Collaborative Research: CISE Planning Proposal: OAC: CC*: Enhancing Cyberinfrastructure-infused Research at Texas A&M University-San Antonio (ECR-TAMUSA)

Enhancing Cyberinfrastructure-infused Research at Texas A&M University-San Antonio (ECR-TAMUSA) seeks to empower Texas A&M University San Antonio by building long-term capacity in high-performance computing (HPC) and artificial intelligence and machine learning (AI/ML) for its research and academic programs. The university will develop a support structure to meet the growing needs of advanced cyberinfrastructure (CI)-infused research in water-management, genomics, biology, chemistry, health, computing, humanities, social, natural, cybersecurity, and other applied sciences. This project addresses that gap through a sustainable and collaborative model that enhances multidisciplinary faculty collaborations on computational research, development of academic programs, and student research participation. The work supports national priorities by promoting the progress of science and expanding participation in the science, engineering, and entrepreneurial workforce. The project’s outcomes will help build cutting-edge computing. The project will develop a coherent campus-wide strategy that includes identifying the mechanisms by which researchers from different disciplines can form new research collaborations; determining the scope of joint research initiatives, including forming teams between CISE researchers and other domains scientists; incorporation of cybersecurity into research and student training activities; outlining a sustainability plan for growing computational research and campus CI; and developing training and education programs to facilitate research on advanced CI. The proposed work will provide the time, resources, input, research, and support from various stakeholders, ensuring that the resulting approach will be integrated intra-campus and with regional research programs. This work will better position the university to benefit from forthcoming regional and national initiatives that advance the use of AI/ML in research and academic programs. The outcomes will include innovative educational frameworks, enhanced research capabilities, and models of collaborative computational research that can be adopted by other emerging research institutions. 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.