1. Introduction. 2. AI refresher. 3. Current and future applications of AI in Earth-related sciences. 4. AI and challenges in Earth-related sciences. 5. AI hardware and quantum computing. 6. Why believe AI? The role of machine learning in science. 7. Generative AI. 8. Causal models: AI that asks ‘why’ and ‘what if’. 9. Conclusion.
Biography
Michel Speiser is Chief Data Scientist at the International Centre for Earth Simulation (ICES Foundation) in Geneva, Switzerland. He strives to bring the advantages of AI and Machine Learning to bear on Earth Systems Modeling, Simulation & Visualization. He spent over six years at IBM Research, pushing the limits of data science, and unlocking the value hidden in large, complex data, drawing on techniques in probabilistic and statistical modeling, Machine Learning and Data Mining, and developing new tools and methods as needed. Michel holds a PhD in Information Systems and Operations Research (ETH Zurich), and Master’s degrees in Computer Science (EPFL), Complex Systems (Chalmers University of Technology), and Mathematical Sciences (EPFL).
