NRT-HDR: Transdisciplinary Graduate Training Program in Data-Driven Adaptive Systems of Brain-Body Interactions

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Nearly one in five Americans currently live with a disability that affects performance of their daily activities. Individuals living with complex disabilities as a result of substance use disorders, autism spectrum disorders, post-traumatic stress disorder and traumatic brain injury often have multiple negative health outcomes involving physical and psychosocial factors. These disabilities have pervasive societal, public health and economic consequences that impact individuals, families, support networks, and sometimes whole communities. Addressing this challenge requires an in-depth understanding of the physical and physiological underpinnings of the disabling condition, the environmental factors and social-ecological context that limits an individual's participation in daily activities, and the development of technological solutions to help overcome these barriers. The next generation STEM workforce charged with addressing this challenge must work together across traditional academic disciplinary boundaries to integrate engineering, data science and social science knowledge, while meaningfully engage with stakeholder communities in a mutually beneficial manner. This National Science Foundation Research Traineeship (NRT) award to George Mason University will address the need to train a versatile, interdisciplinary community-engaged STEM workforce with the skills to harness the data revolution to create fundamental research and translational innovations aimed at improving the quality of life for individuals with disabilities. The project anticipates training one hundred (100) PhD students, including nineteen (19) funded trainees, from electrical and bioengineering, data science, computer science, neuroscience, and the social sciences. The NRT project will include students with disabilities in the trainee cohort.Trainees will develop and use both data-collection devices and data-analysis techniques to promote data-driven solutions associated with complex disabilities that have major social, public health and economic consequences. For example, students may utilize their training in data analytics, wearable sensors and imaging to design new technology-assisted methods for personalized service delivery, to develop new machine learning algorithms to support the next generation of brain computer interfaces and improved prosthetic control systems, or to advance research on virtual reality based multisensory training. This NRT program will cross-train engineers, data scientists and social scientists to use state-of-the-art data analytic methods and wearable computing technologies based on a novel transdisciplinary CAP (competencies, applications and practice) curriculum and a community-engaged design project. The CAP curriculum will provide immersive, individualized training in data analytics, wearable sensors and imaging, contextualized in terms of applications (cognitive and behavioral neuroscience, human movement and function and neuroengineering) and scaffolded by hands-on practice in research and professional skills development. The design project will provide experience in convergent research, communication across disciplinary boundaries, and communication to a broad audience. Within George Mason University, the project will involve 14 core faculty from the Center for Adaptive Systems of Brain-Body Interactions, and an additional 15 faculty from 14 departments and 5 schools/colleges. By aligning with strategic institutional priorities and engaging diverse faculty mentors, this NRT project is well-positioned to sustain the traineeship model beyond the funded period.The NSF Research Traineeship (NRT) Program is designed to encourage the development and implementation of bold, new potentially transformative models for STEM graduate education training. The program is dedicated to effective training of STEM graduate students in high priority interdisciplinary or convergent research areas through comprehensive traineeship models that are innovative, evidence-based, and aligned with changing workforce and research needs.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.