This National Science Foundation (NSF) Project Grant award under the Computer and Information Science and Engineering (CISE, CFDA 47.070) program provides $200,000 in funding to George Mason University to develop a digital twin (DT) framework for individuals with autism spectrum disorder (ASD). The project aims to create computational models integrating clinical, neurological, and behavioral data to enable personalized predictions, uncertainty quantification, and optimized treatment interventions for ASD. Key focus areas include dynamic modeling, multimodal data integration, synthetic data generation, and a DT-based reinforcement learning framework. The research is expected to produce advancements in mathematical and statistical foundations that can enhance healthcare efficiency and promote community well-being beyond ASD. The project will also develop cyberinfrastructure to share algorithms, data, and open-source software, while training students and collaborating with medical experts and industry.