REU Site: Computing for Health and Well-being

This Research Experiences for Undergraduates (REU) site addresses the ongoing strains faced by the U.S. healthcare system due to short-term challenges, such as those posed by the COVID-19 outbreak, as well as long-term trends, such as aging population. To tackle these and other problems, the next generation of computer scientists should be trained to work with both computer scientists and health professionals on interdisciplinary, problem-focused teams. REU students will (1) learn about interdisciplinary research;(2) apply computational thinking to real-world problems; (3) become familiar with the culture and research methods of different disciplines; (4) participate in workshops on research methods, scientific communication, and career development; and (5) develop their first professional network while boosting self-confidence in their own skills and abilities. The special focus is on providing research experiences to students from schools that are not research institutions, schools that lack the interdisciplinary research opportunities afforded by the presence of a comprehensive medical center, and/or students from underrepresented groups, including a special emphasis on first-generation students. The goal is to help prepare a workforce of talented young scientists who will help maintain the nation's competitive advantage in science and technology. The REU participants will learn and apply algorithmic methods from computing and data science to enhance health and well-being. Tackling socially relevant problems and participating in professional development will provide students with an intellectually challenging and engaging experience, while fostering a passion for computer science and scientific research. Each student is integrated into an established research group working under a mentor's direct supervision on cutting-edge interdisciplinary challenges in health and well-being. Using the latest technology and computational tools, as well as advanced algorithmic methods from modeling, simulation, artificial intelligence, machine learning, and human-computer interaction, students will work on problems in areas such as infectious disease modeling, disease risk assessment, advanced hearing aid technology, screening tools to assess mood or emotion, and immersive technologies used to engage neurodiverse children through gameplay. Students will also learn through their interactions with other REU participants, graduate students, domain experts, and mentors. Exposure to a collection of diverse research projects within their cohort will further participants’ understanding of their own projects while broadening their appreciation of different research methods: at the same time, mentor development activities will help early-career faculty and advanced graduate students learn how to work effectively with young scientists. 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.