معرفی
Lynn Kaack is an Assistant Professor of Computer Science and Public Policy at the Hertie School in Berlin. Her research focuses on applying machine learning and statistical methods to inform climate mitigation policy in the energy sector and AI policy related to climate action. She co-founded and chairs Climate Change AI, an organization advancing machine learning applications for climate solutions. Previously, she was a Postdoctoral Researcher and Lecturer at ETH Zürich’s Energy Politics Group. She holds a PhD and Master’s in Machine Learning from Carnegie Mellon University and degrees in Physics from the Free University of Berlin.
Education:
- PhD in Engineering and Public Policy, Carnegie Mellon University
- Master’s in Machine Learning, Carnegie Mellon University
- MS and BS in Physics, Free University of Berlin
Research Interests: Her work bridges computer science and public policy, emphasizing data-driven approaches for climate policy design. Key areas include energy system decarbonization, AI ethics in environmental governance, and scalable solutions for urban sustainability. She develops tools to analyze policy text, monitor transport emissions, and model building energy efficiency at city scales.
Key Contributions: Kaack leads the Horizon Europe project AI-EFFECT and contributes to initiatives like the POLIANNA dataset for policy design analysis. Her work on spatiotemporal machine learning for urban traffic and solar panel detection exemplifies her focus on actionable climate data science.
Awards: No specific awards listed, though her impactful contributions to Climate Change AI and policy-relevant research are notable.
Teaching & Leadership: Teaches courses on Deep Learning and AI & Climate Change at the graduate level. Serves as faculty advisor for the Hertie School’s Climate Policy initiatives and collaborates with global institutions on sustainability projects.
