Building Partnerships to Bolster Training in Machine Learning and Artificial Intelligence for Graduate Students

About This Grant

This project will contribute to the national need for well-educated scientists, mathematicians, engineers, and technicians by supporting the retention and graduation of high-achieving, low-income students with demonstrated financial need at the University of Texas at El Paso (UTEP) and the University of Houston (UH). Both UTEP and UH are members of the Alliance of Hispanic Serving Research Universities (HSRU), an association of Hispanic-Serving Institutions with high research activity, affordability, strong community engagement, and commitment to serving first-generation and diverse students. UH is also an Asian American, Native American, and Pacific Islander Serving Institution. Over its one-year duration, this planning project will establish the necessary infrastructure and collaborations to lay the foundation for a future Track 3 S-STEM proposal to award scholarships to talented, low-income students pursuing a graduate degree in biomedical engineering or engineering technology with foci on machine learning (ML) and artificial intelligence (AI). Strategies will be developed to support student academic and career pathways, aligned with each institution's contexts and resources. This project will also develop a research plan to investigate the experiences of S-STEM scholars through an asset-based framework meant to recognize and leverage students' individual strengths. The overall goal of this project is to increase STEM degree completion of low-income, high-achieving undergraduates with demonstrated financial need. The project will focus on recruiting and supporting scholars in biomedical engineering (UTEP), computational health informatics (UH), and biotechnology (UH) to meet the national demand for professionals who understand and can apply ML and AI to biomedical problems. The central goal of this planning effort is to develop the basis for a multi-institutional project by: (1) identifying and recruiting faculty to participate in the collaborative partnership; (2) identifying institutional, systemic, and programmatic barriers for potential scholars; and (3) developing an asset-based graduate-level training framework. This project will identify evidence-based curricular and co-curricular activities for future scholars; engage the respective collaborating institutions' Financial Aid Offices to determine each institution's definition of low-income status; and establish inter-institutional agreements to benefit scholars at both institutions. Results will be disseminated among Texas minority-serving institutions and the Alliance of Hispanic-Serving Research Universities. This project is funded by NSF's Scholarships in Science, Technology, Engineering, and Mathematics program, which seeks to increase the number of low-income academically talented students with demonstrated financial need who earn degrees in STEM fields. It also aims to improve the education of future STEM workers and to generate knowledge about academic success, retention, transfer, graduation, and academic/career pathways of low-income students. 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.