[Ieee_vis] CFP for ISAV: In Situ AI, Analysis and Visualization at #SC26

[Matthew Larsen]

https://isav-workshop.github.io/2026/

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ISAV'26: In Situ Analysis and Visualization
12th Annual Workshop at SC26
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WORKSHOP THEME
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HPC platforms and applications have reached such large scale, complexity, and
heterogeneity that a major challenge has become the wide gap between our ability
to compute extreme-scale data and our ability to gain insight from it to make
timely, data-driven decisions. A well-known, yet challenging, approach to visual
analysis, learning, and processing is performing the tasks in situ -- i.e.,
while the data is still in memory, potentially in lieu of saving the raw data
out.

Since 2015, ISAV has fostered a community of in situ developers, practitioners,
researchers, and users of in situ methods and infrastructure, connecting
industry, government laboratories, and academia across all career levels.
Through presentations, discussions, and peer-reviewed proceedings of research
findings, lessons learned, and early ideas, ISAV illuminates new requirements
and gaps driven by science and engineering applications and fosters the
application of in situ methods.

This is the 12th year of the ISAV workshop. Continuing from last year, we now
invite full paper submissions and in situ methods on ML/AI. We are also
expanding the lightning talks track to a "Community Talks" track, inviting
members to share early research ideas, hands-on practical learnings, and
insights into creative solutions, with more emphasis on practical experiences
and knowledge sharing.

In situ methods are in high demand:

  - In training ML/AI surrogate models or leveraging ML/AI for analysis
  - In system-scale 3D visualization for Exascale supercomputers
  - In cloud products providing responsive user experiences
  - In tightly coupled digital twins and computational sciences

Exploration in the in situ space is needed to address multifaceted goals:

  (1) To preserve important elements of simulations
  (2) To significantly reduce the data needed to preserve these elements
  (3) To offer as much flexibility as possible for post-processing exploration
  (4) To accelerate the gathering of insights for timely decision-making

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PARTICIPATION / CALL FOR PAPERS
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ISAV'26 invites three submission types:

  Full Papers        Up to 10 pages (including references)
  Short Papers       5 pages + 1 page references
  Community Talks    Abstract, 1 page (including references)

Full papers should present research results, identify opportunities or
challenges, or present case studies/best practices for in situ methods. Short
papers may cover the same topics or document late-breaking ideas and early
progress on novel concepts. Community talks invite members to share early
research ideas and practical learnings, with emphasis on knowledge sharing.

Full and short papers will appear in the workshop proceedings; all authors will
be invited to give an oral presentation at the workshop.

AREAS OF INTEREST

  Methods, Algorithms & Synthesis between HPC & ML
    In situ analysis (feature detection, data reduction/compression, data
    summarization, ML training) and scientific visualization using data-driven,
    surrogate-assisted, statistical, or time-varying methods.

  Applications & Workflows
    Applications (simulations, data processing, scientific user facilities)
    and integrations into digital twins. Workflows for complex in situ
    processing pipelines, including resilience and reproducibility.

  Scalability Requirements
    Scalability, resource utilization, data flow, and simplified access to
    extreme heterogeneous resources. Real-time coupling of data, surrogates,
    and algorithms.

  Case Studies, Data Sources & Best Practices
    Examples of solving specific science challenges with in situ
    methods/infrastructure. Deployments and software engineering.

  Software Evolution & Standardization
    In situ libraries from research prototypes to production quality.
    Challenges, gaps, API designs, and community standards.

  Enabling Hardware & Emerging Architectures
    Hardware and system architectures enabling in situ processing. Efficient
    use of accelerators and heterogeneous architectures across HPC, data
    center, or edge.

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REVIEW PROCESS
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All submissions undergo peer review by three domain experts, evaluated on:
relevance, technical soundness, creativity, originality, and impact.

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IMPORTANT DATES
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  Submission deadline (all types)    07 Aug 2026
  Author notification                04 Sep 2026
  Camera-ready copy due (FIRM)       25 Sep 2026
  ISAV'26 workshop                   Week of SC26

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