Invited Speakers
Michael Batty
University College London, UK Michael Batty is Bartlett Professor of Planning at University College London, where he is Chair of the Centre for Advanced Spatial Analysis (CASA). He has worked on computer models of cities and their visualisation since the 1970s and has published several books, such as Cities and Complexity (MIT Press, 2005) and The New Science of Cities (MIT Press, 2013). Both books won the Alonso Prize of the North American Regional Science Association. His most recent book, Inventing Future Cities, was published by MIT Press in late 2018. Prior to his current position, he was Professor of City Planning and Dean of the School of Environmental Design at the University of Wales at Cardiff from 1979 to 1990 and then Director of the National Center for Geographic Information and Analysis at the State University of New York at Buffalo from 1990 to 1995. He is a Fellow of the British Academy (FBA) and the Royal Society (FRS), was awarded the CBE in the Queen’s Birthday Honours in 2004 and the 2013 recipient of the Lauréat Prix International de Géographie Vautrin Lud. In 2015 he received the Gold Medal of the Royal Geographical Society for his work on the science of cities. In 2016, he received the Senior Scholar Award of the Complex Systems Society and the Gold Medal of the Royal Town Planning Institute. In 2018, he was awarded the Waldo Tobler prize for GI Science of the Austrian Academy of Sciences, and in 2019, he was elected as a Fellow of the Regional Science Association. Title: The Pulse of the city Abstract: In this talk, I will sketch the ways in which networks have and are being developed for understanding and forecasting the spatial structure of cities. I will review a little of the history of the way cities have developed, and the way networks are key to the way energy in terms of people, goods, and information provide the lifeblood of the city. I will make an important distinction between the high and low-frequency city, arguing that flows on networks are usually studied either in near real-time or over much longer periods, the former being central to the way we understand traffic on a minute by minute, hour by hour basis, the latter being ways in which cities grow and evolve with respect to different transportation networks. I will relay two examples of such ideas, first explaining how we have used the Oyster card payment data in Greater London to represent and simulate movements on the Tube, and secondly to explore ways in which the entire spatial structure of Great Britain can be explored in terms of the long term impact of new infrastructure projects such as Crossrail 1 and HS2. In this way, I hope to outline ways in which networks are critical constructs in building a science of cities and effective methodologies for their planning. Go back to the list of speakers |
Laura Alessandretti
Copenhagen Center for Social Data Science, Denmark Twitter: @lau_retti Laura Alessandretti is a Postdoctoral Researcher at the Copenhagen Centre for Social Data Science at the University of Copenhagen. She studies aspects of human behavior and cognition, with a focus on Human Mobility and Human/Smartphones interactions, through the analysis of longitudinal digital traces, using network science methods, as well as mathematical and computational modelling. Her current research includes the study of exploration-exploitation trade-offs in human mobility (Nature Human Behaviour 2.7 (2018): 485-491.), the interplay between mobility behaviour and smartphone usage, and dynamics of competition and consensus in blockchain-based ecosystems (Royal Society open science 4.11 (2017): 170623.). Laura holds a PhD in Applied Mathematics from City, University of London and a Master's in Physics of Complex Systems from École normale supérieure de Lyon. She previously held a postdoctoral position at the Department of Mathematics and Computer Science at the Technical University of Denmark and is a former elected member of the Young Researchers of the Complex Systems Society advisory board. Title: The Scales of Human Mobility Abstract: There is a paradox at the heart of our current understanding of human mobility. On one hand, a highly influential stream of literature driven by analyses of massive empirical data found that human movements show no evidence of characteristic spatial scales, and describe human mobility as scale-free. On the other hand, in geography, the concept of scale, referring to meaningful levels of description from individual buildings through neighborhoods, cities, regions, and countries, is central for the description of various aspects of human behaviour such as socio-economic interactions, political and cultural dynamics. In this talk, I will present how we solved this apparent contradiction and showed that human mobility indeed contains meaningful scales, corresponding to spatial containers restricting mobility behavior. The scale-free results arise from aggregating displacements across containers. I will present a simple model, which given a person’s trajectory, infers their neighborhoods, cities, and so on, as well as the sizes of these geographical containers. I will show that our description dramatically improves on the state-of-the-art in modeling, and allows us to better understand effects due to socio-demographic differences and the built environment. Go back to the list of speakers |
Robin Dunbar
