Overview of the talks in chronological order.

Monday, December 17

Konstantin Blyuss

Title: Controlling current on the quantum scale

Affiliation: Newcastle University, UK

Control of the emission and flow of electrons forms the basis of electronics and with it much of modern technology.  As we shrink and cool electronic circuits, we enter a regime where the granularity and wave-particle duality of electrons become important.  Learning to control electron behaviour in this quantum-transport regime presents significant challenges, but also opens up opportunities for new physics and device functionalities.

In this talk, I will give an overview of the nascent field of feedback control in quantum transport.  I will discuss how feedback can give rise to a range of interesting effects, such as noise suppression, quantum-state stabilisation, and Maxwell's daemon. Finally, I will also future developments and the prospect of  coherent quantum control.

Philipp Strasberg

Title: Operational stochastic thermodynamics: From quantum backaction to time-delayed feedback control

Affiliation: Université du Luxembourg

The theory of stochastic processes describes noisy systems which
are perfectly and passively observed. Unfortunately, it can be no
longer used whenever an external agent passively or actively intervenes
the process (e.g., via measurement disturbance or feedback control).
The lack of a formal understanding of such processes has also
hindered progress in understanding the thermodynamics of feedback
controlled classical and, in general, quantum systems.
After briefly reviewing how to generalize stochastic processes to
arbitrary interventions, I will show how to define the basic
thermodynamic quantities internal energy, heat, work and entropy
along a single observed trajectory. The validity of the first and
second law is established. Based on a recent experiment I
demonstrate the versatility of the framework to describe even time-
delayed quantum feedback control.

Marton Posfai

Title: Emergent hierarchies and social stability

Affiliation: UC Davis, USA

Hierarchy of social organization is a ubiquitous property of animal and human groups, linked to resource allocation, collective decisions, individual health, and even to social instability. In my talk, I will discuss aspects of modelling the dynamics of hierarchy formation. I will first focus on the role of talent versus social feedback in obtaining rank. Experimental evidence shows that both impact hierarchies; existing mathematical models, however, focus on the latter. I will introduce a rigorous model that incorporates both features, and show effects that arise from the interaction of the two.

In the second half of my talk, I will discuss our collaboration with the California National Primate Research Center, this joint work aims to model the social structure and stability of rhesus macaque groups. Rhesus macaques live in cohesive hierarchically-structured groups of approximately one hundred individuals. Their social organization is regulated by a multiplex network defined by kinship and a number of interactions including grooming, fighting and formal submission. A notable property of macaque societies is that they can become unstable: the hierarchical organization may collapse, culminating in large-scale fighting, dissolution of social order and disbanding of entire groups. I will briefly describe the structure of their social networks and how modelling their dynamics help us understand social collapse.

Vitaly Belik¹ und Kathleen Loock²

Title: Network Science Perspective on Hollywood Remakes

Title: Bio‐inspired Information Processing: The Future of Artificial Intelligence?

Affiliation: Institute for Electrical Engineering and Information Technology
Kiel University, Germany

Information processing in biological nerve system is characterized by highly parallel,
energy  efficient  and  adaptive  architectures  in  contrast  to  clock  driven  digital  Turing
machines.  Even  simple  creatures  outperform  supercomputers  when  it  comes  to  pattern
recognition,  failure  tolerant  systems  and  cognitive  tasks.  Fundamental  building  blocks
leading  to  such  remarkable  properties  are  neurons  as  central  processing  units,  which  are
(with  variable  strengths)  interconnected  by  synapses  to  from  a  complex  dynamical  three
dimensional network. The field of neuromorphic engineering aims to mimic such biological
inspired  information  pathways  by  electronic  circuitries.  Up  to  today,  this  approach  is
hindered  by  an  inadequate  understanding  how  to  link  the  information  pathways  on  the
local, synaptic and neuron level to the global functionality of the entire brain network. One
of  the  central  pillars  in  science  (for  example  in  solid  state  physics)  the  so‐called
“reductionism”  smilingly  reaches  its  limits  and  nourishes  a  longstanding  conflict  between
natural science and spiritual science. 
In  the  talk  I  will  show  restrictions  of  conventional  IT  and  present  alternative
computing  architectures,  which  are  currently  under  investigations.  The  challenges  and
possible limitations of bio‐inspired computing approaches will be discussed.

Hiroyasu Inoue

Wednesday, December 19

Vittoria Colizza

Title: Complexity and infectious disease epidemics

Affiliation: Inserm & Sorbonne Université Paris, France

Our understanding of infectious diseases prevention and control is rooted in the theory of host population transmission dynamics. Contacts between hosts (along which transmission can occur) and contacts between populations of hosts (along which spatial diffusion can take place) drive the epidemiology of infectious diseases, determining if and how quickly they spread, and who gets infected. Mathematical epidemiology has made great progress in this area in the last decades, moving from approximations where every host is in contact with anyone else with equal probability (i.e. the homogeneous mixing assumptions) to frameworks where patterns of contacts between hosts or population of hosts are explicitly accounted for through networks, made of nodes representing hosts/populations of hosts and connections representing potential transmission/diffusion links. This talk will present recent findings on the role that complexity of host population structure has on the resulting disease spreading dynamics and discuss future perspectives on the use of epidemic modeling approaches in the realm of public health.

