Announcing ESSIC’s 1st AI/ML Workshop: On the Pathway to a Digital Earth

The rapid growth of Artificial Intelligence (AI) and Machine Learning (ML) has brought tremendous opportunities to advance knowledge in earth science, most prominently by enabling novel approaches to existing problems. For example, spectroscopic instrument design and data retrievals can be informed by ML-based spectral fitting methods. Earth System models can substitute ML models for prohibitively expensive full-physics simulations. Flood, landslide, and famine risk can be assessed using remote sensing images with ML approaches for classification, detection, and regression. Recent work applying AI/ML techniques to Earth science problems has demonstrated its promise, and there are still many challenges and opportunities to be addressed through multi-disciplinary teams of AI/ML and Earth science researchers.


To embrace the rapidly evolving field, ESSIC presents the two activities. The first is the ESSIC AI Forum, a platform for ESSIC and partner scientists to foster novel research while connecting to inter- and cross-disciplinary AI/ML communities on campus and beyond. The other is the one-day AI-ML workshop on September 22, 2021.


The workshop, “On the Pathway to a Digital Earth”, will bring together researchers from the NASA Goddard Space Flight Center (GSFC) and the University of Maryland (UMD) to present highlights of their work on AI/ML and Earth Science applications as well as their needs and ideas for possible future developments. Discussions will center on current state-of-the-art ML techniques, successful examples of ML applications (both scientific and operational) as well as opportunities for and barriers to collaboration. The workshop will include plenary talks, a panel session, and breakout sessions on topics bridging the participants’ diverse area of expertise and topics of interest within AI/ML for Earth Sciences.


ESSIC Director Ellen Williams leads the overall effort by closely working with the NASA GSFC leadership and colleagues. At UMD, Kayo Ide (AOSC/ESSIC/IPST/MATH), Julie Nicely (ESSIC/GSFC), Hannah Kerner (GEOG SCI), David Jacobs (CS/UMIACS), Ramani Duraiswamy (CS/UMIACS), serve on the Organizing Committee.


The organizers are calling for abstract submissions from practitioners of AI/ML as well as those with a candidate Earth science-relevant problem to which AI/ML techniques could be applied. Lightning talks and possible poster presentations, pending demand, will be assigned and organized by breakout group topics, including but not limited to:

    • Satellite retrieval, data acquisition, and data processing
    • Solutions that serve society with established stakeholders
    • Land cover and land use change analysis
    • Modeling, simulation, and hybrid approaches
    • Mitigating the training data bottleneck


To learn more about ESSIC-AI and “On the Pathway to a Digital Earth”, click here:


To submit an abstract, click here: