research lines

The research at the Institute is structured along four major pillars. Together, they combine the exploration of new concepts in the field of Complex Systems and their application in different scientific and social disciplines.

Social Sciences

Applications in the social sciences range from aspects of the individual plan to the study of great sociopolitical and economic structures. One of the applications that we can already consider as a traditional complex system we find it in economy and finances. But the activities of the institute want to open other fields of applicability. For example, concepts such as coordination dynamics and other characteristics of networks are applied to the study of the behavior related to sports, both individually and at team level. Similarly, issues related to biological nature of the ability of human language, its development at individual level, its emergence in species, and its implementation at brain level. In the same way, the complex perspectives illuminate the dynamics more thoroughly sociocomunicative and sociopolitical influencing linguistic uses, change evolutionary of forms, and the linguistic maintenance and replacement phenomena. Inside its application to history, we highlight an innovative project on which based on data archaeological and with introduction of ideas and formalisms typical of complex networks, is studying the political and economic structure of the Roman Empire.

Psychology and Behaviour

We work together with many actors and build tailored-made research collectives to address concerns and issues mostly grounded in urban contexts. Our methodology is based on community processes and provides a large set of social dilemmas and dyadic games to grasp specific behavioural traits in social interactions. By means of citizen science strategies, our experimental setup placed in the wild with situated, public and participatory experiments involving citizens at different levels. We have been working in several neighborhoods and we have been applying this methodology study mechanisms behind collective climate actions, to provide innovative tools to schools to increase student’s motivation or to better understand the mental health care-in-community ecosystem.

Economy and Finance

Stock markets describe several universal statistical stylized facts and patterns which can be studied and modelled thanks to the large data sets available. Relevant issues can in this sense be studied for better understanding stock price movements and better describing risk. Physics, complex systems science and their way of looking at natural phenomena has been in this sense contributed to this field in a multidisciplinary way, since early 1990s labelled as econophysics.

Stochastic processes and other tools coming from statistical physics have been implemented to model volatility, understand the statistics of extreme times such as the first-passage time, interpret emerging prices with agent based models or even to identify relevant information that triggers trader’s individual actions. Other topics been studied recently includes the economics of climate change and game theory.    


In the area of Linguistics we deal with the study of language and our lines of research currently include Biolinguistics, Sociolinguistics and Computational linguistics.

In the line of Biolinguistics we focus on the neurobiological foundations of the human capacity to naturally acquire grammatical systems.

In the line of Sociolinguistics and Linguistic Variation we focus on the application of theories of complexity to the comprehension of social, communicative-cognitive and linguistic phenomena.

In the line of Computational Linguistics we focus on the detection of linguistic features that allow us to identify communicative attitudes, opinion (polarity), irony, emotions and socio-political stance, in oral and written texts, especially those produced in social media. We are also interested in the development of language technology resources, which are the base of natural language processing applications (information extraction, question-answering, recommendation systems, machine translation, etc.).


The CEIPAC group has created a digitized amphorae epigraphy corpus. The main goal of this database is not only to gather as many data as possible related to amphorae epigraphy but, above all, to create a systemization model. Nowadays this database has more than 40,000 entries. The data associated with a specific amphora type, Dressel 20, stands out. This amphora type contained olive oil and originated from the Roman province of Baetica (Andalusia, Spain), as these were amphorae consistently stamped. The production area along the valley of the Guadalquivir and Genil rivers has been methodically documented, as well as the Monte Testaccio (Rome), an enormous depot of Dressel 20 amphorae.

The ultimate goal of the CEIPAC data collection is to carry out a study on the Ancient Economy based on the research of the production and distribution of food. The economy of the ancient world is fundamentally defined by the production and distribution of foodstuffs, and agriculture was the main occupation of a vast majority of the population. Our investigations provided new food for thought on the supply system both to the city of Rome and the army. This has led to the study of the role played by each of the Roman provinces. We study how each of these provinces was exploited according to the different needs of Rome and its army, how these provinces were transformed, how the provincial elites influenced on the political development of the empire and how the organization of supply affected the political progress of the Roman empire.