University of Oxford, UK Twitter: @RobinDunbar10 Robin Dunbar gained his MA from the University of Oxford and PhD from Bristol University. He is currently Professor of Evolutionary Psychology at the University of Oxford, and an emeritus Fellow of Magdalen College. He has held Research Fellowships and Professorial Chairs in Psychology, Biology and Anthropology at the University of Cambridge, Stockholm University, University College London, and the University of Liverpool. He is an elected Fellow of the British Academy, and was co-Director of the British Academy’s Centenary Research Project. His principal research interests focus on the evolution of sociality in mammals (with particular reference to ungulates, primates and humans). He is best known for the social brain hypothesis, the gossip theory of language evolution and Dunbar’s Number (the limit on the number of relationships that we can manage). His current project focusses on the mechanisms of social cohesion, and uses a range of approaches from comparative analysis to cognitive experiments to neuroimaging to explore the mechanisms that allow humans to create large scale communities. His popular science books include The Trouble With Science, Grooming, Gossip and the Evolution of Language, The Human Story, How Many Friends Does One Person Need? Dunbar’s Number and Other Evolutionary Quirks, The Science of Love and Betrayal and Human Evolution. Title: The dynamics of friendship in the offline and online worlds Abstract: As one of the most intensely social species, friendships are central to our success as individuals and as a species. In the face-to-face offline world where our sociality, and the psychological mechanisms that underpin this, has evolved over many hundreds of thousands of years, time imposes severe constraints on our abilities to interact with many people. Out of sight quickly becomes out of mind. The internet, and especially social media, offers the opportunity to break through these constraints so as to dramatically increase the size of our global village. But has this promissory note been fulfilled? And if not, why not? I shall suggest that the constraint lies as much in our psychology as it does in the constraints of time. Nonetheless, a better understanding of how these constraints work may provide better insights into how social media might be employed to greater advantage. Go back to the list of speakers |
Andrea Migliano
University of Zurich, Switzerland Twitter: @andrea_migliano Andrea Bamberg Migliano is a Professor in Evolutionary Anthropology at the University of Zurich. She works on comparative behaviour of hunter-gatherer populations, with ongoing fieldwork in the Philippines and Congo. She uses behavioural ecology, network analyses and experimental psychology to understand how diversity in the hunter-gatherers foraging niche has shaped human specific adaptations such as complex sociality, cumulative culture and pro-sociality. Prof Migliano received her PhD in Evolutionary Anthropology from the University of Cambridge in 2007. Following her PhD, she has held a Junior Research Fellowship at Clare College, Cambridge, followed by an Associate Professorship at University College London. Since moving to Zurich in 2018, Prof Migliano has started the Hunter-Gatherers Evolutionary Ecology Group expanding the comparative fieldwork approach to Indonesia and the Amazon. Title: Using social network analyses to understand the evolution of hunter-gatherers' complex Abstract: Human capacity for cumulative culture (the type of culture that cannot be recreated by a single individual and accumulates over generations) has evolved over hundreds of thousands of years in our pre-Neolithic ancestors. Hunter-gatherers are vanishing fast, and yet are the best window we have into a lifestyle that have shaped our unique evolutionary traits. Using social network analyses, quantification of hunter-gatherers medicinal plant knowledge and agent based model simulations, I show how hunter-gatherers multi-level sociality has facilitated the evolution cumulative culture. Go back to the list of speakers |
Tiago de Paula Peixoto
Central European University, Hungary Twitter: @tiagopeixoto Tiago P. Peixoto is Associate Professor at the Department of Network and Data Science at the Central European University in Budapest, and researcher at the ISI Foundation, Turin. He obtained his PhD in Physics at the University of São Paulo, and his Habilitation in Theoretical Physics at the University of Bremen. He was a Humboldt Foundation fellow, and the recipient of the Erdős-Rényi Prize in Network Science. His research focuses on characterizing, identifying and explaining large-scale patterns found in the structure and function of complex network systems — representing diverse phenomena with physical, biological, technological, or social origins — using principled approaches from statistical physics, nonlinear dynamics and Bayesian inference. Title: Network reconstruction from indirect observations Abstract: The observed functional behavior of a wide variety large-scale systems is often the result of a network of pairwise interactions. However, in many cases these interactions are hidden from us, either because they are impossible or very costly to be measured directly, or, in the best case, are measured with some degree of uncertainty. In such situations, we are required to infer the network of interactions from indirect information. In this talk, I present a scalable Bayesian method to perform network reconstruction from indirect data, including noisy measurements and observed network dynamics. This kind of approach allows us to convey in a principled manner the uncertainty present in the measurement, and combined with versatile modelling assumptions can yield good results even when data are scarce. In particular, I describe how the reconstruction approach can be combined with community detection, allowing us to tap into multiple sources of evidence available for the task. We show how this combined approach provides a twofold improvement, by increasing not only the reconstruction accuracy, but also the identification of communities in networks. The latter improvement is possible even in situations where at first we might imagine that reconstruction is superfluous, for example when direct network data are available and measurement errors can be neglected. Go back to the list of speakers |