Abigail Horn

Title: Integrating Network Modeling and Emerging Data Sources to Approach Large-Scale Problems in Public Health

Affiliations:
1 Federal Institute for Risk Assessment (BfR), Berlin, Germany
2 Kühne Logistics University, Hamburg, Germany
∗ E-mail: abbylhorn@alum.mit.edu

My research focuses on modeling network structure and dynamics to better understand how disease and
behavior spread through physical and social systems, to inform and develop interventions for preventing,
mitigating, and controlling both infectious and chronic diseases. Research problems and approaches are
motivated by and evaluated on large-scale real-world network data from physical systems including trans-
port, logistics, and infrastructure, as well as digital trace data from social networks, mobile phone records,
credit card transactions, and other emerging sources. The questions I am researching can be categorized
into three primary areas: (i) How do network structure and dynamics influence transmission of disease or
behaviors; (ii) Can we develop accurate predictions and forecasts for real-time outbreak response and risk
assessment; and (iii) What are network-based interventions and mitigation strategies for preventing diseases.
In this talk I will discuss a few current research activities within these themes, including: modeling food
supply network structure to identify the source of large-scale outbreaks of foodborne disease [1-3]; tracing
the source of network-based disease diffusion processes more generally including infectious diseases spread
through the global air traffic network and cholera spread through water distribution networks; and integrat-
ing digital trace data to quantify the impact of mobility on food consumer behavior, nutrition, and health.
I will also provide a perspective on current themes and opportunities for integrating emerging data sources
to model social network structure for public health applications.
[1] Balster, A., and Friedrich, H. (2018). “Dynamic freight flow modelling for risk evaluation in food supply,”
Transportation Research E, doi.org/10.1016/j.tre.2018.03.002.
[2] Horn, A., Friedrich, H. (2018). “Locating the Source of Large-scale Diffusion of Foodborne Contamina-
tion.” arXiv preprint arXiv:1805.03137.
[3] Liu, X., Horn, A., Su, J., Jiang, J. (2018).“A Universal Measure for Network Traceability.” Omega: The
International Journal of Management Science. 10.1016/j.omega.2018.09.004.

Beatriz Vidondo

Both human and veterinary public health aim to the wellbeing of human populations. Their perspective and therefore the challenges they face are, however, very different. Network approaches have become, for both disciplines, state of the art methods for modelling infectious disease spread. I will summarize a first case study of a bioterror attack on a human population, and the most effective way to control it (Vidondo et al 2012); and a second case study of a generic infectious process spreading on a livestock population and a very effective way to detect it (Vidondo and Voelkl 2018; Schirdewahn et al in prep). In both case studies, social contacts (for disease transmission) are realistically specified using single layer temporal networks. I will finally outline the prospect of multilayer temporal networks to answer research questions in what epidemiologists call a "one-health" approach (humans, their livestock and the environment they live in, including wildlife).

Title: Cascade dynamics on networks

Affiliation: University of Limerick, Ireland

Network models may be applied to describe many complex systems, and in the era of online social networks the study of dynamics on networks is an important branch of computational social science.  Cascade dynamics can occur when the state of a node is affected by the states of its neighbours in the network, for example when a Twitter user is inspired to retweet a message that she received from a user she follows, with one event (the retweet) potentially causing further events (retweets by followers of followers) in a chain reaction. In this talk I will review some simple models that can help us understand how social contagion (the spread of cultural fads and the viral diffusion of information) depends upon the structure of the social network and on the dynamics of human behaviour. Although the models are simple enough to allow for mathematical analysis, I will show examples where they can also provide good matches to empirical observations of cascades on social networks.

Alessio Cardillo

Title: Entropic selection of concepts unveils hidden topics in documents corpora

Affiliation: University of Bristol, UK

The organization and evolution of science has recently become itself
an object of scientific quantitative investigation, thanks to the
wealth of information that can be extracted from scientific documents,
such as citations between papers and co-authorship between
researchers. However, only few studies have focused on the concepts
that characterize full documents and that can be extracted and
analyzed, revealing the deeper organization of scientific knowledge.
Unfortunately, several concepts can be so common across documents that
they hinder the emergence of the underlying topical structure of the
document corpus, because they give rise to a large amount of spurious
and trivial relations among documents. To identify and remove common
concepts, I will introduce a method to gauge their relevance according
to an objective information-theoretic measure related to the
statistics of their occurrence across the document corpus. After
progressively removing concepts that, according to this metric, can be
considered as generic, I will show how the topic organization of the
corpus under scrutiny displays a correspondingly more refined
structure.