A currently funded EPNet project (Production and Distribution of Food during the Roman Empire: Economic and Political Dynamics), thanks to the new tools at our disposal, as well as the collaboration with IT professionals, physicists and experts on simulation, will allow us to validate or reformulate the current theories on the Roman Economy.


An important part of the Institute’s researchers develop their own research in the identification and description of the general principles and the key mechanisms that govern complex systems. This includes, on the one hand, theoretical aspects within the framework of network theory, or in  modeling of basic agents that make up a system and the study of emerging behaviors through their interactions. On the other hand, the analysis of many complex systems often involve processing a large amount of information, which requires the continuous development of tools in the context of the so-called "Big Data", with a clear application in the context of the Institute, as it would be computing gastronomy. Finally, a large number of complex systems are characterized to be dynamic, that is, they evolve over time.

Problems that go from fluid dynamics, plasticity in neural networks or metabolic networks, up to the dynamics of social networks or their own biological evolution as a whole, they all require the development of common tools. This is a fundamental aspect that occupies a good part of the research activities of the members of the Institute. Not to mention, the field from which most of the physical researchers of the Institute, Statistical Physics, with fundamental problems still open.



Network Science focuses on the study of complex networks as graph representations of complex systems. Complex networks display patterns of connection that are neither purely regular nor totally random, and are common to many real networks in differents domains. These non-trivial topological features, combined with dynamical processes and evolutionary changes, explain many observed emergent phenomena in complex systems.

We are working on developing theoretical and computational tools and methodologies for the study of complex networks, and on applying them to construct predictive models of physical, biological, and social phenomena. Some of the Network Science topics at UBICS are, among other, Network Geometry, multilayer networks, dynamical processes, and we consider a wide range of real complex systems, like molecular networks of interactions in the cell, the brain, social online and offline networks, the Internet, or international trade.


Statistical Physics

Statistical Physics techniques are at the basis of our approach to the study of complex systems. Statistical Physics uses methods of probability theory and statistics to bridge the gap between the microscopic properties of individual atoms and molecules to the macroscopic or bulk properties of materials.

We generalize the applicability of this branch of physics by studying also other types of microscopic elements, which interact to give place to macroscopic collective phenomena. Apart from the philosophical approach, some specific techniques that we have adapted for the study of complex systems are statistical models of anomalous diffusion and transport, models for the study of phase transitions and criticality --like the Ising model--, and renormalization group theory.

Data Science and Artificial Intelligence

The study of real complex systems requires the curation, structuring, filtering, analysis, and visualization of large amounts of empirical or experimental data. Our goal is to extract knowledge from data and, to that end, we combine the data-driven approach, based on different statistical, data mining, and machine learning techniques, with analytic and computational methodologies which allow us to construct and simulate meaningful models with predictive power.

Dynamical Systems

Complex systems are dynamic and properties and processes change over time. Dynamical systems theory provides a mathematical framework for treating the time dependence in complex systems, involving typically continuous time and stochastic or random events. Apart from time dependence in geometrical space, we use extended versions for systems with discrete elements. This serves us, for instance, to study dynamical processes on networks.

Among the different dynamical processes the phenomena of synchronization has received a lot of attention becoming one of the paradigmatic examples of emergence of collective properties with applications in physical, biological, chemical, technological and social systems. We have devoted many efforts to understanding synchronization phenomena taking advantage of the most recent developments in complex network science.

Science of Matter

A great variety of material systems can be described as complex systems. Very diverse physical and chemical systems often require not linear science tools, such as formation of spatiotemporal patterns in fluids or chemical reactions, at the same time their growing complexity demands adapting or extending these tools to new situations. Among the outstanding complex materials, the concept of intelligent materials does reference to systems that change their properties or structure depending on the environment where they are, and that have a great technological and industrial interest.

