper Award] K. C. Tsai, R. Bujack, B. Geveci, U. Ayachit, J. Ahrens, “Approaches for In Situ Computation of Moments in a Data-Parallel Environment”, EuroGraphics Symposium on Parallel Graphics and Visualization, 2020.

70.) G. Abram, V. Adhinarayanan, W. Feng, D. Rogers, J. Ahrens, “ETH: An Architecture for Exploring the Design Space of In-situ Scientific Visualization", 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS), 515-526, 2020.

69.) S. Jin, P. Grosset, C. Biwer, J. Pulido, J. Tian, D. Tao, J. Ahrens, “Understanding GPU-Based Lossy Compression for Extreme-Scale Cosmological Simulations,” 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2020.

68.) C. Bolme, D. Orban, D. Banesh, C. Tauxe, C. Biwer, A. Biswas, R. Saavedra, C. Sweeney, R. Sandberg, J. Ahrens, and D. Rogers, “Workflow and visual analysis for XFEL shock physics experiments using Cinema: Bandit”, 21st Biennial Conference of the APS Topical Group on Shock Compression of Condensed Matter, Bulletin of the American Physical Society, Volume 64, Number 8, 2019.

67.) A. Biswas, D. Walters, D. Francom, E. Lawrence, D. Luscher, S. Sjue, J. Ahrens, “Fast Strength Model Parameter Optimization and Model Comparison Using Bayesian Statistics”, 21st Biennial Conference of the APS Topical Group on Shock Compression of Condensed Matter, Bulletin of the American Physical Society, Volume 64, Number 8, 2019.

66.) J. Pulido, Z. Lukic, P. Thorman, C. Zheng, J. Ahrens, B. Hamann, "Data Reduction Using Lossy Compression for Cosmology and Astrophysics Workflows", Journal of Physics: Conference Series, 1290, 1, 012008, 2019.

65.) J. Chen, Q. Guan, X. Liang, P. Bryant, P. Grubel, A. McPherson, L. Lo, T. Randles, Z. Chen, J. Ahrens, “Build and Execution Environment (BEE): an Encapsulated Environment Enabling HPC Applications Running Everywhere”, 2018 IEEE International Conference on Big Data (Big Data), 1737-1746, 2018.

64.) X. Chen, Q. Guan, L. Lo, S. Su, Z. Ren, J. Ahrens, T. Estrada, “In situ TensorView: In situ Visualization of Convolutional Neural Networks”, 2018 IEEE International Conference on Big Data (Big Data), 1899-1904, 2018.

63.) [Best Paper Award] J.Lukasczyk, E. Kinner, J. Ahrens, H. Leitte, and C. Garth, "VOIDGA: A View-Approximation Oriented Image Database Generation Approach , IEEE 8th Symposium on Large Data Analysis and Visualization (LDAV), 2018.

62.) A. Biswas, S. Dutta, J. Pulido, J. Ahrens, “In situ data-driven adaptive sampling for large-scale simulation data summarization”, Proceedings of the Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization 2018.

61.) J. Chen, Q. Guan, Z. Zhang, X. Liang, L. Vernon, A. McPherson, L. Lo, p. Grubel, T. Randles. Z. Chen, J. Ahrens, “BeeFlow: A Workflow Management System for In Situ Processing across HPC and Cloud Systems”, 2018 IEEE 38th International Conference on Distributed Computing Systems, 1029 - 1038, 2018.

60.) C. Gillmann, T. Wischgoll, B. Hamann, J. Ahrens, “Modeling and Visualization of Uncertainty-Aware Geometry Using Multi-variate Normal Distributions”, 2018 IEEE Pacific Visualization Symposium (PacificVis), 106-110, 2018.

59.) D. Banesh, J. Wendelberger, M. Petersen, J. Ahrens, and B. Hamann. “Change Point Detection for Ocean Eddy Analysis” In Workshop on Visualization in Environmental Sciences (EnvirVis), K. Rink, D. Zeckzer, R. Bujack, and S. Jnicke (Eds.). The Eurographics Association. 2018.

