ABSTRACT

Recent years have witnessed a significant growth in computationally intensive scientific and engineering studies involving large-scale data processing, thereby driving groundbreaking innovations across STEM disciplines. These studies require an interdisciplinary approach, where a combination of domain-specific expertise and knowledge of developing scalable algorithms is necessary. The ten-week Research Experience for Undergraduates (REU) program at University of Wisconsin ? Eau Claire will provide a comprehensive research experience in high performance computing (HPC) and inspire a diverse group of students to pursue careers in STEM disciplines related to multidisciplinary computational science. The REU site will support research for ten undergraduate students each summer engaging them in a collaborative research experience with the central theme of designing computationally intensive algorithms and simulation models using HPC. The goal of the program is to attract students to careers in STEM and train them to use advanced hardware and computing resources, providing an opportunity that most undergraduate students do not get to experience during their course of study. The REU site will also work to promote national STEM workforce diversity goals by recruiting students from underrepresented groups in STEM at two-year colleges, where research opportunities are limited. With its focus on HPC and its application in diverse scientific disciplines, the project will serve to fulfill several of the key goals of NSF: to advance discovery and learning, to promote inclusion in the science and engineering workforce, and provide an integrated strategy to advance the frontiers of knowledge.

Through a focused research experience provided by research mentors, students will have the opportunity to develop new algorithms that utilize HPC infrastructure to solve scientific problems. Students will learn to complete research projects, develop simulation and predictive models, analyze results, prepare manuscripts for submission in journals, conference proceedings, and do technical presentations. A total of ten projects from five separate research domains in computational science will be made available to the students. These domains include (1) deep learning and computer vision with applications in biomedical imaging, pattern recognition, and geospatial data analysis, (2) machine learning and its application to social media analytics, (3) quantum chemical simulation to probe events at the electron level, (4) multiscale modeling and simulation to explore complex biomolecular structure and function, and (5) computational astrophysical study of stellar structure and evolution. Additionally, the REU program will develop leadership and interpersonal skills through seminars in undergraduate research, diversity in STEM, scientific writing, ethics in computing, preparing for graduate school, service learning, and career planning. The REU program will also engage students through invited guest speaker presentations and field trips. The success of the REU site will be assessed by internal evaluation along with evaluation resources and services offered through the Comparative Evaluation for NSF CISE Research Experiences for Undergraduates (CERP-REU).

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.

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