Special Issue

In today’s research landscape, software is essential across various disciplines. Many researchers utilize high-performance scientific codes to obtain simulation results, conduct data analysis, and visualize their findings. In recent years, there has been an explosion in the ways that the capabilities of large language models and AI are adapted and targeted for use in scientific discovery workflows. Research software engineers have always worked behind the scenes to maintain existing codes or improve their user experience; now they are also a key part of the teams integrating AI into the scientific enterprise. Research software engineers generally cover a wide range of roles, ranging from researchers who spend some of their time in programming to full-time software engineers who develop professional software to address research challenges.

This special issue, titled, “Advancing Science in the Age of AI”, will focus on the ways that RSEs and collaborators increase research impact during these rapidly changing times. Additionally, it will explore leadership and career paths for research software engineers.

Topics of interest include (but are not limited to) the following, with preference shown to those that focus on specific new challenges and opportunities in the current “age of AI”.

  • Discovery enabled by software
  • Architectures, frameworks, libraries, and technology trends
  • Research data management
  • Support for scalability and data-driven methods
  • Improving the reproducibility of research
  • Usability, portals, workflows, and tools
  • Sustainability, security, and stability
  • Software engineering approaches supporting research
  • Community engagement
  • Diversity, Equity, and Inclusion for RSEs and in RSEng
  • Training and workforce development
  • Building an RSE profession

Some examples of specific new challenges and opportunities in the current age of AI are: how AI changes the skills and responsibilities of research software engineers; challenges in the integration of LLMs into scientific research workflows; privacy, security, licensing, and attribution in AI-assisted development; and organizational policies for responsible use of generative AI.

Editorial board

If you have questions or wish to confirm your work is eligible to be submitted please contact the Special Issue Editors:

  • Patrick Diehl, Los Alamos National Laboratory
  • Dan Gunter, Lawrence Berkeley National Laboratory
  • Chen Zhang, Oak Ridge National Laboratory

You may contact them at usrse26-publications - at - us-rse.org.

Important dates

Dates will be announced soon once final coordination with the journal is completed.

  • Submission deadline: TBA
  • Authors receive first review: TBA
  • Revised manuscripts are due: TBA
  • Authors receive final notifications: TBA

Requirements

  • Only accepted talks and papers to USRSE’26 are invited to submit to the special issue.
  • Accepted work must be extended with at least 40% new content.
    • In the case of conference talks which submitted solely an abstract you must write a full paper if submitting to the special issue. We highly suggest discussing your work with the Special Issue Editors before undertaking any work.
    • We are unable to publish computational notebooks in the special issue. Authors may choose to write a full paper about their work based on their notebook. We highly suggest discussing your work with the Special Issue Editors before undertaking any work.
  • We will try to have at least one reviewer of the conference paper as a reviewer for the journal paper to assist with the decision.
  • The journal submission will undergo a separate evaluation process from the conference paper and acceptance is not guaranteed.

Submission details

Please follow the submission guidelines of the journal Future Generation Computer Systems carefully. The templates are available here.

Previous special issues