Birds of a Feather

AI in Practice - Managing Research Projects Incorporating Artificial Intelligence

David Pettifor, Daniel Madren, and Kenton McHenry

The substantial shift in the technological landscape that Artificial Intelligence has brought to the research community is felt across the board. It seems like everywhere we turn, AI has infiltrated conversations, opinions, and expectations. To some, it may be a simple buzzword and expect the fad to fade. Others may see it as a secret sauce to “just make my project better.” How do we, as RSEs and leaders in tech, approach AI with responsibility and effectively communicate its value-add to research? Beyond that, might this be game changing for RSEs, who are often underfunded on grants so as to be more competitive, yet committed to deliverables larger in scope than their time commitment. How might RSE leverage such tools safely? Join us as we share our perspectives and recent experiences with integrating AI into a variety of research projects.

Accelerating Research: Strategies from the Field

Jen Rosiere Reynolds, Lance Parsons, Gail Rosenbaum, Jason Simms, and Sarah Stevens

Accelerating Research: Strategies from the Field is a Birds of a Feather (BoF) session aimed at exploring how research software engineering (RSE) and computational tools are being utilized to enhance research capacity and impact across various institutions and disciplines. This session will feature a diverse panel of individuals and organizations actively engaged in building and supporting the systems that facilitate computational research. The session will begin with panelists sharing their strategies, operational models, and the impacts of their work. Following the panel, the session will transition to an interactive format, inviting audience members to participate in a structured discussion. This session is geared towards practicing RSEs, researchers who utilize or depend on computational methods, institutional leaders looking to enhance their RSE efforts, and community builders interested in supporting such collaboration. By showcasing real-world examples and encouraging collective problem-solving, this BoF aims to inspire practical next steps, deepen connections among attendees, and contribute to a more interconnected, effective, and sustainable research environment.

Better Scientific Software Fellowship Community

Elsa Gonsiorowski, Adam Lavely, and Mary Ann Leung

Software developers face increasing complexity in computational models, computer architectures, and emerging workflows. In this environment Research Software Engineers need to continually improve software practices and constantly hone their craft. To address this need, the Better Scientific Software (BSSw) Fellowship Program launched in 2018 to seed a community of like-minded individuals interested in improving all aspects of the work of software development. The BSSw Birds of a Feather session brings together alumni, honorable mentions, current fellows, BSSw leadership and potential applicants to discuss software best practices and the upcoming 2026 Fellowship requirements and deadlines.

Sustainable Models of RSE Support: The Prospects of Centralization in Institutional Research

Eric Manning, Lori Bougher, Colin Swaney, and Sangyoon Park

Research Software Engineers (RSEs) remain relatively new to the social sciences. With little precedent, how do you build an effective and sustainable model of RSE support?

We present a model of centralized support over more traditional siloing of RSEs in research labs. Centralization can offer greater stability in funding and demand in an uncertain climate, but forces a choice of versatility over depth in domain expertise.

Working with a lean team means clearly defining an RSE’s role, from broad strategy to project-specific deliverables. In the social sciences, models tend to fail when responsibilities are ill-defined—for example, when RSEs assume postdoc roles, centers replicate existing generalized services, or mission creep leads to indefinite support. In this model, RSEs generally do not take a co-authorship role or assist in the development of research questions or statistical methods.

We describe our workflow for managing projects under this model. While social scientists are generally experienced collaborators with deep technical expertise, outreach—explaining how RSEs can innovate and accelerate social science research–is a key challenge. Our adopted strategies include a discovery phase for consultations, department- and lab-specific outreach, and a consistent program of educational workshops.

Centralization enhances public good creation by expertly reconciling shared needs across departments and projects. We present two success stories: a machine-learning-as-a-service tool that offers a no-cost, private, replicable alternative to cloud services; and the emergence of a new role, Research Data Engineer, where we reintroduce a more active research component with technical concentration on the data engineering pipeline.