SPRINGER NATURE Invited Speaker
Yamir Moreno University of Zaragoza, Spain Twitter: @cosnet_bifi Prof. Yamir Moreno got his Ph.D. in Physics (Summa Cum Laude, 2000) from University of Zaragoza. He is the Director of the Institute for Biocomputation and Physics of Complex Systems (BIFI), the head of the Complex Systems and Networks Lab (COSNET) and Professor of Physics at the Department of Theoretical Physics of the Faculty of Sciences, University of Zaragoza. Prof. Moreno is also a Deputy Director of the ISI Foundation in Italy and External Professor of the Complexity Science Hub Vienna, Austria. He received the CSS Senior Scientific Award in 2019 and is an ISI Highly Cited Scientist 2019. Prof. Moreno is the elected President of the Network Science Society and was the President of the Complex Systems Society from 2015 to 2018. His field of research is in the theoretical foundations of complex systems, which he investigates using tools from mathematics, physics and network science. Prof. Moreno is a world expert on disease dynamics, diffusion processes, mathematical biology, nonlinear dynamical processes, and the structure and dynamics of complex systems. He has published more than 200 scientific papers with a total of 18500+ citations and h-index=54 (ISI WoK) or 30500+ and 64 (Google Scholar). At present, Prof. Moreno is a Divisional Associate Editor of Physical Review Letters, Editor of the New Journal of Physics, Chaos, Solitons and Fractals, and Journal of Complex Networks; an Academic Editor of PLoS ONE, and a member of the Editorial Boards of Scientific Reports, Applied Network Science, and Frontiers in Physics. Title: Biodiversity and Structural Stability of Multilayer Ecological Networks Abstract: Relations among species in ecosystems can be represented as complex networks where both negative and positive interactions are concurrently present. In the past years, such representation has spurred many advances –but also many debates– especially around mutualistic communities, whose structural features appear to facilitate mutually beneficial interactions and increase biodiversity, under some given population dynamics. However, current approaches neglect the complexity of inter-species competition by adopting a mean-field perspective that does not deal with competitive interactions properly. In this talk, we show that the information encoded in mutualistic networks can be used to build up a multilayer network that naturally accounts for both mutualism and competition. We then propose a new population dynamics that reveal that the structural stability of the system depends on an intricate relation between competition and mutualism. Finally, by performing a stability analysis, we show that May's hypothesis for the complexity of real ecosystems holds for real mutualistic networks. Go back to the list of speakers |
Hiroki Sayama Binghamton University, State University of New York, USA Waseda University, Japan Twitter: @HirokiSayama Hiroki Sayama is a Professor in the Department of Systems Science and Industrial Engineering, and the Director of the Center for Collective Dynamics of Complex Systems (CoCo), at Binghamton University, State University of New York. He received his B.Sc., M.Sc. and D.Sc. in Information Science, all from the University of Tokyo, Japan. He did his postdoctoral work at the New England Complex Systems Institute in Cambridge, Massachusetts. His research interests include complex dynamical networks, human and social dynamics, collective behaviours, artificial life/chemistry, interactive systems, and complex systems education, among others. He is an expert of mathematical/computational modelling and analysis of various complex systems. He has published more than 150 peer-reviewed journal articles and conference proceedings papers and has written or edited 13 books and conference proceedings about complex systems related topics. He currently serves as an elected Council and Executive Committee member of the Complex Systems Society (CSS), the Chief Editor of Complexity (Wiley/Hindawi), an Associate Editor of Artificial Life (MIT Press), and as an editorial board member for several other journals. Title: Diversity and Social Evolution: Theoretical and Experimental Approaches Abstract: In this talk, I will provide an overview of our three recent studies on the effects of diversity on complex social processes. Multidisciplinary methodologies are used, combining mathematical/computational modeling and human-subject experiments. The first study investigates primarily through agent-based simulation how diversities of individuals' knowledge and behavior may affect the performance of collective decision-making taking place in a social network. The second study experimentally tests the effects of individuals' background diversity on collaborative design and innovation. The third study elucidates via adaptive network simulation the importance of behavioral diversity of individuals on the maintenance of cultural (informational) diversity and social connectivity. Through these three interrelated studies, we illustrate how different forms of diversity of social constituents can have different, nontrivial implications for collective social dynamics. Go back to the list of speakers |