58.) X. Chen, Q. Guan, X. Liang, L. Lo, S. Su, T. Estrada, J. Ahrens, "Tensorview: visualizing the training of convolutional neural network using Paraview", Proceedings of the 1st Workshop on Distributed Infrastructures for Deep Learning, 11-16, 2017.

57.) M. Zeyen, J. Ahrens, H. Hagen, K. Heitmann, S. Habib, "Cosmological particle data compression in practice", Proceedings of the In Situ Infrastructures on Enabling Extreme-Scale Analysis and Visualization, 12-16, 2017.

56.) M. Larsen, J. Ahrens, U. Ayachit, E. Brugger, H. Childs, B. Geveci, C. Harrison, "The ALPINE In Situ Infrastructure: Ascending from the Ashes of Strawman", Proceedings of the In Situ Infrastructures on Enabling Extreme-Scale Analysis and Visualization, 42-46, 2017.

55.) J. Patchett, B. Nouanesengesy, J. Pouderoux, J. Ahrens, H. Hagen, “Parallel multi-layer ghost cell generation for distributed unstructured grids”, IEEE 7th Symposium on Large Data Analysis and Visualization (LDAV), 84-91, 2017.

54.) J. Woodring, J. Ahrens, J. Patchett, C. Tauxe, D. Rogers, "High-dimensional scientific data exploration via Cinema", 2017 IEEE Workshop on Data Systems for Interactive Analysis (DSIA), 1-5, 2017.

53.) V. Adhinarayanan, W. Feng, D. Rogers, J. Ahrens, S. Pakin, "Characterizing and Modeling Power and Energy for Extreme-Scale In-situ Visualization", 2017 IEEE International Parallel and Distributed Processing Symposium (IPDPS), 978 - 987, 2017.

52.) D. Banesh, J. Schoonover, J. Ahrens, B. Hamann, "Extracting, Visualizing and Tracking Mesoscale Ocean Eddies in Two-dimensional Image Sequences Using Contours and Moments", Workshop on Visualisation in Environmental Sciences (EnvirVis), 2017.

51.) A. Berres, T. Turton, M. Petersen, D. Rogers, J. Ahrens, K. Rink, A. Middel, D. Zeckzer, R. Bujack, "Video Compression for Ocean Simulation Image Databases", Workshop on Visualisation in Environmental Sciences (EnvirVis), 2017.

50.) J. Patchett, B. Nouanesengsy, G. Gisler, J. Ahrens, H. Hagen, "In Situ and Post Processing Workflows for Asteroid Ablation Studies", EuroVis 2017-Short Papers, 2017.

49.) T. Turton, A, Berres, D, Rogers, J, Ahrens, "ETK: An Evaluation Toolkit for Visualization User Studies", EuroVis 2017-Short Papers, 109-173, 2017.

48.) [Best Paper Award] H. Carr, G. Weber, C. Sewell, J. Ahrens, "Parallel peak pruning for scalable SMP contour tree computation", IEEE 6th Symposium on Large Data Analysis and Visualization (LDAV), 75-84, 2016.

47.) C. Ware, D. Bolan, R. Miller, D. Rogers, J. Ahrens, "Animated versus static views of steady flow patterns", ACM Symposium on Applied Perception, pgs. 77-84, 2016.

46.) F. Samsel, S. Klaassen, M. Petersen, T. Turton, G. Abram, D. Rogers, J. Ahrens, "Interactive Colormapping: Enabling Multiple Data Range and Detailed Views of Ocean Salinity", CHI - Extended Abstracts on Human Factors, 2016.

45.) C Ware, D Rogers, M Petersen, J Ahrens, E Aygar, "Optimizing for Visual Cognition in High Performance Scientific Computing", Electronic Imaging 2016 (16), 1-9.

