EAGER: NAIRR Pilot Expansion: FA1: Swarm Coordination and Autonomous Learning for Emerging Researchers (SCALE)

About This Grant

The Swarm Coordination and Autonomous Learning for Emerging Researchers (SCALE) project addresses a critical gap in STEM education by providing students with access to advanced artificial intelligence (AI) training and hands-on experience in autonomous systems. SCALE develops a specialized AI curriculum that introduces innovative topics such as federated learning, explainable AI, and privacy-preserving data sharing. These curricular innovations will be shared broadly, facilitated via the National AI Research Resource (NAIRR) Pilot, to give students the opportunity to engage with cutting-edge technologies that are often inaccessible in their regions. By offering field-based learning experiences, the project ensures that students are well-equipped to apply advanced AI tools to real-world challenges, many of which are inspired by the research needs of national laboratories and universities. The SCALE project’s primary objective is to develop a comprehensive AI curriculum that integrates theoretical knowledge with hands-on application. The curriculum will focus on four key areas: (i) AI Curriculum Development, including advanced AI techniques such as federated learning, explainable AI, homomorphic encryption, neural networks, and other emerging topics, delivered through a combination of lectures, exercises, and simulations. (ii) Federated Learning for Drone Teams, where the project will focus on federated learning techniques that enable drone systems to collaboratively improve AI models without sharing raw data. Students will work with state-of-the-art tools and platforms, such as cloud-based platforms or specialized computing environments, in the NAIRR Pilot, to apply federated learning to drone swarms in real-world scenarios. (iii) Privacy-Preserving Data Sharing, where SCALE will integrate privacy-preserving methods such as homomorphic encryption, blockchain-based smart contracts, and other techniques into the curriculum to teach students how to secure data and model training processes across distributed systems. (iv) Field-Based Training, in which students will engage in real-world training scenarios, such as using AI models to control autonomous drone systems in dynamic environments. This hands-on experience will involve activities like mission planning, real-time decision-making, and implementing secure communication strategies. By combining these innovative educational approaches, SCALE will prepare students for careers in AI and autonomous systems while making significant contributions to both the academic and practical development of these technologies. 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.