Dirk Brockmann
Humboldt University, Germany Twitter: @DirkBrockmann Dirk Brockmann is a Professor at the Institute for Biology at Humboldt University of Berlin and the Robert Koch Institute, Berlin. He is known for his work in complex systems, complex networks, computational epidemiology, human mobility and anomalous diffusion. He studied physics and mathematics at Duke University and the University of Göttingen where he received his degree in theoretical physics in 1995 and his PhD in 2003. After postdoctoral positions at the Max Planck Institute for Dynamics and Self-Organization, Göttingen, he became Associate Professor in the Department of Engineering Sciences and Applied Mathematics at Northwestern University in 2008. In 2013, he became Professor at the Institute for Biology at Humboldt University of Berlin. Brockmann worked on a variety of topics ranging from computational neuroscience, anomalous diffusion, Levy flights, human mobility, computational epidemiology, and complex networks. Title: What network science can say about the imminent COVID-19 pandemic Abstract: The novel coronavirus SARS-CoV-2 is currently developing from a national epidemic into an event of international and global scale. During the early phase of the epidemic, when case counts were high in Hubei province in China and low elsewhere one of they key epidemiological questions were to what extent other parts of the world were at risk of importing cases and when first case counts are expected to occur. Especially during the onset of an epidemic, little is known about epidemiological parameters of the emergent virus and the initial situation is difficult to assess. Therefore dynamical models are often unreliable because essential ingredients, initial conditions and parameter values, are missing. I will discuss how general network scientific principles and properties of the worldwide air-transportation network can be used to compute relative import risks at various locations and multiple scales. Predictions made by this approach are consistent with arrival time statistics and case counts in currently more than 20 affected countries. Furthermore I will explain why the dynamics of the epidemic in China unfolded in an unusual way and will provide an explanation for it Go back to the list of speakers |
Adilson Motter
Northwestern University, USA Twitter: @adilson_motter Adilson E. Motter is a Chair Professor of Physics at Northwestern University. Prior to joining the Northwestern faculty in March 2006, he held positions as Guest Scientist at the Max Planck Institute for the Physics of Complex Systems and as Director's Funded Postdoctoral Fellow at the Center for Nonlinear Studies at Los Alamos National Laboratory. Awards received by Prof. Motter include the Sloan Research Fellowship, the NSF CAREER Award, the Erdős-Rényi Prize in Network Science, and the Simons Foundation Fellowship in Theoretical Physics. He is a Fellow of the American Physical Society (APS) and of the American Association for the Advancement of Science (AAAS). He is also a member of the Science Board of the Santa Fe Institute and serves in the Editorial Board of Physical Review X, among other journals. He is a former Chair of the APS Topical Group on Statistical & Nonlinear Physics (GSNP) and is the current Vice President and Secretary of the Network Science Society. Prof. Motter's research is focused on the dynamical behavior of complex systems and networks and is inherently interdisciplinary, cutting across physics, mathematics, engineering, and life sciences. Title: Making the case for a perfectly imperfect world Abstract: The central goal of my research on collective behavior is to understand how systems can exhibit behavioral homogeneity even though the systems themselves are not homogeneous at all. Think of heart cells beating together, a power grid operating in sync, agents trying to reach consensus, and so on. It is widely held that individual entities in such systems are more likely to exhibit the same behavior if they are equal or similar. Our recent research shows that this assumption is generally false when the entities interact with each other. In this talk, I will discuss scenarios in which interacting entities can keep pace with each other only when they are suitably different, and thus the observed behavior is homogeneous only when the system itself is not. This exposes situations in physical and biological systems in which consensus, coherence, or synchronization is observed because of – not despite – differences. Since individual differences are ubiquitous and often unavoidable in real systems, such “imperfections” can be an unexpected source of behavioral homogeneity, epitomizing the notion that imperfections can make things perfect. Go back to the list of speakers |
Clara Granell
