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The Ohio State University's interdisciplinary center for applied AI in the College of Arts and Sciences — with an initial focus on Earth observation and environmental monitoring.

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$1M Seed Funding
~30 Affiliated Faculty
6 Research Themes

Our Mission

Earth observation satellites now generate ~100 TB of data per day — spanning, among others, optical, radar, gravity, magnetic, thermal, LiDAR, and microwave sensors. Traditional analyses cannot scale to these volumes or fully exploit multi-modal inputs. Across the natural and mathematical sciences, AI is the frontier technology for turning massive observational archives into discovery.

The BuckAI Observatory catalyzes AI-driven research across the College of Arts and Sciences (ASC) at The Ohio State University. While Earth observation is our primary focus, the Observatory welcomes researchers across the natural and mathematical sciences — from astronomy and mathematics to ecology and geography — who are pushing the frontier of AI applied to large scientific datasets. We provide shared GPU infrastructure, professional data engineering support, and a vibrant interdisciplinary community, lowering the barriers for faculty and students to harness modern machine learning in their research.

Build Community

Connect scientists across the natural and mathematical sciences — Earth scientists, ecologists, astronomers, mathematicians, and AI experts — before funding calls emerge, to establish durable collaborative research teams.

Shared Infrastructure

Multi-GPU nodes on ASC's Unity HPC cluster, petabyte-scale managed data storage, professional data engineering, and dedicated AI visualization space in Mendenhall Laboratory.

Advance AI for Science

Develop foundation models and novel AI algorithms for large scientific datasets — from petabyte satellite archives to massive astronomical surveys and high-dimensional numerical simulations.

Train the Next Generation

AI certificate programs, graduate courses, coding boot camps, workshops, and an undergraduate labeling pool to build a pipeline of AI-ready scientists.

Research Themes

Six interconnected themes anchor BuckAI's applied AI research program.

Hydrology & Water Resources: AI tools for river mapping, discharge estimation, and flood dynamics from commercial and open satellite imagery, spanning Arctic streams to the Amazon floodplain.
Coastal & Marine Systems: Physics-informed neural networks for shallow-water bathymetry, sea-level change from GRACE and altimetry, coral reef monitoring, and wetland carbon dynamics.
Forests & Ecosystems: Satellite-based deforestation tracking, forest carbon stock estimation, biodiversity modeling, and agroforestry mapping — with active projects in Sub-Saharan Africa.
Cryosphere & Climate: Ice sheet dynamics, glacier mass balance, mountain water resources, and snow remote sensing — quantifying Earth's frozen reservoirs in a warming climate.
Geodesy & Subsurface: Satellite geodesy, gravity missions, GPS seismology, and AI prospecting for natural hydrogen reservoirs — bridging space observation and subsurface energy resources.
AI Methods & Scientific Computing: Developing and advancing the AI algorithms themselves — scientific machine learning, uncertainty quantification, self-supervised foundation models, and ML-enhanced numerical methods for large scientific datasets.

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