This $170,992 Project Grant award from the National Science Foundation's (NSF) Social, Behavioral, and Economic Sciences (CFDA 47.075) program supports a collaborative research effort led by Brown University to develop AI-based tools for conducting continental-scale archaeological surveys. The key products and services to be delivered under this 3-year award (Aug 2024 - Jul 2027) include: Developing new deep learning models to automatically identify abandoned archaeological structures in...
This $138,559 National Science Foundation Project Grant supports the development of machine learning methods to automatically detect archaeological features of varying sizes as well as anthropogenic landscape modifications in light detection and ranging (LIDAR) data from tropical regions. Awarded on August 1, 2022 to the University of Nebraska with a completion date of July 31, 2024, this grant falls under the NSF's Social, Behavioral, and Economic Sciences program (CFDA 47.075). An...
This $207,737 federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will fund research to develop a new class of machine learning models called "Programmatic Foundation Models" that can efficiently analyze large-scale satellite, aerial, and ground imagery. The goal is to create interpretable, robust AI models that can understand global and local phenomena from images, providing insights...
This $141,318 National Science Foundation award under the Social, Behavioral, and Economic Sciences program will fund collaborative research to reconstruct the landscape of one of the earliest cities in the United States. The researchers will conduct a high-resolution magnetometry survey covering over 5.5 sq km of the urban landscape, making it the largest such subsurface survey ever performed in the Americas for an archaeological site. This near-total geophysical survey of the subsurface will...
This $589,708 Project Grant award from the National Science Foundation's Geosciences program (CFDA 47.050) supports research to advance artificial intelligence (AI) methods for imaging and monitoring the Earth's subsurface. The project aims to develop a multi-task deep learning inversion framework that can simultaneously estimate subsurface velocity structures and earthquake source parameters using passive seismic data. By integrating deep learning with conventional full-waveform inversion...
This Project Grant award of $236,131 from the National Science Foundation's (NSF) Social, Behavioral, and Economic Sciences (CFDA 47.075) program supports a comprehensive archaeological study of early human settlements in rural settings. The research, conducted by Emory University, aims to examine the relationship between imperial settlement policies and local community dynamics, with a focus on agricultural organization, production, and the interaction between rural communities and the...
This $313,226 National Science Foundation project grant will fund collaborative research to reconstruct the landscape of one of the earliest cities in the United States through non-invasive archaeological techniques. The awardee, Colorado State University, will perform high-resolution magnetometry surveys covering over 5.5 square kilometers to map buried archaeological features across the entire urban landscape. This will be the largest such geophysical survey ever conducted in the Americas on...
This $213,247 Project Grant from the National Science Foundation's Division of Behavioral and Cognitive Sciences under the Social, Behavioral, and Economic Sciences program (CFDA 47.075) will fund research to advance understanding of how wear patterns form on stone tools and facilitate identification of worked materials. An interdisciplinary team of archaeologists and engineers will conduct controlled tribological experiments rubbing surrogate and organic materials against stone bits to generate...
This two-year, $148,000 National Science Foundation project grant supports modeling of long-term urban and rural settlement dynamics through the Social, Behavioral, and Economic Sciences program (CFDA 47.075). The grant recipient will conduct archaeological and geospatial analyses to develop a predictive rural site distribution model and targeted survey of an urban hinterland in order to refine global urbanism models. Specifically, the recipient will use low-cost aerial and satellite imagery...
This $100,000 Project Grant awarded by the National Science Foundation's (NSF) Biological Sciences (CFDA 47.074) program will fund Cornell University to develop and validate an AI framework that can use a broad array of image data, such as satellite, drone, and internet-posted images, to automate and accelerate the generation of interpretable environmental science hypotheses at a planetary scale. The framework will integrate new techniques into foundational models for satellite imagery that...