This Cooperative Agreement award of $999,919 from the National Science Foundation (NSF) under the Technology, Innovation, and Partnerships (CFDA 47.084) program supports the development of an autonomous air traffic management (ATM) solution for uncrewed aerial vehicles (UAVs). The project aims to enable efficient, safe, and cost-effective deconfliction of dense UAV operations, addressing the growing need for robust ATM solutions to unlock the societal and economic potential of UAVs. The key...
This $550,000 Project Grant award from the National Science Foundation (NSF) Technology, Innovation, and Partnerships (TIP) program (CFDA 47.084) supports the development and demonstration of a novel system to provide secure, unmanned, aerial vehicle guidance in limited connectivity environments. The project aims to develop secure communication protocols for robust and accurate vehicle position, navigation, and timing (PNT) when GPS or GNSS signals are compromised or unavailable. The key...
This $250,000 federal Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) supports a collaborative research project to enhance the cognitive capabilities of aviation maintenance technicians through the integration of artificial intelligence (AI) and extended reality (XR) technologies. The primary goal is to improve inspection processes and reduce maintenance errors that cause aircraft accidents. The award is funding research and development led by a...
This Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) supports a collaborative research project led by Clemson University, in partnership with Purdue University, Greenville Technical College, and several industry/professional organizations. The goal is to leverage artificial intelligence (AI) and extended reality (XR) technologies to enhance the cognitive capabilities of aviation maintenance technicians during critical aircraft inspection...
This National Science Foundation (NSF) Technology, Innovation, and Partnerships (CFDA 47.084) award to Changeaerial LLC provides $274,727 to integrate deep learning algorithms with uncrewed autonomous system (UAS) imaging to enable automated inspection and monitoring of electric power grid infrastructure. The goal is to develop a hybrid AI model framework that can detect defects and damage in overhead electric utility equipment using temporal changes in UAS imagery. Additional AI algorithms will...
The National Science Foundation (NSF) Division of Information and Intelligent Systems awarded a $400,000 Project Grant to The Trustees of Princeton University, Office of Research and Project Administration, under the NSF Computer and Information Science and Engineering (CFDA 47.070) program. This 3-year grant supports collaborative research on developing theories and algorithms for scalable multi-agent planning and control to enable safe and robust autonomous electrical vertical take-off and...
This National Science Foundation (NSF) Technology, Innovation, and Partnerships (CFDA 47.084) Project Grant award of $275,000 to Quantireal Inc. aims to develop computational methods to generate realistic synthetic data for training machine learning algorithms used in advanced passenger and personal property screening technologies. The project will focus on creating a cost-efficient radiation physics solver to virtually scan representative object assemblies and generate precisely annotated...
This federal Project Grant award, provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program, aims to create a framework that integrates real-time safety verification and assurance into the performance optimization process of AI-driven safety-critical systems. The $209,421 award, effective July 1, 2024, through June 30, 2029, will enable researchers at the New Jersey Institute of Technology (NJIT) to devise innovative...
This $300,000 Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) supports research by the University of Maryland, College Park to enhance pilot training through the development of methods for optimizing sensory-motor interactions. The goal is to reduce training duration and improve safety by leveraging secondary sensory cues, such as touch and audition, and insights into pilot neurophysiology. The research involves creating a pilot training...
This $304,943 Project Grant awarded by the National Science Foundation (NSF) under the Technology, Innovation, and Partnerships (TIP) program (CFDA 47.084) supports the development and testing of an AI-driven foundation modeling framework for the atmosphere and ocean. The goal is to create an advanced multimodal AI model that can provide essential environmental intelligence to help businesses, governments, and municipalities navigate environmental volatility and extreme weather events. The model...
This Project Grant award of $304,695 from the National Science Foundation (NSF) Technology, Innovation, and Partnerships (TIP) program (CFDA 47.084) aims to develop and validate predictive algorithms for enhancing aviation safety at airports without air traffic control towers. The research will leverage machine learning and data analytics to generate probabilistic 4D aircraft trajectories, enabling earlier and more accurate alerts to general aviation pilots and reducing the risk of mid-air collisions and near-misses. The project, awarded to Digital Copilot, Inc. on June 1, 2025, with an ultimate completion date of November 30, 2025, will address the critical safety gap for over 90% of U.S. airports that lack coordinated traffic separation services, ultimately improving safety reporting metrics and supporting the broader commercial impact of reducing mid-air incidents. No sub-awards are planned for this award.