REU Site: Interdisciplinary Research Experience in Computational Sciences

About This Grant

Computational science provides a foundation for modern scientific research. The very rapid development of high performance computing platforms, together with a similar emergence of highly accurate algorithms, allow the treatment and modeling of complex systems that were intractable just a few years ago. The use of Artificial Intelligence, including Large Language Models and Machine Learning techniques, has opened a new venue for computational approaches. In parallel, automated scientific instruments create massive amounts of measurements that demand modern scientific computing methods to process and understand. However, computational science will only fulfill its full potential if advances in undergraduate education accompany the advances in hardware and in numerical and data-based models. Frequently, students learn little, if any, computational science in the classroom and are not prepared for computational science or data science research. This project provides an evidence-based approach to address these issues and prepare the next generation of students. The 30 undergraduate students participating in this Research Experiences for Undergraduates (REU) site will be engaged in authentic computational science projects, learn how to use state-of-the-art cyberinfrastructure tools, manage large amounts of data, experience activities that characterize research careers, and work in interdisciplinary research teams. The faculty mentors will provide activities that help students understand the nature of multidisciplinary research and the value of working as a team. These skills have the potential to be transformative in both the students' education as well as in their future careers. The Louisiana State University's Center for Computation & Technology (CCT), with its research activities organized into interdisciplinary focus areas that span traditional academic departments, provides an ideal setting for the REU students to experience interdisciplinary research. With research groups working on problems like gravitational waves, complex emergent phenomena in material science, and computational arts, the participants will be working on cutting edge research in computational science. An extensive training component will remedy any weak preparation of students in computational science, providing knowledge on how to leverage state-of-the-art cyberinfrastructure tools. At the conclusion of the REU, students are encouraged to continue their research and present their work at their home institution, informing others about computational science. The combination of individual training with student immersion in a multidisciplinary research group has previously been successful in engaging students to explore computational science. 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.