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AI

Geoscience AI at the Jackson School

AI Across Earth and Planetary Science

Jackson School researchers have long used machine learning to address questions across the geosciences, and a growing group of faculty now makes AI central to their work.

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Research here spans the entirety of the geosciences — from solid Earth, to water and ice, to the atmosphere, all the way to other planets and moons.

Machine learning and AI are changing how this research is done, and Jackson School researchers are developing methods to make new discoveries in each of these areas. The school supports this work with a dedicated computational science team, a graduate certificate, and a new series of AI focused events.

Research

Where AI meets Earth science.

  • Subsurface Imaging, Interpretation & Quantum Computing

    Neural networks detect faults, characterize reservoirs, and identify patterns in sparse subsurface data. Researchers are also designing inversion algorithms for quantum computers.

  • Earthquake & Hazard Modeling

    Graph neural networks and data from real-time seismic networks speed up simulations of earthquake cycles and ruptures and support hazard assessment.

  • Digital Twins & Data-Driven Simulation

    AI-powered replicas of real systems, such as cities and coastlines, let researchers explore “what if” scenarios in real time.

  • Hydrology & Remote Sensing

    Hybrid models that combine physics and machine learning improve streamflow, flood, and groundwater predictions while preserving physical understanding of the systems. Machine learning applied to satellite data improves estimates of water storage.

  • Glaciers, Ice & Sea Level

    Machine learning maps glacier termini in satellite imagery and helps forecast how ice sheets and sea level will respond to a changing climate.

  • Community & Ecosystem Resilience

    Knowledge-guided AI integrates remote sensing, ground observations, and Earth system models to assess wildfire and hydroclimatic risks, understand ecosystem functioning, and inform strategies that strengthen community and ecosystem resilience.

  • Energy, Earth Resources & Coupled Subsurface Processes

    AI methods accelerate modeling of interacting thermal, hydrological, biogeochemical, and geomechanical processes. Applications span geothermal energy, reservoir simulation, well-log analysis, carbon cycling and storage, greenhouse gas emissions, and environmental and geohazard risk assessment.

  • Climate, Weather & Cities

    AI-driven tools translate climate and weather data into actionable information, from heat-vulnerability mapping to microclimate models for marathon routes.

Academics

Strengthen your geosciences education with machine learning.

The graduate certificate in Machine Learning and Data Analytics in Geosciences (opens in new tab) teaches students how to use modern data analytics tools and machine learning to solve Earth science problems involving large volumes of data, such as climate modeling, seismic imaging, earthquake modeling, and satellite mapping.

Courses in the certificate include

  • GEO 396D.1 Introduction to Machine Learning in the Geosciences (opens in new tab)
  • GEO 392P Python for Geoscience Research and Data Analytics
  • GEO 396D.2 Applications of Data Analysis, Visualization, and Machine Learning
  • GEO 396D.3 Data Analytics and Geostatistics
  • GEO 396D.4 Subsurface Machine Learning
  • GEO 396D.5 Machine Learning Research, Advanced Topics and Capstone Research Project
  • GEO 393D 3D Analysis of Volumetric Data

Other ways to get involved

Geospatial and Geographic AI Courses at UT

  • GRG 327G/CS 378 Introduction to Geospatial Artificial Intelligence
  • GRG 356T Geospatial Semantics and Geo-Text Mining
  • GRG 396T Graduate-Level Seminar in GeoAI
  • GRG 460G Environmental GIS
  • GRG 356T Spatial Data Science and Maps
  • GRG 356T Generative AI in a Geospatial World
  • GRG 396T Spatial Data Science and GeoAI
UT Resources

Collaborators and resources at UT Austin

The Jackson School has strong ties to the Texas Advanced Computing Center (opens in new tab) and Oden Institute for Computational Engineering and Sciences (opens in new tab). These partnerships give students and researchers access to high-performance computing, specialized expertise, and opportunities for collaboration.

Partner centers and groups

UT is pioneering the future of artificial intelligence (opens in new tab)

All University of Texas at Austin students and faculty members have access to UT Sage (opens in new tab), an AI tutor and virtual instructional designer that supports the responsible use of generative AI in teaching and learning.

Other UT resources and policies

Individual Researchers

Researchers using AI and machine learning in their work.

News

AI news from the Jackson School.

Easily Overlooked Small Wetlands Are a Big Source of Global Methane

Water-logged land areas such as marshes, bogs and fens are the world’s largest natural source of methane. Even the smallest of wetlands emit this powerful…

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Data Centers Are Growing in Texas, But Big Questions Remain About Water Use

Data centers could potentially account for 3% to 9% of Texas’ water use by 2040, according to a new white paper from The University of Texas at Austin that recommends greater…

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News

Fa Li Brings AI Expertise to Jackson School Faculty

Fa Li, who uses artificial intelligence to study how ecosystems on the land respond to shifts in the climate and water cycle, joined the Jackson…

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News

Dapeng Feng Joins Jackson School Faculty in AI Cluster Hire

Dapeng Feng, a hydrologist exploring the Earth’s water and its interactions with the environment, has joined the Jackson School of Geosciences Department of Earth and…

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AI and Computing Support

Help with your project.

The Jackson School has a dedicated team of computational scientists with expertise in AI and machine learning. The team works with faculty, researchers, and students on code development, model training, and use of high-performance computing resources at TACC. The team is growing; see the open position.

Want to stay in the loop on all things AI at the Jackson School?

Sign up for the Jackson School's AI mailing list (opens in new tab)

Questions about AI and computing

Thorsten Becker

Special Advisor to the Dean on AI & Computing

twb@ig.utexas.edu