REU Site: Cyberinfrastructure (CI) Research for Societal Advancement REU

The nation’s ability to maintain global economic competitiveness depends on its efforts to prepare a diverse workforce trained in scientific computing and data science that will tackle grand challenges in multidisciplinary environments. The rapidly changing technology landscape further necessitates increased training using the national Cyberinfrastructure (CI) and training students as early as possible.

Advanced computing - data, high performance computing (HPC), artificial intelligence (AI), machine learning (ML), visualization, and analytics - is required to keep pace with the accelerating rate of scientific discoveries. In response to the National Science Foundation's mission to promote the progress of science; advance the national health, prosperity and welfare; and secure the national defense, the CI Research for Societal Advancement REU project is actively engaging 10 undergraduate students each summer for nine weeks in solving real-world problems of national relevance.

The REU project is preparing a future scientific workforce using advanced CI resources and building capacity in areas that support major advances in predictions across societal challenges. The inclusive research environment encourages creativity and collaboration amongst diverse social groups to develop innovative solutions and prepare students for careers that will ensure the country’s prosperity and security.

The REU aims to meet three objectives: 1) train students to use national CI by integrating the learning of computational science, AI, data-enabled science, and multidisciplinary science in preparation for graduate programs and the workforce; (2) train students to apply advanced computational skills, critical thinking, and creativity to research problems that advance society; and (3) increase the number of diverse and computationally trained students in science, technology, engineering, and mathematics (STEM) disciplines. The REU includes cutting-edge research in science and engineering disciplines, training using TACC resources, mentoring by The University of Texas (UT) at Austin and TACC researchers, social and team-building activities on the UT Austin campus, professional development and graduate school preparation, and opportunities to enhance communication skills.

Research projects emphasize advanced computing as a tool to power discoveries that will impact social change for future generations. Students use AI to support decision-making in resource management, and apply preference-based planning in AI to help develop theory and algorithms for designing and verifying autonomous systems at the intersection of computing, control theory, and learning theory.

Additionally, students enhance research resources for the modeling and prediction of porous material properties in the fields of petroleum, civil and environmental engineering, and geology. Other projects include simulating and controlling turbulent fluid flows, with a particular emphasis on creating large-scale turbulent simulations and other complex phenomena; investigating the application of constrained optimization models and algorithms to enforce fairness and reduce bias in machine learning models; and developing a bioinformatics pipeline in support of new, cleaner chemical processes.

The REU aims to recruit at least 50% of students who identify as Black, Latinx/Hispanic, Native Hawaiian, and Pacific Islander, and also targets women, first-generation college students, and students from institutions without doctoral programs including Minority-Serving Institutions and community colleges.

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.