We are currently witnessing a broad adoption of methods from artificial intelligence across many disciplines of exact and applied sciences. These new approaches, which are based on probabilistic data analysis or implicit knowledge representations, challenge and transform traditional scientific practice in fields ranging from physics via chemistry and biology all the way to geography and robotics.

The aim of this interdisciplinary symposium is to discuss how the core of scientific practice might be revolutionised through the adoption of these new methods. Through talks of a small number of distinguished researchers in each field and a public discussion session with members of the scientific community and representatives from the industry we hope to set a common ground for the future of AI methods in the sciences.

Invited Speakers
  • Anima Anandkumar Caltech & NVIDIA
  • Costas Bekas IBM Zurich
  • Abraham Bernstein UZH
  • Michael Bronstein Imperial College / USI Lugano / Twitter
  • Kyle Cranmer NYU
  • Giacomo Indiveri UZH & ETHZ
  • Sofia Olhede EPFL
  • Lenka Zdeborova Paris - Saclay
Sebastian D. Huber (ETH Zurich), Titus Neupert (University of Zurich), Mark H Fischer (University of Zurich), Maciej Koch-Janusz (ETH Zurich)
Program Advisory Committee
Joachim Buhmann (ETH Zurich), Markus Reiher (ETH Zurich),