KLI Colloquia are invited research talks of about an hour followed by 30 min discussion. The talks are held in English, open to the public, and offered in hybrid format.
Join via Zoom:
https://us02web.zoom.us/j/5881861923?omn=85945744831
Meeting ID: 588 186 1923
Fall-Winter 2026/27 KLI Colloquium Series
1 October 2026 (Thurs) 3-4:30 PM CET 
Scientific Integration as Fit: The Developmental Biases of Interdisciplinarity
Olesya BONDARENKO (KLI)
8 October 2026 (Thurs) 3-4:30 PM CET
The Role of Conversational Cues in the Co-Evolution of Language and Cooperation
Theresa MATZINGER (University of Vienna)
5 November 2026 (Thurs) 3-4:30 PM CET
Kin Matters: An Intervention in the Fragile Sciences
Robert A. WILSON (University of Western Australia)
19 November 2026 (Thurs) 3-4:30 PM CET
Modeling the Evolution of Human Early Embryogenesis with Stem Cells
Nicolas RIVRON (Institute of Molecular Biotechnology/IMBA, Vienna)
3 December 2026 (Thurs) 3-4:30 PM CET
Peter TURCHIN (Complexity Science Hub, Vienna)
10 December 2026 (Thurs) 3-4:30 PM CET
On the Cultural Macroevolution of Intentional Cranial Modifications
Marcelo SÁNCHEZ-VILLAGRA (University of Zurich)
14 January 2027 (Thurs) 3-4:30 PM CET
DNA from Archaeological Sediments as a Tracer for Past Societies
Benjamin VERNOT (University of Vienna)
28 January 2027 (Thurs) 3-4:30 PM CET
Beyond Fear: How the Amygdala Links Interoception and Exteroception
Ronald SLADKY (University of Vienna)
KLI Colloquia 2014 – 2026
Event Details
Picture Gallery
In the biosciences, the rapidly growing amount of experimental results and the increasing complexity of the phenomena under investigation pose an unprecedented challenge for the interpretation and integration of the accumulated data. Abstraction and modeling are required. Due to the improvement of computational methods, the modeling of biological phenomena has reached a completely new stage. It is now possible to model spatial and temporal interactions of nearly all processes in hitherto unknown detail, and with increasing sophistication. The generation of models promotes the organization of data and knowledge, the formulation of hypotheses, the estimation of measures, and the analysis and classification of results. At the same time, bottom up models elucidate the properties of natural biological systems. Therefore, the concepts and methods used in modeling and simulation are a key for major advances in the biological sciences. The present workshop investigates the ways in which the new modeling strategies help and influence our understanding of biological processes.

