The National Science Foundation awarded a $500,000 Project Grant to the Texas A&M Engineering Experiment Station to advance optimization for threshold-agnostic fair artificial intelligence systems under the Computer and Information Science and Engineering program (CFDA 47.070). The three-year project aims to develop scalable stochastic optimization algorithms and novel threshold-agnostic fairness measures to directly optimize machine learning models for fairness without reliance on thresholds. Researchers will evaluate algorithms on tasks including image recognition, recommendation, spatial-temporal hazard prediction, and student performance prediction. The Texas A&M Engineering Experiment Station will collaborate with sub-awardees The University of Iowa and Louisiana State University on this research to integrate techniques into real-world systems and broaden training in AI and machine learning fields.