REU Site: AI Research for Intelligent Systems and Efficiency

Artificial Intelligence (AI) serves as a strategic engine for economic growth, national security, and global competitiveness. This project establishes a Research Experiences for Undergraduates (REU) site, AI Research for Intelligent Systems and Efficiency (ARISE), in the Electrical and Computer Engineering Department at the University of Arizona. The project recruits and trains eight undergraduate students each summer, engaging them in immersive research at the intersection of AI applications, efficient algorithms, and hardware system optimization. The overarching goal is to address real-world engineering challenges through sustainable and effective computational solutions. The project’s novelties are its focus on the "full-stack" nature of AI integrating the systems and hardware architecture with high-level AI applications and algorithms and a collaborative mentoring approach that provides participants with multidisciplinary expertise. The project's broader significance and importance are the development of a skilled workforce in national priority areas; the creation of educational demos and course materials for the public; and the fostering of technology transfer to industry partners to strengthen the domestic technology ecosystem. The ARISE REU site organizes research into three complementary thrusts: AI Applications, Efficient Algorithms, and Hardware Systems. Each project is co-mentored by faculty paired from different thrusts to facilitate interdisciplinary collaboration across the computing stack. Research projects focus on the frontiers of the field, exposing students to state-of-the-art AI algorithms, efficient training and inference techniques, and distributed learning. The technical approach emphasizes application-guided optimization, high-performance computing, reconfigurable systems, and hardware-software co-design to solve real-world engineering tasks, including autonomous agents, design automation, healthcare, and defense applications. Participants gain expertise in energy-efficient AI through intensive bootcamps, research seminars, and systematic training in research methodologies. Structured mentoring and professional development activities prepare participants for diverse careers in the AI infrastructure and semiconductor sectors. The project shares outcomes through technical publications, demonstrations, and the integration of research findings into university curricula and industry-university cooperative research centers. This work strengthens the national capacity for AI innovation by preparing an interdisciplinary cohort of researchers to solve the efficiency bottlenecks of next-generation AI computing and systems. 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.