Fragile Earth 2023

Background Info

Since 2016, the Fragile Earth Workshop has brought together the research community to find and explore how data science can measure and progress climate and social issues, following the framework of the United Nations Sustainable Development Goals (SDGs). Over the years, Fragile Earth workshop has focused on SDGs. This year we also focus on two other aspects, Environmental Justice and Planetary Health. Environmental Justice can be defined as the effort to “document and redress the disproportionate environmental burdens and benefits associated with social inequalities” (Chakraborty et. al 2016), as well as SDG 13: Climate Action. Planetary Health involves complex spatial–temporal interactions. Various methods in earth data analytics, including spatial–temporal statistics, spatial evolutionary algorithms, remote sensing image analysis, wireless geo-sensors, and location-based analytics, are emerging disciplines in understanding complex interactions in planetary health. 

The application problems and agenda of interest include the Sustainable Development Goals, accelerating progress on the United Nations’ 2030 agenda, envisioning solutions for climate mitigation and adaptation, and measuring and diminishing the inequitable benefits and burdens across socioeconomic groups. In particular, the workshop has maintained a strong focus and community in the following areas: food security, sustainable agricultural practices and supply chains, ecosystem restoration, water management, sustainable energy, climate action and adaptation, socioeconomic equality, and resilience across a broad range of natural disasters such as wildfires, storms, and hurricanes. Fragile Earth Workshop invites ML and AI researchers, social and behavioral scientists, as well as natural scientists and engineers, to convene and discuss interdisciplinary solutions for progress towards

List of Topics

The Workshop will target both methodological and applied research agenda within these areas of investigation.

• The methodological topics of interest are relevant areas of KDD, including but not limited to:
  • the integration of physics into data-driven modeling and the use of machine learning to enhance physical simulations 
  • model explainability, uncertainty quantification, privacy and fairness questions in environmental modeling 
  • integration of symbolic and neural machine learning for accurate and interpretable models
  • causal learning in complex physical world as foundations for model trustworthiness 
  • ML applications at low-energy edge devices
  • frameworks for helping the scientific and KDD communities to work together 
  • combining predictive and prescriptive tasks
  • multi-agent systems for participatory modeling that integrate stakeholders into knowledge creation and decision processes
  • geometric and topological deep learning for environmental modeling and assessment of environmental justice 
    
    
• Domains of interest include but are not limited to:
  • food security, sustainable agricultural practices and supply chains, ecosystem restoration, water management, sustainable energy, climate action and adaptation, socioeconomic equality, and disaster resilience
  • wildfire analytics: detection, prediction, and discovery; wildfire smoke and environmental fairness
  • innovations in data science and predictive modeling, applied to earth sciences 
  • investigations centering sustainability, including but not limited to environmental justice
  • data-informed climate change and resource management policy discussions
  • carbon removal technologies
  • easily usable and publicly available data+model+frameworks (possibly challenge problems) based on satellite/drone data  to monitor and predictively model the fragile earth
  • natural catastrophes under a changing climate ranging from improved modeling to development of resilient infrastructures
  • economic/quantitative characterization of climate change risk and associated incentives towards policy/decision making.

• Any other topics related to the themes of the workshop are welcome!