Project Grant 2040898
- This two-year Project Grant from the National Science Foundation's Division of Computing and Communication Foundations provides $174,999 to develop a novel technique for testing fairness in human decisions using algorithmic bias. The work will be performed by Rochester Institute of Technology under the Computer and Information Science and Engineering program (CFDA 47.070), which supports research and education across computing, communications, and information science. Specifically, the awardee...
- 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 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 $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...
- 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 Project Grant award of $160,673 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports research to combine algorithms and machine learning to improve decision-making under uncertainty. The project, led by New York University (NYU), will explore incorporating machine-learned predictions into algorithm design as well as developing learning models optimized for specific algorithmic objectives. This work aims to create a...
- This three-year, $292,993 project grant from the National Science Foundation's Computer and Information Science and Engineering program aims to develop fair algorithms for auctions, pricing, and marketing mediated by artificial intelligence. The grantee, Columbia University, will design new theoretical frameworks and AI algorithms to ensure consumers from protected groups are not harmfully discriminated against in advertising auctions, ride-sharing and loan pricing, and targeted social media...
- 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...
- 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...
- The University of California, Santa Barbara (UCSB) was awarded a $439,984 Project Grant by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Program (CFDA 47.070) to conduct research on mitigating bias in machine learning algorithms. The goal of the 3-year project is to develop theoretical frameworks and principled algorithms to enhance fairness in both static and dynamic machine learning-based decision-making systems. The research will investigate...
This $625,000 project grant from the National Science Foundation's Computer and Information Science and Engineering program will fund research into end-to-end fairness for algorithm-in-the-loop decision making in the public sector. New York University will lead the development of novel methods for identifying and correcting biases in massive, multivariate data used for algorithmic decision making. This will include building models to represent human decision making processes, auditing tools to evaluate data and subsequent decisions from these processes, and techniques to discover undesirable impacts. Co-Principal Investigators from Harvard University and the University of Minnesota will co-supervise machine learning aspects and focus on statistical methods for anomalous pattern detection and discovering heterogeneous treatment effects to support these goals. The sub-awardees will contribute their expertise in interdisciplinary statistical machine learning and machine learning method development to help enable the automatic evaluation of fairness in algorithm-assisted public sector decisions.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $0 | 9/1/21 | ||
| Not listed | $0 | 5/20/21 | ||
| Not listed | $625.0k | 1/25/21 |
GrantNumber | Description | Subgrantee | Prime Award | Dollars Obligated | Updated At |
|---|---|---|---|---|---|
F165102S | President And Fellows Of Harvard College | Project Grant 2040898 | $138.4k | 10/18/21 | |
F165101S | Regents Of The University Of Minnesota | Project Grant 2040898 | $138.4k | 2/9/21 |