This Project Grant award was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070). The $289,894 award, effective October 1, 2024, supports Emory University's research project titled "Towards Fairness in the Real World Under Generalization, Privacy and Robustness Challenges." The project aims to investigate and develop solutions to ensure fairness in AI algorithms, which face practical...
This $597,149 Project Grant awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to advance fundamental research in fair algorithmic decision-making. The project at Purdue University will develop novel algorithms and software to facilitate the adoption and evaluation of fair artificial intelligence (AI) systems, with a focus on promoting health equity in applications like Alzheimer's disease research. Key...
This $600,000 federal Project Grant award from the National Science Foundation (NSF)'s Computer and Information Science and Engineering (CISE) program will support research and education efforts at the University of Illinois on the topics of fairness in algorithmic decision-making and machine learning. The project aims to advance the state-of-the-art on achieving fairness in computational resource allocation tasks, like vaccine distribution, as well as developing fairness concepts for machine...
The National Science Foundation awarded $235,438 under the Computer and Information Science and Engineering federal grant program to develop interpretable and fair machine learning frameworks, algorithms, and methodologies. The two-year project grant aims to address concerns that machine learning algorithms can inadvertently amplify human biases by funding research to design scalable, data-driven methods with provable fairness guarantees. Specifically, the grant will support the development of...
This Project Grant award of $500,000.00 from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) aims to address the critical need for trustworthy Artificial Intelligence (AI) and Machine Learning (ML), particularly in reinforcement learning (RL) systems used in applications like healthcare, education, and commerce. The project seeks to advance trustworthy RL by addressing challenges of data privacy, robustness against corruption, and fairness across diverse user...
This National Science Foundation (NSF) Project Grant award to Purdue University, under the Computer and Information Science and Engineering program (CFDA 47.070), focuses on developing novel technologies to enable robust, fair, and explainable data-driven decision-making systems. The $466,411 award, effective July 1, 2023 through June 30, 2028, will fund research to: 1) detect and mitigate biases in machine learning model outcomes, 2) assess the validity of data for learning fair and trustworthy...
The Trustees of the University of Pennsylvania received a $392,992 Project Grant from the National Science Foundation Division of Information and Intelligent Systems under the Computer and Information Science and Engineering program (CFDA 47.070). The grant will support research and education activities aimed at developing machine learning techniques that break through the fairness-accuracy tradeoff paradigm. Specifically, the university researchers will draw on ideas from learning theory and...
This $625,000 National Science Foundation project grant supports research at the University of Maryland, College Park toward developing fair machine learning algorithms and applications. Specifically, the grant funds the "Toward Fair Decision Making and Resource Allocation with Application to AI-Assisted Graduate Admission and Degree Completion" project. The research aims to design artificial intelligence systems that make admission and resource allocation decisions for graduate...
The National Science Foundation (NSF) awarded a $1,182,881 Project Grant to the University of California, San Diego (UCSD) under the NSF's Computer and Information Science and Engineering program (CFDA 47.070). The grant supports the development of new methods to ensure that machine learning models assigned to decisions such as lending and hiring can be changed through individual actions, protecting the right to access these services. The project will create techniques for (1) detecting...
This $331,698 National Science Foundation project grant supports research at Michigan State University to develop fair machine learning systems through improved data representations. Specifically, the Computer and Information Science and Engineering grant will fund research to study fundamental tradeoffs between utility and fairness in different data representations. The researchers will identify solutions to reduce gaps in achieving optimal tradeoffs and develop new representations and...