Current activities:

• On August 22, 2024, Prof. Stefan Kramer was appointed "KI-Lotse" (roughly translated as "AI guide") for the life sciences by Alexander Schweitzer, the Prime Minister of the State of Rhineland-Palatinate. In his new role, Prof. Kramer will be advising partners from either AI or the life sciences regarding collaborations and the state government regarding the interface between the two disciplines. Congratulations and good luck with his plans to further strengthen the interaction between AI and the life sciences!

 

Gutenberg Workshop on AI for Scientific Discovery:

• From 2-4 September the Gutenberg Workshop on AI for Scientific Discovery will take place in Weingut Wasem with an excellent line-up of invited speakers. The workshop was scientifically organized by Professor Peter Baumann and Professor Stefan Kramer of JGU Mainz. It will dive into a fascinating journey through the world of automated scientific discovery, driven by artificial intelligence. Since its inception, AI research has been deeply intertwined with the pursuit of uncovering scientific insights, a synergy that has gained remarkable momentum since the late 1970s. Fueled by advancements across various domains, AI now stands at the forefront of reshaping the landscape of scientific inquiry. The workshop focuses on cutting-edge topics, such as automation and autonomy in science, deep learning and foundation models for science, and the automated discovery of interpretable scientific knowledge. The workshop is organized around the following four themes:
  • Automation and autonomy in science
  • Applications of AI
  • Equation discovery, symbolic regression, and the induction of process models
  • Integration effort

• The list of speakers includes some of the pioneers of the field:
  • Pat Langley (who started the field of AI for Scientific Discovery and wrote the groundbreaking book about it together with Herbert Simon, the only person to win both a Nobel and a Turing award)
  • Burkhard Rost (the first person to apply neural networks -- together with alignments -- successfully to protein data, to achieve the first breakthrough in secondary structure prediction)
  • Ross D. King (the first person to build a completely autonomous robot scientist)
  • Sašo Džeroski (who established equation discovery as a field and achieved a major breakthrough by employing context-free grammars for that purpose)

• Additionally, some of our group members and associates will present their current research:
  • Jannis Brugger will show how equation discovery can profit from a supervised learning setting instead of a reinforcement one. Furthermore, he will highlight the important task of how to embed tabular data.
  • Mattia Cerrato developed together with his seminar students a testbed for AI-driven scientific discovery, called Science-Gym. The benchmark foster physical understanding of the tasks, by having agents autonomously perform data collection, experimental design, and equation discovery.
  • Cedric Cerstoff worked on an extension for Monte-Carlo tree search that allows the exclusion of already explored subtrees or leaves, resulting in a broader search, while maintaining identical computational resources.
  • Marius Köppel will highlight the use of AI in particle physics in the past, discuss
    current capabilities, and explore future directions.

 

• Mattia Cerrato will present Science-Gym: A Simple Testbed for AI-drivenScientific Discovery, which is a joint work with Nicholas Schmitt, Lennart Baur, Edward Finkelstein, Selina Jukic, Lars Münzel, Felix Peter Paul, Pascal Pfannes, Benedikt Rohr, Julius Schellenberg, Philipp Wolf, and Stefan Kramer.
• Jannis Brugger will present Residuals for Equation Discovery, which is a joint work with Viktor Pfanschilling, Mira Mezini and Stefan Kramer.