REU SITE: Research Experience for Undergraduates in Translational Applications of AI to Engineering (REU-TrACE)

The research experiences for undergraduates in the translational application of artificial intelligence to engineering (REU-TRACE) site will create novel research experiences for a talented and diverse group of undergraduate students from traditionally underrepresented populations with limited access to STEM research opportunities. Advances in Artificial Intelligence (AI) are helping engineers and scientists address fundamental questions of monitoring, understanding, and achieving the desired outcomes in human and animal health systems, agricultural productivity, and advanced manufacturing. To develop pathways for students with advanced technological skills, the ten-week research experience will focus on applying artificial intelligence principles, techniques, and technology to problems in 1) Design and Manufacturing, 2) Smart Infrastructure, 3) Biology, and 4) Sustainable Agriculture. The students will conduct research on AI applications to digital twins for advanced manufacturing, design of energy harvesting devices, prognostics of battery reliability, prediction of 3D protein structures, biomechanical characterization, manipulators for monitoring individual plants and others. The experience of working in an intensive research environment, where students will progress from dependent to independent contributors, will enable them to leave the program with life-long learning skills that will impact their contributions to science, engineering, and society. Over a three-year period, this REU Site program will engage ten undergraduate students per year in a 10-week intensive, summer research experience. The students will be active members of multidisciplinary groups and will interact with a diverse faculty team with broad research interests and an outstanding record of mentoring undergraduate students. The key components of this REU program include 1) well-defined research projects executed by students under the mentorship of faculty members and graduate students; 2) participation in cohort experiences such as programming bootcamp, joint seminars/meetings, workshops, and research facilities tours; 3) development of communication skills through technical reports and presentations; 4) professional development activities that include 'lunch and learns', short courses and communication workshops; and 5) an REU Research Symposium to provide feedback and recognize exceptional achievement. Students will also undergo training in the ethical implications of engineering conducted by Iowa State University's Bioethics program. A REU-TRACE alumni LinkedIn page will ensure that the participants have access to a built-in professional network that can help them to decide how to apply their AI research experience in their careers. This project is jointly funded by the Office of Advanced Cyberinfrastructure and the Established Program to Stimulate Competitive Research (EPSCoR). 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.