Leopoldina - National Academy of Sciences
Founded in 1652, the Leopoldina is one of the oldest academies of science in the world. It is dedicated to the advancement of science for the benefit of humankind and to the goal of shaping a better future. With some 1,500 members, the Leopoldina brings together outstanding scientists from Germany, Austria, Switzerland and many other countries.
Young, excellent and motivated - Jonas Peters has been elected as one of ten new members to the "Junge Akademie" and will contribute to the interdisciplinary work of this organization. Congratulations!
Excellent doctoral dissertation
Dr. Jakob Zscheischler is to receive this year’s Wladimir Peter Köppen Award. The Cluster of Excellence CliSAP selected the mathematician for his excellent doctoral dissertation submitted at the Swiss Federal Institute of Technology Zurich (ETH) in 2014. His work was rated trendsetting by the jurors who found its thematic and methodical approach particularly original. Jakob Zscheischler completed his dissertation in Germany at the German Max Planck Institute for Biogeochemistry in Jena and the Max Planck Institute for Intelligent Systems in Tübingen.
2nd prize at the "Fast Forward Science 2015" Competition
The movie "Light gets on your nerves" was financed and coordinated by the Max Planck Society and pictures the research of the Brain-Computer-Interfaces group at our institute.
MLSS 2015 Tübingen
The 4th MLSS at Tübingen welcomes more than 110 participants, bringing together 35 nationalities from 19 different countries.
Probabilistic Numerical Methods assign Uncertainty to Deterministic Computations
With a new approach, Scientists of the Max Planck Institute for Intelligent Systems aim to make numerical algorithms more efficient. During the next five years, this research project will be supported by the Emmy-Noether-Programme of the German Research Foundation (DFG) with nearly a million Euros. The applicant Dr. Philipp Hennig prevailed in a competitive process. With the start of two new PhD students in April this Emmy Noether Group takes up its research activities.
In machine learning, we use data to automatically find dependences in the world, with the goal of predicting future observations. Most machine learning methods build on statistics, but one can also try to go beyond this, assaying causal structures underlying statistical dependences. The hope is that this also allows prediction in certain situations where systems change, for instance by interventions.