Project Grant 2313481
- The National Science Foundation (NSF) awarded a $125,000 Project Grant under its Biological Sciences program (CFDA 47.074) to The General Hospital Corporation, doing business as Massachusetts General Hospital (MGH), for a collaborative research project titled "EAGER: Deep Learning-Based Multimodal Analysis of Sleep." The two-year project aims to develop a multimodal machine learning approach to simultaneously monitor and process electroencephalogram (EEG) data and animal behavior...
- This Project Grant from the National Science Foundation's $150,000 Biological Sciences program (CFDA 47.074) supports research from October 1, 2022 to September 30, 2026 to translate insights from sleep biology to improve continual learning in artificial neural networks. The University of California San Diego will study multi-phasic sleep patterns across the honeybee brain using electrophysiological experiments. This will inform computational models of sleeping neural networks to enhance deep...
- This $850,000 Project Grant award, funded jointly by the National Science Foundation's (NSF) Division of Integrative Organismal Systems and Division of Information and Intelligent Systems under CFDA 47.070 Computer and Information Science and Engineering, supports research to understand how sleep and memory are connected in the brain. The project will use long-duration, high-resolution recordings of neuronal activity to observe changes in synaptic connections during sleep and memory tasks,...
- This National Science Foundation Project Grant of $255,851 awarded on September 15, 2022 will support the development of a neuromodulation device to promote healthy sleep cycles through the completion of prototype engineering. The awardee, Neurolight Inc. of Suffern, New York, will utilize controlled light and sound stimuli delivered via an externally worn system to transpose normal brain wave patterns associated with desired sleep states into recipients suffering from sleep disorders. This aims...
- This is a Project Grant awarded by the National Science Foundation (NSF) Division of Information and Intelligent Systems under the Computer and Information Science and Engineering program (CFDA 47.070). The $299,708 grant, with a period of performance from August 15, 2023 to July 31, 2027, supports collaborative research to develop AI-driven radio frequency identification (RFID) sensing techniques for smart health monitoring applications. The research aims to create more affordable, comfortable,...
- The National Science Foundation (NSF) Biological Sciences program awarded a $124,997 project grant to the University of Massachusetts Boston from October 1, 2023 to September 30, 2025. The grant supports the development of a multimodal machine learning method to simultaneously analyze electroencephalogram (EEG) data and animal behavior data to study group behavior, particularly sleep patterns. The project aims to create a "dictionary" of animal movements and behaviors and incorporate...
- This National Science Foundation (NSF) Social, Behavioral, and Economic Sciences (CFDA 47.075) Project Grant award provides $160,000 in funding to support a postdoctoral fellowship investigation into how sleep facilitates the integration of new and existing memories. The goal is to understand the brain mechanisms that enable this integration process, which is critical for building knowledge from new information encountered in daily life. The study will use electroencephalography (EEG),...
- This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $174,740 to the University of Texas at Tyler to enhance the integration of deep learning models for the detection and monitoring of cardiac conditions from electrocardiogram (ECG) data. The project aims to address key challenges in the real-world clinical application of deep learning for ECGs, such as data scarcity for rare conditions,...
- This $500,000 Project Grant award from the National Science Foundation's Division of Mathematical Sciences supports the development of novel deep learning techniques for interpretable survival analysis of complex longitudinal healthcare data. The project aims to create a unified deep learning model that can effectively analyze multi-modal data, such as text, images, and lab values, collected at irregular intervals to predict patient outcomes. Key objectives include providing a unified feature...
- This federal Project Grant award, valued at $678,710 and awarded on June 15, 2025, was provided by the National Heart, Lung, and Blood Institute under the Cardiovascular Diseases Research program (CFDA 93.837). The award supports the development and validation of a novel multi-sensor machine learning approach to precision sleep tracking for nightshift workers. The project aims to leverage wearable devices, environmental sensors, and machine learning algorithms to accurately detect sleep patterns...
This two-year, $200,000 project grant from the National Science Foundation's Computer and Information Science and Engineering program (CFDA 47.070) will support the development of interpretable deep learning methods and software for automated sleep phenotyping using multimodal health sensing data. Beth Israel Deaconess Medical Center will leverage polyssomnography data and novel radio frequency sensing techniques to build accurate deep learning models for classifying sleep stages and apnea events. Researchers will develop adversarial deep learning approaches for modeling radio frequency signals and leverage historical polysomnography data to improve models for radio frequency data. Interpretable models incorporating medical knowledge of sleep phenotypes will be created. All proposed models will be validated through a prospective clinical study assessing the feasibility of automated sleep studies using radio frequency data. The research team plans to release open-source software and large datasets to benefit the computer science, engineering and medical communities.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $200.0k | 2/7/23 |