REU Site: Undergraduate Research Experiences in Artificial Intelligence, Data Analytics, and Mixed Reality for Smart and Connected Health

This project aims to engage undergraduate students in innovative research focusing on the topics of Smart and Connected Health and Smart and Connected Communities. Through the Research Experiences for Undergraduates (REU) site at Texas State University, students will explore emerging areas such as intelligent emotion recognition for children with Autism Spectrum Disorder (ASD), Artificial Intelligence (AI)-driven systems to enhance firefighting responses, and technology-assisted sports assessments for individuals with spinal cord injuries. The program offers a unique opportunity for students to collaborate on projects that apply machine learning, artificial intelligence, and Internet-of-Things (IoT) technologies to address real-world challenges. For instance, students will work on developing smart home systems that utilize AI to create personalized and supportive environments for individuals with ASD and improve diagnosis methods for chronic ankle instability using biomechanics and patient-reported outcomes. Additionally, students will explore advanced computer vision techniques for object recognition and tracking for applied engineering applications. Participating in these interdisciplinary projects will gain hands-on experience applying cutting-edge technologies, preparing them for advanced studies and careers in STEM fields. This REU site at Texas State University will engage undergraduate students in research focusing on Smart and Connected Health (SCH) and Smart and Connected Communities (S&CC). The program aims to develop students' disciplinary knowledge and research skills through hands-on experiences in cutting-edge technologies, including machine learning (ML), artificial intelligence (AI), and the Internet of Things (IoT). The research activities encompass a wide range of topics, such as developing AI-driven emotion recognition systems for children with Autism Spectrum Disorder (ASD), building adaptive smart home environments, enhancing chronic ankle instability diagnosis, and improving adaptive sports participation for individuals with spinal cord injuries. Students will work on projects integrating advanced object recognition and tracking, autonomous data collection for smart-city firefighting, and AI-assisted communication tools for individuals with ASD. The participants will address complex real-world challenges through these projects, applying AI, deep learning models, and biomechanics to improve public safety, health outcomes, and overall quality of life within smart health and connected communities. The program will host nine students annually over three summers, with a particular emphasis on recruiting women and students from underrepresented groups. Each REU project will advance the state of the art in SCH and S&CC by leveraging computational models, data analytics, and real-time sensor integration, preparing students to contribute to future innovations in computing and health-related fields. The project will provide long-term engagement and support for students as they transition to advanced studies and professional careers in STEM disciplines. 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.