Abstract: Climate change represents one of the most pressing challenges of our time, demanding innovative solutions that can operate at global scale. Machine learning (ML) offers powerful tools to address these grand challenges, from predicting extreme weather events to optimizing renewable energy systems and modeling the complex dynamics of Earth’s climate.
In this talk, Dr. Saket Anand and Dr. Sai Ravela from MIT will explore how ML can be harnessed to confront climate challenges with scientific rigor and practical impact. The session will highlight the role of data-driven models in advancing climate science, while also emphasizing the importance of integrating domain knowledge to ensure reliability and interpretability.
Key themes will include:
Applications of ML in climate modeling, forecasting, and risk assessment.
Leveraging AI for sustainable energy, resource management, and environmental monitoring.
Challenges of data scarcity, uncertainty, and the need for robust, trustworthy models.
Interdisciplinary approaches that combine machine learning with physics, engineering, and policy.
The presentation will showcase case studies and ongoing research that demonstrate how ML can accelerate progress toward climate resilience. By bridging cutting-edge AI with urgent environmental needs, the speakers will illustrate how technology can play a transformative role in addressing the climate grand challenges of the 21st century.