44.) C. Sewell, K. Heitmann, H. Finkel, G. Zagaris, S.T. Parete-Koon, P. Fasel, A. Pope, N. Frontiere, L. Lo, B. Messer, S. Habib, J. Ahrens, “Large-Scale Compute-Intensive Analysis via a Combined In-situ and Co-scheduling Workflow Approach. Proceeding of International Conference for High Performance Computing, Networking, Storage, & Analysis (SC), Supercomputing 2015, November 2015.

43.) [Best Scientific Visualization & Data Analytics Showcase], F. Samsel, M. Petersen, G. Abram, T. Turton, D. Rogers, J. Ahrens, ”Visualizing Ocean Currents and Eddies in a High-Resolution Global Ocean-Climate Model”, Proceeding of International Conference for High Performance Computing, Networking, Storage, & Analysis (SC), Supercomputing, 2015. https://vimeo.com/145875477

42.) C. Sewell, L. Lo, K. Heitmann, S. Habib, J. Ahrens, “Utilizing Many-Core Accelerators for Halo and Center Finding within a Cosmology Simulation”, Proceedings of the IEEE Symposium on Large Data Analysis and Visualization (LDAV), October 2015.

41.) W. Widanagamaachchi, K. Hammond, L. Lo, B. Wirth, F. Samsel, C. Sewell, J. Ahrens, V. Pascucci, “Visualization and Analysis of Large-Scale Atomistic Simulations of Plasma-Surface Interactions”. Proceedings of EuroVis (short paper), May 2015.

40.) X. Adhinarayanan, W. Feng, J. Woodring, D. Rogers, J. Ahrens, “On the Greenness of In-Situ and Post- Processing Visualization Pipelines”, The Eleventh Workshop on High-Performance, Power- Aware Computing at IPDPS 2015, May 2015.

39.) F. Samsel, G. Abram, M. Petersen, J. Wendelberger, T. Geld and J. Ahrens, “Colormaps that Improve Perception of High-Resolution Ocean Data”, CHI EA 2015, April 2015.

38.) J. Ahrens, S. Jourdain, P. O'Leary, J. Patchett, D. Rogers, M. Petersen, “An Image-based Approach to Extreme Scale In Situ Visualization and Analysis”, Proceeding of International Conference for High Performance Computing, Networking, Storage, & Analysis (SC), Supercomputing 2014, November 2014.

37.) B. Nouanesengsy, J. Woodring, J. Patchett, K. Myers, and J. Ahrens, “ADR Visualization: A Generalized Framework for Ranking Large-Scale Scientific Data using Analysis-Driven Refinement”, IEEE Symposium on Large-Scale Data Analysis and Visualization (LDAV), 2014.

36.) W. Widanagamaachchi, P-T. Bremer, C. Sewell, L. Lo, J. Ahrens, V. Pascucci, “Data-Parallel Halo Finding with Variable Linking Lengths”, IEEE Symposium on Large-Scale Data Analysis and Visualization (LDAV), 2014.

35.) Yu Su, Gagan Agrawal, Jonathan Woodring, Kary Myers, Joanne Wendelberger, James P. Ahrens: Taming massive distributed datasets: data sampling using bitmap indices, HPDC 2013.

34.) Christopher Sewell, Li-Ta Lo, James P. Ahrens: Portable data-parallel visualization and analysis in distributed memory environments, LDAV 2013.

33.) Boonthanome Nouanesengsy, John Patchett, James Ahrens, Andrew Bauer, Aashish Chaudhary, Berk Geveci, Ross Miller, Galen M. Shipman, and Dean N. Williams, "Optimizing File Access Patterns through the Spatio-Temporal Pipeline for Parallel Visualization and Analysis". Proceedings of the Workshop on Ultrascale Visualization at SC13, 2013.

32.) Jonathan Woodring, James Ahrens, Timothy J. Tautges, Tom Peterka, Venkatram Vishwanath, Berk Geveci, "On-Demand Unstructured Mesh Translation for Reducing Memory Pressure during In Situ Analysis". Proceedings of the Workshop on Ultrascale Visualization at SC13, 2013.

