Symposium: New Directions in Natural Sciences: Complexity, Machine Learning and Algorithms

Date: 05.03.2020

The main purpose of this meeting is the gathering of the EASA class "Natural Sciences" in order to foster scientific contacts among its members, to discuss essential past achievements in the areas it comprises (mathematics, physics, chemistry, biology etc.), and to look into important as well as promising future issues. This time the latter predominantly focus on machine learning and algorithms not only with regard to big data but also relating to methods to treat problems of complexity in natural sciences.

Scientific organisers:
Prof. Dr. Klaus Mainzer (Dean Class IV "Natural Sciences" of EASA)
Prof. Dr. Willibald Plessas (University of Graz)
Prof. Dr. Marko Robnik (University of Maribor)

Venue: Kardinal Schwarzenberg Haus, Kapitelplatz 3, 5020 Salzburg
REGISTRATION via e-mail to: 

EASA President Felix Unger:
Opening Address

Dean of Class IV "Natural Sciences" 
Klaus Mainzer (Technical University of Munich and University of Tübingen):
Complexity, Machine Learning and Algorithms


Session I  Chair: Willibald Plessas (University of Graz)

Mirjam Cvetic (University of Pennsylvania, Philadelphia):
Unification of Fundamental Forces of Nature by Modern String Theory

Felicitas Pauss (ETH Zürich):
Science Without Borders: From Infinitely Small to Infinitely Large

Tomaz Prosen (University of Ljubljana):
Dynamical Complexity and Chaos in Quantum Many-Body Systems

10:50-11:20   Coffee, Tea


Session II   Chair: Marko Robnik (University of Maribor)

Ferenc Krausz (MPI for Quantum Optics Munich):
Attosecond Science: From Basic Research to Cancer Detection

Kurt Wüthrich (Scripps Research, La Jolla, and ETH Zürich and iHuman Institute, ShanghaiTech University):
Biophysics and Structural Biology

Marc-Thorsten Hütt (Jacobs University Bremen):
How Patterns in Data Help Us to Understand Biological Complexity

13:20-14:20   Lunch


Session III    Chair: Mirjam Cvetic (University of Pennsylvania)

Gisbert Wüstholz (ETH and University of Zürich):
Computability, Complexity, and Effectivity in Number Theory

Dusan Repovs (University of Ljubljana):
Topologically-Based Machine-Learning Methods

15:40-16:10   Coffee, Tea


Session IV   Chair: Klaus Mainzer (TU Munich and University of Tübingen)

Dirk Inzé (Ghent University):
Solving the Complexity of Biological Systems

Markus Hengstschläger (Medical University of Vienna):
Medical Genetics in Digital Transformation

General Discussion and Closing

Place: Salzburg

Time: 08.30h - 17.50h


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