Collaborative research: epiic: accelerating sustainable partnerships for innovation, research, and entrepreneurship in AI (aspire-AI)

The National Science Foundation (NSF) awarded $399,226 to California State University, Bakersfield (through its Auxiliary For Sponsored Programs Administration) under the NSF Technology, Innovation, and Partnerships program (CFDA 47.084) on October 1, 2025, for the ASPIRE-AI (Accelerating Sustainable Partnerships for Innovation, Research, and Entrepreneurship in AI) collaborative research initiative. The project, scheduled for completion by September 30, 2028, will deliver institutional structures, resources, and frameworks designed to enhance regional capacity in artificial intelligence (AI) research and innovation among non-R1 institutions.

The primary deliverables include centralized partnership hubs, comprehensive faculty development programs, and interdisciplinary research initiatives that generate applied AI tools and actionable knowledge. Key intellectual contributions will include toolkits for managing external partnerships, faculty engagement playbooks, and technology transfer frameworks customized for under-resourced institutions. The project will also integrate AI across multiple research and curricular areas—including agriculture, healthcare, climate adaptation, and advanced manufacturing—while establishing a community of practice across cohort institutions to share successes, build institutional capacity, and strengthen regional workforce development in emerging technologies.

Abstract

Aspire-AI will accelerate sustainable external partnerships in artificial intelligence (AI) and applying AI to drive innovation, research, and entrepreneurship. The project aims to enhance regional economic growth and workforce development by establishing institutional structures for partnership development, strengthening faculty engagement, and advance workforce preparedness. Each collaborating institution brings unique strengths, leveraging regional and disciplinary expertise to address barriers such as limited infrastructure and fragmented institutional cultures. By promoting interdisciplinary research collaborations and building sustainable industry and community partnerships, aspire-AI generates actionable knowledge and tools to advance applied AI research and innovation. The cohort collaboration will create a model for non-R1 institutions to leverage external partnerships to enhance regional capacity in responding to emerging technologies and the impact IT will have on workforce development. Aspire-AI will establish centralized partnership hubs, implement comprehensive faculty development programs, and facilitate interdisciplinary research initiatives that generate actionable knowledge and tools to advance applied AI research and innovation. These efforts are supported by shared resources and a focus on scaling successes across cohort institutions, which naturally form a community of practice to augment mutual support for capacity building. The project will produce intellectual contributions including toolkits for managing external partnerships, faculty engagement playbooks, and technology transfer frameworks tailored to the challenges of under-resourced institutions. Aspire-AI will also integrate AI into research and curricula across fields such as agriculture, healthcare, climate adaptation, and advanced manufacturing, equipping students with the skills needed to address critical societal challenges through experiential learning activities. Additionally, aspire-AI will drive institutional cultural change that encourages and supports external collaboration in use-inspired research, innovation, and workforce initiatives. Through these efforts, the participating institutions have the opportunity to emerge as regional leaders in AI-driven research and innovation and become vital contributors to their regional innovation ecosystems. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the foundation's intellectual merit and broader impacts review criteria.- subawards are not planned for this award.