31.) Yu Su, Gagan Agrawal, Jonathan Woodring, Kary Myers, Joanne Wendelberger, James Ahrens, "Taming Massive Distributed Datasets: Data Sampling Using Bitmap Indices", HPDC 2013.

30.) Uliana Popov, Eddy Chandra, Katrin Heitmann, Salman Habib, James P. Ahrens, Alex Pang: Analyzing the evolution of large scale structures in the universe with velocity based methods, PacificVis 2012.

29.) Li-Ta Lo, Christopher Sewell, James P. Ahrens: PISTON: A Portable Cross-Platform Framework for Data- Parallel Visualization Operators, EGPGV 2012.

28.) Christopher Sewell, Jeremy Meredith, Kenneth Moreland, Tom Peterka, Dave DeMarle, Li-ta Lo, James Ahrens, Robert Maynard, and Berk Geveci. "The SDAV Software Frameworks for Visualization and Analysis on Next-Generation Multi-Core and Many-Core Architectures". Proceeding of the Workshop on Ultrascale Visualization at SC12, 2012.

27.) Carson Brownlee, John Patchett, Li-Ta Lo, David E. DeMarle, Christopher Mitchell, James P. Ahrens, Charles D. Hansen: A Study of Ray Tracing Large-scale Scientific Data in Two Widely Used Parallel Visualization Applications, EGPGV 2012.

26.) Christopher Sewell, Jeremy S. Meredith, Kenneth Moreland, Tom Peterka, David E. DeMarle, Li-Ta Lo, James P. Ahrens, Robert Maynard, Berk Geveci: The SDAV Software Frameworks for Visualization and Analysis on Next-Generation Multi-Core and Many-Core Architectures. Proceeding of the Workshop on Ultrascale Visualization at SC12, 2012.

25.) J. Bent, S. Faibish, J. Ahrens, G. Grider, J. Patchett, and J. Woodring, “Jitter-Free Co-Processing on a Prototype Exascale Storage Stack”, Proceedings of 28th IEEE Symposium on Massive Storage Systems and Technologies, Pacific Grove, CA, April 2012.

24.) Christopher M. Brislawn, Jonathan Woodring, Susan M. Mniszewski, David E. DeMarle, James P. Ahrens: Subband coding for large-scale scientific simulation data using JPEG 2000, SSIAI 2012.

23.) Boonthanome Nouanesengsy, James P. Ahrens, Jonathan Woodring, Han-Wei Shen: Revisiting Parallel Rendering for Shared Memory Machines, EGPGV 2011.

22.) Christopher Mitchell, James P. Ahrens, Jun Wang: VisIO: Enabling Interactive Visualization of Ultra- Scale, Time Series Data via High-Bandwidth Distributed I/O Systems, IPDPS 2011.

21.) Jonathan Woodring, Susan M. Mniszewski, Christopher M. Brislawn, David E. DeMarle, James P. Ahrens: Revisiting wavelet compression for large-scale climate data using JPEG 2000 and ensuring data precision, LDAV 2011.

20.) J. Woodring, K. Heitmann, J. Ahrens, P. Fasel, C.-H. Hsu, S. Habib and A. Pope. “Analyzing and Visualizing Cosmological Simulations with ParaView”, The Astrophysical Journal Supplement Series, Volume 195, Issue 11, June 2011.

19.) C. Hsu, J. Ahrens, K. Heitmann, "Verification of the Time Evolution of Cosmological Simulations via Hypothesis-Driven Comparative and Quantitative Visualization", PacificVis 2010.

18.) J. Ahrens, J. Woodring, D. DeMarle, J. Patchett, M. Maltrud, "Interactive Remote Large-Scale Data Visualization via Prioritized Multi-resolution Streaming", Workshop on Ultrascale Visualization, Nov. 2009.