University of Zaragoza, Spain Twitter: @claragranell Clara Granell Martorell is a Juan de la Cierva Postdoctoral Researcher at the Department of Physics of the Condensed Matter at the Universidad de Zaragoza, Spain. She obtained her PhD from Universitat Rovira i Virgili, in Tarragona, Spain. Her past appointments include postdoctoral training at the Department of Mathematics of the University of North Carolina at Chapel Hill and the Universitat de Barcelona Institute of Complex Systems. Her work is devoted to complex systems, with a special focus on problems suited to be represented with networks. She has experience working in Epidemic Spreading, Community Detection, Multiplex Networks as well as applying theoretical methods to real data, such as Neuronal Networks. Title: Studying the interplay between epidemic dynamics and human behavior based on risk perception Abstract: Human behavioral responses play an important role in the impact of disease outbreaks and yet they are often overlooked in epidemiological models. Understanding to what extent behavioral changes determine the outcome of spreading epidemics is essential to design effective intervention policies. In this talk we will explore the interplay between the personal decision to protect oneself from infection and the spreading of an epidemic. I will present a model that couples a decision game based on the perceived risk of infection with a Susceptible-Infected-Susceptible model. Interestingly, we see that the simple decision on whether to protect oneself is enough to modify the course of the epidemics, by generating sustained steady oscillations in the prevalence. We deem these oscillations detrimental, and propose two intervention policies aimed at modifying behavioral patterns to help alleviate them. Surprisingly, we find that pulsating campaigns, compared to continuous ones, are more effective in diminishing such oscillations. Go back to the list of speakers |
Ciro Cattuto
ISI Foundation, Italy Twitter: @ciro Dr. Ciro Cattuto is an Associate Professor in the Computer Science Department of the University of Torino and a Research co-Director of ISI Foundation. His research interests include data science, network science, computational social science, public health. He holds a PhD in Physics from the University of Perugia, Italy and has carried out interdisciplinary work at the University of Michigan, USA, at the Enrico Fermi Center and Sapienza University in Rome, and at the Frontier Research System of RIKEN, Japan. He is a founder and principal investigator of the SocioPatterns project, a decade-long international collaboration on studying human and animal social networks with wearable sensors. He is an editorial board member of Nature Scientific Data, EPJ Data Science, PeerJ CS, Journal of Computational Social Science, Data & Policy journals. He was organizer and chair of leading conferences in Computer Science, Data Science and Complex Systems. He is a Fellow of the European Laboratory for Learning and Intelligent Systems (ELLIS). He is deeply interested in the social impact of data science and artificial intelligence, and he was designated by the European Foundation Centre to join the Strategic Planning Committee of CRT Foundation, a leading European philanthropy. Title: High-Resolution Social Networks Abstract: Digital technologies provide the opportunity to quantify human behaviors with unprecedented levels of detail and coverage. Personal electronic devices, wearable sensors and instrumented environments will be increasingly used to study the network structure of human mobility and interactions in environments relevant for computational social science, public health and infectious disease dynamics. In this talk I will review the experience of the SocioPatterns collaboration, an ongoing, decade-long international effort on studying high-resolution human and animal social networks using wearable proximity sensors. I will cover recent advances in data collection, focusing on important settings such as schools and households in low-resource, rural environments, and on recent work on animal social networks. I will discuss the network structures observed in empirical temporal network data, reflect on challenges such as generalization and data incompleteness, and review modeling approaches based on ideas from network science and machine learning. Go back to the list of speakers |
Heather Harrington
University of Oxford, UK Twitter: @haharrington Prof Harrington's research focuses on the problem of reconciling models and data by extracting information about the structure of models and the shape of data. To develop these methods, Prof Harrington integrates techniques from a variety of disciplines such as computational algebraic geometry and computational topology, statistics, optimisation, network theory, and systems biology. She is Co-Director of the Centre for Topological Data Analysis and she has been awarded a LMS Whitehead Prize and Adams Prize for her research contributions. Title: Topological data analysis for investigating dynamics on and of biological networks Abstract: Topological data analysis (TDA) allows one to examine features in data across multiple scales in a robust and mathematically principled manner, and it is being applied to an increasingly diverse set of applications. We investigate dynamics of biological networks, models and data using topological data analysis with concrete examples from contagions, neuroscience, and cancer. Time permitting, we will present preliminary results using TDA to analyse biological systems indexed by multiple parameters. Go back to the list of speakers |