Also, in materials’ field, we can highlight soft matter, which includes gels, polymers, colloids and other systems with a structure, on intermediate stairs that gives them special physical properties, high deformability and complex rheology. These materials are of great relevance in Biology, and at the same time, of a high technological interest mainly in the industry of food and cosmetics.

Finally, they also belong to the field of active matter those systems that operating far from the thermodynamic balance are composed of units which are self-propelled from the Conversion in movement of energy that stores or takes advantage of the environment in which they move. Interaction between these elements originates patterns of self-organization and Very characteristic flows, examples of which we find from the stools of birds, the bacterial suspensions or filamentous protein assemblies (tubes) and motors molecular (kinesines). These systems generate central conceptual issues when encountered intrinsically out of balance, opening a possibility of synthesizing new types of materials, and have a very close connection with biological systems.

Smart Materials

Condensed matter systems exhibiting phase transitions and criticality are, most probably, the oldest example of study of complexity in science. In such situations, the material response to external changes is not a simple superposition of the response of its constituents but an emerging collective property. Its understanding using techniques from statistical physics, increases its predictability and allows the design of new useful tailored materials. In many cases this implies control of disorder as well as multiscale modelling from nanoscale to large thermodynamic scales. Our group has focused its study on functional materials for sensors and actuators, super-elastic materials, shape memory alloys, ferrocaloric materials for efficient refrigeration, as well as the problem of critical failure of materials under compression (up to geophysical scales).

Soft Matter

Colloidal systems, i.e. fluid suspensions of micron-sized polymer spheres, are interesting not only for their ubiquitous technological nature (colloids are presents in fogs, creams, foams, smoke, paints, etc..) but also because they provide a rich playground for basic Condensed Matter Physics. Colloidal particles display Brownian motion, size in the visible wavelength and dynamics in experimentally accessible time frames. Yet interactions in colloidal systems can be easily tailored in strength and range via application of relatively small external fields. These striking features make colloids excellent models for behavior and dynamics in dissipative systems with intrinsic noise, i.e. systems broadly distributed in many physical, chemical and biological disciplines.

In this context, we recently discovered a new scenario of first-order phase transition that occurs via a complete inversion of the system energy landscape. This phenomenon was termed the “landscape inversion phase transition” (LIPT) and was observed by applying an external magnetic field to an assembly of paramagnetic colloids two dimensionally confined above a stripe patterned magnetic substrate.

On a different context, a recent breakthrough in optical manipulation of colloidal microspheres demonstrated the possibility to confine a cluster of particles into a circular assembly, and rotate the outer particle corona via laser tweezing. This colloidal model system was used as a microscopic clutch to investigate the transmission of torque through soft materials at the nanoscale.

Active Matter

We are interested in investigating propulsion of colloidal systems at the micro/nanoscale. We recently demonstrated that elongated DNA-linked paramagnetic colloids subjected to external precessing fields are capable to propel in a controlled way in viscous fluids. We will investigate how these micro-swimmers interact between each other and the role played by the hydrodynamic interactions. We will implement optical forces to test the swimmers’ performance and their constrained motion into microscopic pores or microfluidic networks.

Complex Fluids

Life Sciences

Biological systems, both for their intrinsic wealth and because of their importance, they receive special attention from the point of view of the study of complex systems. Much of the Institute's research activity is geared towards a great variety of problems in the biological context in all levels experimental, computational and theoretician. The research areas include the study of fundamental molecular mechanisms, genomics and proteomics, generation of forces and mechanics of cells and tissues, morphogenesis and development, biology of systems at the cellular level and neuroscience. In this case, the Institute has its own experimental laboratories. The associated studies at microorganisms and tissues have, from their fundamental perspective, a clear connection with the active materials that have begun to develop in recent years.