17.) J. Patchett, J. Ahrens, S. Ahern, D. Pugmire, "Parallel Visualization and Analysis with ParaView on a Cray XT4", CUG 2009, May 2009.

16.) J. Ahrens, J. Woodring, D. DeMarle, J. Patchett, M. Maltrud, "Interactive Remote Large-Scale Data Visualization via Prioritized Multi-resolution Streaming", Workshop on Ultrascale Visualization, Nov. 2009.

15.) J. Ahrens, L. Lo, B. Nouanesengsy, J. Patchett and A. McPherson, “Petascale Visualization: Approaches and Initial Results”, Ultrascale Visualization Workshop, November 2008.

14.) Emanuele Santos, Lauro Lins, James P. Ahrens, Juliana Freire and Claudio Silva, " A First Study on Clustering Collections of Workflow Graphs", International Provenance and Annotation Workshop, 2008.

13.) James Ahrens, Nehal Desai, Patrick McCormick, Ken Martin, Jonathan Woodring, "A Modular Extensible Visualization System Architecture For Culled Prioritized Data Streaming", Visualization and Data Analysis 2007, Proceedings of the SPIE - The International Society for Optical Engineering, Volume 6495, Jan. 2007.

12.) Andy Cedilnik, Berk Geveci, Kenneth Moreland, James Ahrens, and Jean Favre, "Remote Large Data Visualization in the ParaView Framework", Eurographics Symposium on Parallel Graphics and Visualization, pg. 163-170, May 2006.

11.) N. Fout, K-L. Ma, and J. Ahrens, "Time-Varying Multivariate Volume Data Reduction", ACM SAC 2005, March 2005.

10.) P. McCormick, J. Inman, J. Ahrens, G. Roth and C. Hansen, "Scout: A Hardware-Accelerated System for Quantitatively Driven Visualization and Analysis" Proceedings of the IEEE Visualization 2004 Conference , October 2004.

9.) A. Stompel, K-L. Ma, E. Lum, J. Ahrens, J. Patchett, "Scheduled Linear Image Compositing for Parallel Volume Rendering", IEEE Symposium on Parallel and Large-Data Visualization and Graphics, October 2003.

8.) C.C. Law, A. Henderson, J. Ahrens, "An Application Architecture for Large Data Visualization: A Case Study", IEEE Symposium on Parallel and Large-Data Visualization and Graphics, October 2001.

7.) T.A. Keahey, P. McCormick, J. Ahrens, K. Keahey, "Qviz: a Framework for Querying and Visualizing Data", Proceedings of SPIE Vol. 4302 - Visual Data and Exploration and Analysis VIII, January 2001.

6.) K. Keahey, P. Beckman and J. Ahrens, "Ligature: Component Architecture for High-Performance Applications", 1st NASA Workshop on Performance-Engineered Information Systems, September 1998.

5.) J. Ahrens and J. Painter, "Efficient Sort-Last Rendering Using Compression-Based Image Compositing", Second Eurographics Workshop on Parallel Graphics and Visualization, September 1998.

4.) J. Ahrens, P. McCormick, J. Bossert, J. Reisner, J. Winterkamp, "Case Study: Wildfire Visualization", Proceedings of IEEE Visualization 1997, pp. 451-454, October 1997.

3.) J. Ahrens and C. Hansen, "Cost-Effective Data-Parallel Load Balancing", International Conference on Parallel Processing, Vol. 2, pp. 218-21, August 1995.

2.) L. Shapiro, S. Tanimoto, J. Brinkley, J. Ahrens, R. Jakobovits and L. Lewis, "A Visual Database System for Data and Experiment Management in Model-Based Computer Vision", Second CAD-Based Vision Workshop, pp. 64-72, February 1994.

1.) F. Ortega, C. Hansen and J. Ahrens, "Fast Data Parallel Polygon Rendering", IEEE Supercomputing, pp. 709-18, November 1993.