Pierre Gentine

Keynote date: 9 June, 2026

Affiliation: Columbia University

Pierre Gentine is a Professor of Geophysics at Columbia University and Director of the NSF Science and Technology Center “Learning the Earth with Artificial Intelligence and Physics” (LEAP). His research focuses on the continental hydrologic cycle, land-atmosphere interactions, and extreme climate events, using machine learning, remote sensing, and high-resolution modeling. He investigates how rising CO₂ levels will alter droughts, precipitation extremes, and ecosystem responses. Gentine earned his engineering degree from SupAéro in Toulouse and completed his MSc and PhD in civil and environmental engineering at MIT. He is a recipient of multiple early-career awards from NASA, DOE, and NSF, and is an American Geophysical Union Macelwane Medalist.

Daniel Ruckert

“AI and Future of Medicine“

Keynote date: 10 June, 2026

Affiliation: Technical University of Munich

Daniel Rückert is Alexander von Humboldt Professor for Artificial Intelligence in Medicine and Healthcare at the Technical University of Munich and a Professor at Imperial College London. His research focuses on artificial intelligence and machine learning for medicine, with particular emphasis on developing innovative algorithms for biomedical image acquisition, analysis, and interpretation, as well as extracting clinically relevant information for computer-assisted diagnosis and prognosis. Rückert has made seminal contributions to image reconstruction, registration, segmentation, tracking, and modeling, and is internationally recognized for advancing AI applications in healthcare. He has received numerous honors, including the Gottfried Wilhelm Leibniz Prize (2025), Fellowship of the Royal Society (2025), the MICCAI Enduring Impact Award (2024), and the Alexander von Humboldt Professorship (2020).

Cordelia Schmid

“Multimodal video understanding & vision-language guided robotics“

Keynote date: 11 June, 2026

Affiliation: Inria, Google

Cordelia Schmid is a Research Director at Inria, France. Her research focuses on computer vision, machine learning and robotics. She is internationally recognized for pioneering contributions to visual recognition and representation learning. Schmid has received numerous honors, including the Inria-Académie des Sciences Grand Prix and multiple Longuet-Higgins Prizes. She is a member of the German National Academy of Sciences (Leopoldina) and continues to shape the field’s advancement in visual intelligence.