Worcester Polytechnic Institute received a five-year, $708k Project Grant from the National Science Foundation under the Computer and Information Science and Engineering program (CFDA 47.070). The grant will support the development of new scientific instruments for classroom observation using a multi-modal machine learning approach. The goal is to advance the development and use of research cyberinfrastructure to enable and accelerate discovery and innovation in computing, communications, and...
This $600,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to advance the field of artificial intelligence (AI) by investigating the mathematical foundations and practical applications of deep learning models. The research project, conducted by the University of Wisconsin-Madison, focuses on understanding the properties of neural networks, analyzing the progressively refined data...
The National Science Foundation (NSF) awarded a $461,597 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to Worcester Polytechnic Institute (WPI) to establish an Research Experiences for Undergraduates (REU) site focused on applied artificial intelligence (AI) research. The project, running from April 2024 to March 2027, provides undergraduate students, particularly those underrepresented in STEM, the opportunity to participate in AI research...
The National Science Foundation Division of Information and Intelligent Systems awarded a $1.2 million Project Grant to the International Computer Science Institute of Berkeley, California from October 1, 2021 to September 30, 2025. The grant supports research under the Computer and Information Science and Engineering program (CFDA 47.070) to develop scalable second-order methods for training, designing, and deploying machine learning models. The CFDA program aims to advance computing and...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) (CFDA 47.070) Project Grant award of $108,000 to the Georgia Tech Research Corp, Office of Sponsored Programs, will fund collaborative research to develop a unified framework for analyzing adaptive stochastic optimization methods for machine learning applications. The research aims to produce self-tuning optimization algorithms with rigorous guarantees to reduce wasteful computation required by current...
This $174,995 Project Grant awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program supports research to understand and optimize the role of human intelligence in data integration and discovery pipelines, especially in the context of emerging large language models (LLMs) like ChatGPT. The project will investigate fundamental questions about human involvement in these data processes, uncover relevant human biases, and...
The National Science Foundation awarded a $600,000 Project Grant under its Computer and Information Science and Engineering program (CFDA 47.070) to the University of Florida to support research on the design and analysis of recursive algorithms with applications in machine learning, optimization, and reinforcement learning. The research aims to develop new techniques to ensure stability and accelerate the convergence of stochastic approximation algorithms, which are critical to training...
The National Science Foundation awarded a $600,000 Project Grant to Princeton University under the Computer and Information Science and Engineering program (CFDA 47.070). The grant will support research toward developing a mathematical foundation for deep reinforcement learning over the period from October 1, 2022 to September 30, 2026. Specifically, the project aims to bridge current gaps in theoretical reinforcement learning and deep neural networks by investigating guarantees achievable by...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Award (CFDA 47.070) provides $122,000.00 to the Massachusetts Institute of Technology (MIT) from June 1, 2025 to May 31, 2030 to develop new mathematical tools and techniques for analyzing sampling algorithms used to manipulate and understand complex high-dimensional probability distributions. The research will focus on three foundational problems in theoretical computer science, with the...
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...