Kay Axhausen
ETH Zurich, Switzerland
Transport planning’s dilemma: Can an ebike city help ?
Transport planning’s dilemma: Can an e-bike city help? »
The current transport policy has to negotiate the demands of the GHG targets of their cities, countries, while maintaining, improving accessibility with its induced demand consequences. The talk will discuss this dilemma against past and current policies.
For cities it will present the idea of the ebike, bike, public transport, walking city as a possible vision for urban areas. The example will be the city of Zürich for which a large collaborative ETH project showed its feasibility.
Will you book the accommodation for me ?
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Johan Bollen
University of Amsterdam, Netherlands
Computational science approaches to study the complex systems that shape mental health.
Millions of individuals have now published extensive longitudinal records of their emotions, thoughts, and activities on social media. We leverage machine learning and artificial intelligence methods to study the complex dynamics of the bidirectional relationship between cognitive biases as they are expressed in large-scale records of online language and internalizing disorders such as depression and anxiety. Our work suggests an interesting relation between the online expressions of cognitive biases and societal polarization, even at the timescale of years and decades. Unraveling the connections between online language, cognitive biases, and social phenomena such as polarization may point towards a better quantitative understanding of the dynamics of the cognitive, behavioral, and social drivers of mental health disorders at population scale.
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Tiziana Di Matteo / Giuseppe Brandi
King’s College London, UK / Northeastern University, UK
Multiscaling in Financial Markets: A Window into the Complexity of Prices and Volatility Dynamics
Financial markets are paradigmatic complex systems, in which the collective behaviour of heterogeneous interacting agents gives rise to emergent statistical regularities that transcend simple diffusion. Among these, multiscaling stands out as a particularly informative signature: a process is multiscaling when its moments scale with non-linear, moment-dependent exponents, reflecting the hierarchical organisation, intermittency, and long-range dependences that characterise market dynamics across multiple time horizons [1]. In this talk, we explore multiscaling as a diagnostic lens for understanding the complexity of both price and volatility dynamics in financial markets. On the price side, we review evidence of multiscaling in financial returns and discuss what it reveals about the structural properties of financial systems from the perspective of econophysics [2-4]. On the volatility side, we turn to the class of rough volatility models, and in particular the rough Bergomi model, where fractional Brownian motion with a small roughness parameter generates strikingly irregular volatility paths [5,6]. We investigate whether the multiscaling observed in these models reflects genuine dynamical complexity encoded in the temporal structure of volatility, or whether it can be traced back to the distributional properties of returns. Our results shed light on the boundary between truepath-dependent complexity and distributional artefacts, with implications for financial modelling, derivative pricing, and risk management. More broadly, this work contributes to the econophysics tradition of using scaling analysis to map and interpret the rich complexity of financial systems.
[1] T. Di Matteo, Quantitative Finance 7(1) (2007) 21.
[2] R. J. Buonocore, T. Aste, T. Di Matteo, Chaos, Solitons and Fractals 88 (2016) 38-47.
[3] R. J. Buonocore, T. Di Matteo, T. Aste, Phys.Rev.E, 95 (4) (2017) 042311.
[4] Giuseppe Brandi, T. Di Matteo, The European Journal of Finance, (2021) DOI:10.1080/1351847X.2021.1908391.
[5] Giuseppe Brandi, T. Di Matteo, International Review of Financial Analysis 84 (2022)102324.
[6] G. Brandi, T. Di Matteo, « Multiscaling in the Rough Bergomi Model: A Tale of Tails »,Quantitative finance, submitted 2026, arXiv preprint arXiv:2601.11305
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Chiara Poletto
University of Padova, Italy
Unravelling the complexity of multi-pathogen interaction
The simultaneous circulation of multiple pathogens fundamentally alters epidemic dynamics and the effectiveness of public health interventions. While advances in genomic sequencing now enable detailed detection of pathogen diversity, interpreting this diversity remains challenging, as it is shaped by complex human behaviour and interaction patterns. These complexities have profound implications for epidemic control.
In this talk, I will explore how human and environmental factors shape the dynamics of co-circulating viruses. By combining data analysis, stochastic modelling, and network theory, I will demonstrate how complex networks operating at different scales, together with dynamically changing transmission conditions, influence viral co-existence and dominance patterns. I will illustrate these concepts using case studies on acute respiratory infections and show how theoretical insights can provide ground knowledge to inform public health response.
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