Systems Biology

Systems Biology is a growing research field that aims at characterizing and understanding living organisms from a systems level approach. The research performed at the UBICS within the field of Systems Biology uses mathematical and computational modelling, integrating methodologies from fields like dynamical systems and complex networks. Our research is mostly carried out in collaboration with wet laboratories or using reported public data. It is devoted to several different aspects of living systems. One aspect aims at understanding patterning and growth processes that underlie the development of multicellular organisms. Such studies range from embryonic animal development of vertebrates to plant growth. Another aspect focuses on the relationship between the large-scale architecture of the biological networks of interactions at different levels and their functionality.


All living neuronal networks, from the smallest neuronal culture up to brain, exhibit some sort of spontaneous activity patterns. The mechanisms that initiate and govern these spontaneous activations are focus of much attention since they arise from a complex interplay between intrinsic neuronal dynamics, connectivity among neurons and noise. To better comprehend these mechanisms and the actors at play, the Neuroscience group uses neuronal cultures as experimental model system to investigate not only the spontaneous activity itself, but its sensitivity to perturbations and circuit damage. Neuronal cultures are prepared from either rat brains or from human induced pluripotent stem cells (iPSC), and neuronal spatial arrangement is tuned through neuro-engineering tools to dictate specific connectivity blueprints. Activity is monitored through high-speed calcium imaging, and data analyzed in the framework of network theory and dynamical systems. For the former, we quantify the likelihood that any two neurons are influencing one another, a concept termed ‘effective connectivity’. The goal is to understand at which extend this effective connectivity reflects the physical one. For the latter, we quantify the spatio-temporal richness of activity fronts and their dependence on connectivity and noise. These analyses are combined with theoretical models and detailed numerical simulations, with the goal to dissect the key agents that trigger, shape, and maintain activity. Additionally, since alterations in spontaneous activity reflect damage at a neuronal or connectivity level, our research also includes the study of neurological disorders in vitro, and the development of neurophysics-based approaches to understand their progress, stop damage, and foster recovery.

Cell and Multicellular Biology

The biological cell is the basic unit of life, and constitutes by itself a remarkable complex system that combines thousands of chemical reactions of thousands of molecular species, all happening at the same time in a fascinating harmony within an extremely crowded and noisy environment. The current access to quantitative data enabled by modern technologies has revealed the cell a whole new universe to the eyes of physical inquiry and quantitative modeling. Understanding the physical mechanisms of self-organization that can integrate such variety of processes at very different scales and the information processing required to orchestrate them in response to external stimuli or to accomplish a variety of tasks required for survival, from metabolism to cell division, has thus posed a formidable challenge for interdisciplinary science. In this context, research at the institute focuses on different aspects of the physics within cells, with emphasis on collective effects and emerging phenomena. Among the aspects more amenable to physical modeling that are studied we can highlight those referring to force generation and mechanics of the cell, crucial for instance for cell motility or cell division, or for processes associated to membrane dynamics.

At a higher level of organization, we also study collective phenomena of cells in tissues. Here our emphasis is in mechanical aspects, and include the study of collective cell migration of epithelial cells, an area that is relevant to a variety of problems, related to wound healing, cell regeneration and ultimately to the understanding of cancer. The goal is to extract generic physical principles that govern the complex network of interactions both mechanical and biochemical, underlying these systems. At the multicellular level, the ultimate goal is to achieve an integration of mechanics and information in development, that is, to understand the organization of physical forces and biological regulation in the context of embryogenesis, organogenesis and beyond.

Molecular Biophysics

In the last decades, with the advent of nanotechnologies, it has been possible to probe and measure biological systems down to the molecular scale. This has allowed a more physical approach to traditional molecular biology, in particular in trying to solve the longstanding puzzles in the understanding of the basic behavior of biological building blocks, from the structure of proteins as a result of their folding dynamics, to the performance of molecular machines such as motor proteins.  In this context the institute develops an important line of research in single-molecule physics, which tries to understand the structural properties of important biomolecules through mechanical measurements on single molecules. Another line of research addresses collective effects of molecular motors, that is, how motor proteins cooperate in the performance of complex tasks, including the development of efficient strategies in intracellular transport and collective force generation, a problem that is directly relevant to medical applications for instance in neurodegenerative diseases.