Guest Lecture on Transcendental Information Cascades by Markus Luczak-Roesch
News from Mar 01, 2018
March 19, 10-12, Markus Luczak-Roesch, Senior Lecturer in Information Systems at Victoria University of Wellington, will hold a guest lecture on the topic of "Transcendental Information Cascades: From Popper's conceptualization of evolution to an understanding of emergence".
The lecture will be held in room 120, Königin-Luise-Str. 24/26.
"In this talk I will introduce Transcendental Information Cascades, a method to understand the temporal dynamics of naturally occurring complex systems. The distinctive feature of the approach is that it relies on a specific kind of spatio-temporal network that represents information token recurrence and coincidence. Transcendental Information Cascades make formerly hidden dimensions of sequential data accessible and throw up novel questions about chaos and randomness. I will present various applications of the method in different domains such as the analysis of digital traces in online communities, English literature, and micro-linguistics."
Markus Luczak-Roesch is a Senior Lecturer in Information Systems at the School of Information Management at Victoria University of Wellington, New Zealand. Markus started his academic career as a Lecturer in Computer Science at the Free University of Berlin and then joined the University of Southampton to work as a Senior Research Fellow on the prestigious EPSRC-funded project SOCIAM – The Theory and Practice ofSocial Machines (http://sociam.org). At the heart of his most recent research are temporal dynamics in information sequences that can be observed in naturally occurring complex systems. His focus is on the foundations of space and time in the context of information as well as emergent meaning that is rooted in coincidence. The information sequences Markus is studying stem from digital traces left by humans in online communities such as Wikipedia, and citizen science platforms such as Zooniverse, but also literary texts, brain wave recordings, and micro-linguistic data about language use.