Project Grant FA23862214034

This $1.2 million project grant from the National Science Foundation's Computer and Information Science and Engineering program will fund research at the Massachusetts Institute of Technology to develop new techniques for interactive machine learning with rich feedback. Over a three-year period from September 2022 to August 2025, the grantee will pursue three objectives: establishing a framework for grounding complex feedback using simple supervisory signals; creating algorithms allowing...

This Project Grant from the National Science Foundation's $524,474 Computer and Information Science and Engineering program will support the development of artificial intelligence systems capable of understanding general real-world tasks and providing step-by-step visual and language guidance to solve complex problems. Over a three-year period from June 2022 to May 2025, researchers at the University of Minnesota will create a new dataset annotating diverse everyday tasks and solutions,...

Articulate.ai Inc. received a $256,000 National Science Foundation Project Grant under the NSF Technology, Innovation, and Partnerships program to develop adaptive dialog systems as second language learning partners. The grant will fund an innovative effort to integrate state-of-the-art artificial intelligence technologies into conversational systems for language education. Key deliverables include user-adaptive algorithms and datasets for dialog policy training on language learning tasks. The...

The National Science Foundation (NSF) awarded a $270,000 EAGER (Early-Concept Grants for Exploratory Research) grant to the Massachusetts Institute of Technology (MIT) to develop an Artificial Intelligence (AI) or Large Language Model (LLM)-powered conversational tutoring system for Quantum Information Science and Engineering (QISE). The project, titled "TRUSTWORTHY AND ETHICAL AI TUTORS WITH FIRST-PRINCIPLES/AXIOMATIC REASONING", aims to create an interpretable AI tutor, called...

This Project Grant award, totaling $413,700, was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program. The overarching goal is to develop scalable, example-based intelligent tutoring systems to enhance workforce upskilling and reskilling programs. The key products and services to be delivered include: Creating an "Exemplify" platform to help instructors develop example-based intelligent tutors for complex...

This three-year National Science Foundation project grant of $300,000 will fund research to advance trustworthy machine learning through bi-level optimization. The grantee, the University of California, Santa Barbara, will develop new algorithms and computational methods to achieve robust and fair deep learning. Specifically, the project will create a bi-level optimization framework for robust learning, defenses against adversarial examples and distribution shifts, and a full-stack robustness...

This three-year, $500,000 Project Grant from the National Science Foundation's Computer and Information Science and Engineering program will fund research at the University of California, Davis to develop trustworthy machine learning systems through adversarial robust reinforcement learning. Specifically, the award supports investigating potential vulnerabilities in reinforcement learning models and algorithms, developing robust RL approaches that mitigate impacts from adversarial attacks, and...

This $348,757 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports research to quantify social and affective cognition in humans and machines. The project aims to define objective measures for assessing the emotional understanding capabilities of large language models used in AI chatbots, in order to enable the development of more capable and safer conversational AI systems. Key aspects include...

This EAGER (Early-concept Grants for Exploratory Research) project, awarded by the National Science Foundation (NSF) under the Engineering program (CFDA 47.041), aims to create a personalized training framework that adapts to each worker's cognitive functions and sensorimotor skills in collaborative robotic manufacturing environments. The $299,953 grant, awarded on September 1, 2024, with a completion date of August 31, 2026, focuses on advancing personalized training strategies for complex...

This $349,683 Project Grant from the National Science Foundation's Computer and Information Science and Engineering program will fund the development of an AI coaching system to enhance surgical teamwork in cardiac operating rooms. Led by William Marsh Rice University, the grant supports the design of multimodal sensing hardware, data-driven algorithms, and an interface to model and computationally generate interpretable feedback and interventions improving teamwork. Researchers will develop a...