About This Session
As data-intensive research, artificial intelligence, and machine learning expand across academic disciplines, demand for research computing support is growing rapidly at liberal arts institutions. These emerging needs introduce both challenges and opportunities — especially for institutions operating within established consortium IT environments.
Drawing on experiences from The Claremont Colleges, this session examines how research computing services — including consultation workflows, faculty and student training, and partnerships with regional high-performance computing (HPC) centers — can be aligned with consortium-wide infrastructure and collaboration models.
Key Topics
HPC Access
How small liberal arts colleges can connect faculty and students to advanced computing resources through regional HPC partnerships without building standalone infrastructure.
Training & Consultation
Developing scalable consultation workflows and training programs that serve researchers across disciplines — from chemistry to computational social science.
Consortium Coordination
How shared consortium IT structures can be leveraged to coordinate research computing support across multiple campuses efficiently.
AI & ML Demand
Navigating the surge in faculty and student demand for AI/ML compute resources in ways that are sustainable, equitable, and aligned with institutional priorities.
Learning Outcomes
- Identify challenges and opportunities in coordinating research computing support within consortium IT environments.
- Understand practical approaches for connecting faculty and students to external HPC and advanced computing resources through partnerships.
- Explore governance and collaboration strategies for supporting research computing across multiple campuses in a shared consortium model.