The first workshop on machine learning for environmental sustainability (co-located with 5th Asian Machine Learning Conference-ACML) invites high quality original research papers on machine learning and data mining applications for environmental sustainability from anywhere in the world. This workshop aims to bring machine learning and data mining researchers and experts in the environmental domain together to tackle challenges towards environmental sustainability.

Environment sustainability related areas can include(but not limited to):

Energy, utilities, transport and infrastructure
Industry and government
Environmental pollution, hazards and health
Disaster and natural calamity
Carbon emissions and climate change
Food and biosecurity
Natural resources management
Precision farming

Goals: Balancing the needs of the environment, society and the economy is critical as we face global challenges associated with energy demand, transport, rapid urbanization, industrialization and climate change. Addressing these challenges requires multi-disciplinary research and AI is a discipline that can assist in solving these challenges. Machine learning and data mining can play a significant role in discovery, modeling and prediction of ill-posed, complex systems.

The workshop invites submissions associated with novel algorithms, discoveries, models and concepts that address environmental sustainability challenges. The workshop also aims to bring together computational scientists with domain scientists in order to tackle environmental sustainability issues.