This $400,000 Project Grant awarded by the National Science Foundation Division of Information and Intelligent Systems under CFDA 47.070 (Computer and Information Science and Engineering) supports collaborative research to develop responsible methods for the design and validation of algorithmic rankers. The key objectives are to: Quantify the impact of item attributes and engineering choices on ranked outcomes to guide the selection of appropriate scoring functions. Quantify the impact of data...
The National Science Foundation (NSF) awarded a $400,000 Project Grant to the New Jersey Institute of Technology (NJIT) under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070). The four-year grant, effective from September 1, 2023 to August 31, 2027, supports collaborative research on the responsible design and validation of algorithmic rankers. The project aims to develop methods to: 1) quantify the impact of item attributes and data engineering choices on ranked...
This Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $400,000 to The Leland Stanford Junior University to research methods for encoding societal values into social media ranking algorithms. The key goals are to: 1) develop techniques for translating social science constructs into algorithmic objective functions, 2) create a library of societal objective functions based on validated theory, and...
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...
This Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) in the amount of $395,059 will support research at the University of Washington to develop techniques for encoding societal values into social media ranking algorithms. The key objectives are: Introduce a novel method using large language models to build algorithmic objective functions that represent social science constructs, referred to...
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 $404,941 Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) supports research by Northeastern University to develop methods for integrating societal values into social media algorithms. The key products or services to be delivered include: Introducing a novel approach to leverage social science constructs and measurements to build algorithmic objective functions, referred to as...
This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $175,000 to Purdue University to conduct research on rank-based decomposable losses for machine learning. The project aims to explore novel aggregate and individual rank-based losses to advance robust machine learning techniques, with a focus on improving optimization algorithms, hyperparameter selection, and theoretical guarantees. The...
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 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 Project Grant award from the National Science Foundation's (NSF) Division of Information and Intelligent Systems (CFDA 47.070 - Computer and Information Science and Engineering) provides $400,000 to New York University (NYU) from September 1, 2023 to August 31, 2027.
The project focuses on developing methods to validate and design responsible algorithmic rankers used in critical domains like hiring, education, and lending. Key objectives include: 1) quantifying the impact of input attributes and data pre-processing choices on ranking outcomes to guide the design of appropriate scoring functions; 2) assessing the impact of data uncertainty and scoring formula changes on ranking stability to improve robustness; and 3) measuring fairness of ranked outputs with respect to underrepresented groups to enable fairness-enhancing interventions. The research outcomes are expected to enable technical improvements as well as identify limitations where alternative screening processes may be needed. The project will also incorporate educational and outreach components.