This three-year, $600,000 project grant from the National Science Foundation's Computer and Information Science and Engineering program aims to develop learning-augmented mechanisms for algorithmic mechanism design. The grant supports research at Columbia University to design robust mechanisms guided by machine-learned predictions of agents' preferences. Researchers will consider learning-augmented mechanism design for canonical problems in areas like auction design, mechanism design without...
This three-year, $292,495 project grant from the National Science Foundation's Division of Computing and Communication Foundations aims to develop new data science techniques for economic environments under the Computer and Information Science and Engineering program (CFDA 47.070). The recipient, Drexel University, will conduct research to design learning algorithms and systems that can effectively interpret data in strategic settings where participants may manipulate information in anticipation...
This National Science Foundation Project Grant of $460,041 awarded to the University of Texas at Austin on October 1, 2021 supports research in algorithmic mechanism design under the Computer and Information Science and Engineering program (CFDA 47.070). The two-year project aims to develop new algorithmic techniques for designing market mechanisms that model consumer behavior and other real-world constraints more faithfully while maintaining simplicity and near-optimal performance....
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...
The National Science Foundation awarded Northwestern University a $600,000 Project Grant under the Computer and Information Science and Engineering program to develop mechanism design problems for the classroom. The grant will fund research exploring fairness in heterogeneous grading, optimizing study incentives through grading, and designing student feedback mechanisms over a three-year period from October 2022 to September 2025. Specifically, the university will study how to design classroom...
This Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program, with a total funding of $101,476, supports research to develop reliable decision-making algorithms for machine learning applications in complex systems. The 5-year project, which commenced on April 1, 2025, aims to address the challenge of ensuring safety and performance when deploying machine learning predictions in feedback loops, such as in weather...
The National Science Foundation (NSF) has awarded a $600,000 Project Grant under the Computer and Information Science and Engineering (CISE) program to The Trustees of Columbia University in the City of New York, operating through its Sponsored Projects Administration Division. The 3-year grant, awarded on February 1, 2024, supports research to address open questions in algorithmic game theory and its applications to online markets and platforms. Key research objectives include developing new...
The National Science Foundation (NSF) awarded a $360,000 Project Grant to the University of Illinois under the Engineering Program (CFDA 47.041) to support fundamental research and development on incentive design mechanisms. The 3-year project, commencing on September 1, 2024, aims to advance the theory of incentive design by removing stringent assumptions that limit its practical application. The research will explore how agents can learn each other's preferences, how behavioral traits...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CFDA 47.070) Project Grant award of $600,000 to the Massachusetts Institute of Technology (MIT) supports research into developing better algorithms for machine learning problems that involve sequential data with rich dependency structures. The project will explore learning methods for linear dynamical systems, graphical models, and hidden Markov models, with the goal of proving rigorous theoretical...
This Project Grant award of $300,000 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program supports research on developing machine learning models for structural decision-making. The goal is to create models that can capture an agent's preferences and understanding of environmental dynamics, enabling better prediction and adaptation of decision-making in complex real-world scenarios. The research will explore methods for...
This Project Grant from the National Science Foundation's Computer and Information Science and Engineering program totaling $599,996 will fund research into the development of learning-augmented mechanisms from October 1, 2022 to September 30, 2025. The goal of the research is to extend the framework of algorithms with machine-learned predictions to the design of mechanisms in the presence of strategic agents. Specifically, the award recipient Drexel University will consider the design and analysis of mechanisms for auction design, mechanism design without monetary transfers, online mechanism design, and decentralized settings that are enhanced with machine-learned predictions about agent preferences. The research aims to develop mechanisms that achieve strong performance guarantees when predictions are accurate, while maintaining optimal worst-case guarantees regardless of prediction accuracy. The results of the research have the potential to help overcome overly pessimistic impossibility results and transform the field of algorithmic mechanism design.