Speakers: Ryan Abernathey, PhD

Associate Professor and Physical Oceanographer at Columbia University and Lamont Doherty Earth Observatory

Picture of Ryan Abernathey, PhD


Ryan P. Abernathey, an Associate Professor of Earth And Environmental Science at Columbia University and Lamont Doherty Earth Observatory, is a physical oceanographer who studies large-scale ocean circulation and its relationship with Earth's climate. He received his Ph.D. from MIT in 2012 and did a postdoc at Scripps Institution of Oceanography. He has received an Alfred P. Sloan Research Fellowship in Ocean Sciences, an NSF CAREER award, The Oceanography Society Early Career Award, and the AGU Falkenberg Award. He is a member of the NASA Surface Water and Ocean Topography (SWOT) science team and Director of Data and Computing for a new NSF Science and Technology Center called Learning the Earth with Artificial Intelligence and Physics (LEAP). Prof. Abernathey is an active participant in and advocate for open source software, open data, and reproducible science. In 2016 he helped found the Pangeo project, an open science community focused on big scientific data analytics.

On the agenda

  1. Open and Collaborative Science

    Sep. 29, 10:00am Panel The Central Hub

    NASA has designated 2023 as the Year of Open Science. The shift to shared cloud data and services creates new opportunities for open, collaborative, and replicable science; accellerating the transition from research to application; and increasing transparency and confidence in science-based understanding.

    But a long path remains between the pricipals behind open science and FAIR (findability, accessibility, interoperability, and reusability) data and the actualization of this vision. The panelists will explore where we are on this journey and the path ahead.

  2. Analysis Ready, Cloud Optimized - The State of Formats and Services

    Sep. 29, 11:30am Panel The Central Hub

    This is an exciting moment for analyzing data at scale. We've seen commitments to host massive earth data archives on publicly accessible cloud infrastructure; investments in analysis ready data products; the evolution of new cloud-native data formats and tooling; and massive improvements in modeling, AI and other approaches to generating insights at speed and scale. This session will explore definitions and standards for Analysis Ready, Cloud Optimized data and what is required to produce and process this data.



  1. Amazon Web Services (AWS)

  2. Caribou Space

  3. Esri

  4. National Aeronautics and Space Administration (NASA)

  5. Picterra

  6. Planet

  7. Replicable AI for Microplanning (RAMP)

  8. SparkGeo

  9. United States Agency for International Development (USAID)


  1. Azavea

  2. Capella Space

  3. D4DInsights

  4. Element84

  5. European Space Agency (ESA)

  6. Locana

  7. PLACE

  8. Radiant Earth Foundation

  9. TileDB

  10. Umbra


  1. Cyient

  2. Development Seed

  3. DevGlobal

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