Machine learning (ML) is rapidly permeating the numerical and natural sciences. The plethora of newly available approaches and methods is overwhelming; the research body is highly dynamic and heterogeneous. In this interactive Research Frontiers Workshop, we aim to extract and structure the often-hidden fundamental concepts that are behind the design or usage of methods in ML. It shall foster reflection and debate on how we can use ML in science, critically questioning which developments will likely live up to their expectations, and which bring the most potential for new, interdisciplinary ideas. It is essential to regard these developments from different points of view, which is why we aim to bring together different fields ranging from physics to engineering and philosophy of science/ AI.
Meet our keynote speakers:
Hoshin Gupta, University of Arizona
Ana Lučić, University of Amsterdam
Florian J. Boge, TU Dortmund University
Image: (c) Nadja Moutevelidis
Viola Priesemann, Georg-August University and Max Planck Institute for Dynamics and Self-Organization Göttingen
Image: (c) Jenna Dallwitz
Michael W. Mahoney, UC Berkeley
Emily Gordon, University of Auckland
Ramón Alvarado, University of Oregon
Karoline Wiesner, Potsdam University
Mathias Niepert, University of Stuttgart
Lina Jaurigue, TU Ilmenau
Image: (c) AnLi Photographie / TU Ilmenau
Sebastian J. Wetzel, Perimeter Institute
Oliver Buchholz, ETH Zurich
Funding
The workshop is funded by the Cluster of Excellence "Data-integrated Simulation Science (SimTech)", the German Research Foundation (DFG), the Cluster of Excellence “Machine Learning: New Perspectives for Science” and the Heidelberg Academy of Sciences and Humanities.
