CyberTraining: Pilot: NEXABio: Building a Next-Gen AI Biomaterials Workforce

Artificial intelligence is rapidly changing how new materials are discovered and developed for applications such as medical devices, drug delivery, and regenerative medicine. By helping researchers identify promising materials more quickly and efficiently, artificial intelligence can reduce development costs, accelerate innovation, and improve healthcare technologies. However, many students in bioengineering and materials science currently lack opportunities to learn how artificial intelligence can be applied to biomaterials research. This project addresses that workforce development challenge by providing interdisciplinary training that prepares students to combine expertise in biomaterials with modern data science and machine learning methods. The project will help build a skilled workforce capable of advancing next-generation healthcare technologies, strengthen the nation's capacity for innovation in biotechnology and advanced manufacturing, and broaden access to emerging computational tools that are transforming scientific discovery. This project, NEXABio, is a CyberTraining pilot program at the University of Texas at Dallas that prepares undergraduate and graduate students for artificial intelligence-driven biomaterials research. The program integrates CyberTraining workshops, a ten-day summer bootcamp, and invited lectures into a modular curriculum covering polymer chemistry, biomaterials design, structure-property relationships, machine learning fundamentals, representation learning, model evaluation, and uncertainty quantification. Participants will complete hands-on projects using publicly available biomaterials datasets to study topics such as predicting drug and gene delivery performance, selecting candidate monomers for material design, and evaluating prediction reliability. An online learning platform will support personalized exercises and progress tracking. The project aims to train 40 to 50 students annually while developing sustainable educational resources that can be adopted and disseminated broadly to support the growing intersection of artificial intelligence and biomaterials research. 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. NSF Award ID: 2612287 | Program: 01002627DB NSF RESEARCH & RELATED ACTIVIT | Principal Investigator: Yunhui Guo | Institution: University of Texas at Dallas, RICHARDSON, TX | Award Amount: $286,781 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2612287 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2612287.html