Project Grant 2551976
- The National Science Foundation Division of Information and Intelligent Systems awarded Syracuse University $350,000 on August 1, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) to develop algorithm-design-technology co-optimization frameworks for next-generation self-evolving implantable medical devices. The project establishes a cross-layer co-design framework jointly optimizing applications, learning algorithms, hardware architectures, and system-level...
- The National Science Foundation Division of Information and Intelligent Systems awarded the University of Notre Dame DU Lac $349,281 on August 1, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) for collaborative research on algorithm-design-technology co-optimization for next-generation self-evolving implantable devices. The project develops a cross-layer co-design framework that jointly optimizes applications, learning algorithms, hardware architectures,...
- The National Science Foundation Division of Information and Intelligent Systems awarded the University of Massachusetts $430,468 on July 15, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) to develop neuromorphic wearables for continuous neurophysiological monitoring outside clinical settings. The research develops brain-monitoring wearables that capture the full spectrum of brainwave signals, including high-frequency components during motion, and operate...
- The National Science Foundation Division of Information and Intelligent Systems awarded Regents of the University of Michigan $800,000 on September 1, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) to develop a neuro-symbolic framework for hardware-software co-design of specialized computing accelerators. The project combines artificial intelligence pattern-finding methods with mathematical proof techniques to explore large design spaces for accelerator...
- The National Science Foundation Division of Information and Intelligent Systems awarded $400,000 to the Regents of the University of Michigan on September 1, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) for collaborative research on neuro-AI foundations for long-range dependency tasks. The project develops spiking neural networks (SNNs) that efficiently handle long-range dependencies and generative tasks in edge-based AI systems by reconceptualizing SNNs...
- The University of Notre Dame received a two-year, $120,000 Project Grant from the National Science Foundation's Technology, Innovation, and Partnerships program to develop next-generation, self-evolving implantable medical devices. Through the award ending April 2025, the university will research cross-layer co-design approaches allowing dynamic adjustment of detection algorithms and hardware configurations in implantable devices based on individual patient data and circumstances. The goal is to...
- The National Science Foundation Division of Electrical, Communications and Cyber Systems awarded Rochester Institute of Technology $514,145 on May 1, 2026, under the NSF Engineering program (CFDA 47.041) to develop ionically gated transistors that combine memory and processing within a single material for energy-efficient artificial intelligence on edge devices. The research establishes the fundamental science and engineering of a dual-mode ionically gated transistor functioning as a...
- This $666,667 Project Grant from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CFDA 47.070) program aims to develop innovative mathematical algorithms to enable safe automated patient monitoring, treatment guidance, and reconciliation of potentially conflicting medical treatments. The research will advance control theory, inference, and optimization to create new knowledge, leading to transformative approaches for coordinating complex interacting...
- This $317,591 federal Project Grant awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will fund research to enhance personalized healthcare through the use of large language models (LLMs) and novel memory semiconductor devices. The project aims to develop efficient retrieval-augmented generation (RAG) techniques for LLM personalization, focusing on reducing latency and hardware overhead through algorithm-hardware...
- The National Science Foundation (NSF) awarded a $900,000 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to Arizona State University's Orspa division. The funding will be used to expand the application of electronic design automation (EDA) tools, traditionally used in microelectronics, to biomechanical devices such as implantable valves. The project aims to develop equivalent circuit models and leverage finite element analysis to rapidly explore...
The National Science Foundation Division of Information and Intelligent Systems awarded The Research Foundation For The State University Of New York $299,998 on August 1, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) to develop algorithm-design-technology co-optimization frameworks for next-generation self-evolving implantable medical devices. The project creates adaptive implantable devices—including pacemakers, implantable cardioverter defibrillators, deep brain stimulators, cochlear implants, and sleep apnea implants—that automatically adjust to changing patient physiological needs while operating within strict constraints on size, power, and battery life. The work establishes a cross-layer co-design framework jointly optimizing applications, learning algorithms, hardware architectures, and system-level operation. Research is organized into five integrated tasks across two phases. Phase one explores device requirements, develops lightweight state-space models for physiological signal analysis, introduces uncertainty-aware safety mechanisms, and designs energy-efficient in-memory-computing architectures. Phase two advances adaptive model updating, uncertainty-triggered evolution, hardware reconfiguration, and algorithm-architecture co-evolution. Investigations include structured state-space models, adaptive quantization, Bayesian confidence estimation, processing-in-memory architectures, fault tolerance techniques, and reinforcement learning-based optimization. Work is performed in Buffalo, New York, with a period of performance from August 1, 2026, through July 31, 2030. This is a Project Grant.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $300.0k | 7/29/26 |