Do you help researchers using IT tools to further their research goals? Are you involved in research computing and/or data science training? Do you consult with researchers on more effectively doing their research with advanced computing resources? Compute with data?
The Researcher-Facing Track of the People Network brings together people from research computing groups, libraries, research institutes, and other organizations who support researchers in every phase of the research lifecycle. Many of us are also Data- & Systems-Facing, but this track is a community-led opportunity to discuss the practices, perspectives, and experiences of facilitation from any perspective.
Topics include:
Research computing facilitation
Outreach to all disciplines, esp. those under-represented, to aid with research computing resources
Education and training
The art and practice of facilitation
Increasing communications, collaborations, and team-building
Research computing UX and user-facing tech
And more, as determined by our members!
We connect via monthly calls and an email list. We also invite you to review and contribute to the Leading Practices of Facilitation!
Join Us!
Join Us! Create a membership profile to let us know who you are and what you’re interested in. You can add other People Network Tracks at the same time.
Monthly Calls
Monthly calls are on the second Thursday of the month, 1PM ET/ 12PM CT/ 11AM MT/ 10AM PT. Connection information and links to any materials are distributed via the Researcher-Facing email list.
Upcoming Call(s)
Title: Should Your Institution Host an Open Source LLM?
Coltran Hophan-Nichols, Director of Systems and Research Computing, Montana State University Johnathan Lee, Sr Systems Architect, Research Technology Office, Arizona State University
Date: June 11th, 2026
Abstract:
As interest in generative AI grows, many institutions are exploring how to support large language models in ways that align with privacy, security, research, and campus needs. This session will focus on local and institutionally managed open source LLMs as an alternative to closed, commercial, or provider-hosted services. We will discuss how institutions are aggregating demand, designing sustainable services, selecting infrastructure models, and balancing usability, cost, governance, security, and support expectations. Drawing on emerging peer examples and broader federal interest in open-source AI, participants will compare self-hosted hardware, cloud-based managed infrastructure, and hybrid approaches while considering the practical benefits, challenges, and tradeoffs of hosting open source LLMs on campus.
The R-F Track Committee is looking for new members as well. Please send us an email if you are interested in supporting our monthly calls – rf-coordinators@carcc.org.
