EAI & CSG Retreat 2023

The 2023 joint scientific retreat of the EAI Center & Computational Systems Genomics Group took place in Burghausen, Germany.

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EAI Retreat 2022

In November 2022, an EAI scientific retreat took place in Gent, Belgium with Students and researchers from all associated projects. Hereby, new ideas and cooperations were brought out during project presentations by means of posters. Special thanks go to the guest speakers Dr. Pietro Verzelli, Dr. Nicolo Alagna and Max Sprang who sparked the scientific discourse with interesting presentations on the topic of machine learning. And of course, besides scientific exchange and interesting talks, the enjoyment of the picturesque city was not neglected. We'd like to thank the Carl Zeiss foundation for funding this special event.

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Emergent AI Annual Meeting 2022

people discussing in front of scientific posters and having snacks
The Emergent AI Annual Meeting 2022 took place from September 27-28, 2022 at the Johannes Gutenberg-University of Mainz. Students and researchers from all associated projects presented their work. Numerous exciting discussions once again demonstrated the diversity and necessity of understanding emergent artificial intelligence and fostered novel ideas.
We'd like to thank the Carl Zeiss foundation for funding, and especially acknowledge Mr. Findeisen for taking the time to attend this event. Furthermore, we are grateful to the Institute of Molecular Biology for the accommodation.

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New Publication in Nature Electronics: Neuromorphic spintronics

Neuromorphic computing is a modern approach to computation that has attracted lots of interest from the research community. It uses brain-inspired principles to design circuits that can perform computational tasks with superior power efficiency to conventional computers. Researchers from the Emergent AI Center, in collaboration with groups in France, USA, and Japan have published a review on the subject, exploring spintronics-based implementations of neuromorphic computing tasks as well as discussing the challenges that exist in scaling up these systems.

Read the original Publication here: Neuromorphic spintronics

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Computer-based weather forecast: New algorithm outperforms mainframe computer systems

New algorithm solves complex problems more easily and more accurately on a personal computer while requiring less processing power than a supercomputer

The exponential growth in computer processing power seen over the past 60 years may soon come to a halt. Complex systems such as those used in weather forecast, for example, require high computing capacities, but the costs for running supercomputers to process large quantities of data can become a limiting factor. Researchers at Johannes Gutenberg University Mainz (JGU) and Università della Svizzera italiana (USI) in Lugano in Switzerland have recently unveiled an algorithm that can solve complex problems with remarkable facility – even on a personal computer.

Continue reading "Computer-based weather forecast: New algorithm outperforms mainframe computer systems"

Emergent AI Center welcomes eight new projects

The Emergent AI Center welcomes the following new projects:

  • Neural network-based approaches for multiscale modelling of topological defects
    Prof. Dr. Friederike Schmid, Dr. Karin Everschor-Sitte
  • Machine learning prediction of Odorant Receptor (OR)-ligand interactions: Chemical communication as the basis of swarm intelligence
    Prof. Dr. Miguel Andrade, Prof. Dr. Susanne Foitzik
  • Computational performance of autistic-like networks
    Prof. Dr. Martin Heine, Dr. Arthur F Bikbaev, Jun-Prof. Dr. Susanne Gerber
  • How emergent is the Brain?
    Prof. Dr. Heiko Luhmann, Jun-Prof. Dr. Maik Stüttgen, Prof. Dr. Illia Horenko
  • Application of machine learning algorithms to search for dark-matter signals in spectroscopic data
    Prof. Dr. Dmitry Budker, Prof. Dr. Stefan Kramer
  • Deep Learning of natural selection in population genomic data
    Dr. Yoan Diekmann, Prof. Dr. Joachim Burger
  • Repetitive DNA and the ‘C-value enigma’ of genomics
    Prof. Dr. Thomas Hankeln, Prof. Dr. Miguel Andrade
  • Learned Structures for Big Data in Bioinformatics
    Prof. Dr. Bertil Schmidt, Prof. Dr. Thomas Hankeln, Prof. Dr. Andreas Hildebrandt

For more information on the individual projects, please take a look at the research part of the website

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Seminar on Reservoir Computing by Prof. Dr. Herbert Jaeger

On June 4th of 2019 Prof. Dr. Herbert Jaeger, pioneer in the field of Reservoir Computing, presented a seminar at the Johannes Gutenberg University Mainz (JGU). Reservoir Computing is an alternative machine learning approach for Recurrent Neural Networks which is in many ways complementary to deep learning.  The talk gave an introduction to the basic principles and variants of Reservoir Computing. Some illustrative examples were presented.

Announcement for Prof. Dr. Jaeger seminar

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