Projects

Inequality is one of the most important problems in our societies. For example, economic inequality is today higher than it was in the 1970’s and by some metrics stands at levels not seen since the last Great Depression. A special form of segregation is that happening in our cities. We share the public places, our workplaces and our residential neighborhoods with people like us: same type of jobs, same education, similar economic status, and political opinions. ...

Our behavior conditions our health. Exposure to infections depends on our and other people’s mobility. Exposure to healthy environments or habits depends on our choices and opportunities. Although human behavior is highly adaptive and dynamic, most social determinants of health are restricted to static aggregated representations of socio-demographic groups or residential environments. We have started a program to understand behavioral-network determinants of health outcomes by modeling physical exposure between people and environments using large datasets of human mobility and activity and multilayer networks. ...

Like ecosystems, societies with adaptable economies are best prepared for the future. We started a research program to understand and detect economic resilience encoded in the dependency networks of agents, businesses, cities, or jobs. In particular, how much of the adaptability of our economies depends on the fragility of those economic networks? Can we identify weaknesses and design policies to strengthen those interdependent units? Using highly detailed information about jobs, skills, and cities, our foundational study extended traditional economic models to show that the network structure of interactions and flows between jobs determines the resilience of labor markets. ...

Temporal, structural and activity patterns in social networks are related to human behavior. Thus, networks do have different shape and dynamics under different exogenous and endogenous shocks or conditions. In the last years we have addressed the question of whether we can use our understanding of social networks to anticipate, predict or measure important phenomena as information propagation, disaster damage, unemployment shocks, weather conditions, gender digital divide, etc. For example in a series of papers, we demonstrated for the first time the ability of the so-called “friendship paradox” in social networks to get better collection of users (sensors) that can anticipate meme, news or event-related information propagation in networks. ...

We live in a networked society and our actions, opinions, behaviors are affected and can affect other people. Understanding such social networked structures is one of the key challenges in our attempt to decode human behavior and its impact in our society. Although human interactions are dynamical by nature, most of our understanding relies in static representations of those social networks. However, social interactions are rarely static. Very often the networks evolve by means of processes that happen at diverse time scales, like link decay/formation, group formation, etc. ...

Human decision making strategies evolve through time based on past experience and they are influence by the spectrum of other strategies with which they come into contact. Financial markets provide the best empirical lab to understand how human decide under risk and uncertainty. They are complex systems which provide massive datasets of detail records of human decisions which constantly evolve and collide in centralized or social structures. Furthermore financial markets provide us with a very simple measure of performance (profits, ROI), thus enabling us to study the relationship between human decision making strategies and performance. ...