The ISI Foundation is looking for excellent candidates at all levels of seniority to join the Learning and Algorithms for Data Analytics research area, to contribute to both fundamental and applied research projects.

Contact tracing, both manual and potentially with digital apps, is considered a key ingredient in the control of infectious disease outbreaks. During the ongoing COVID-19 crisis, for example, it has been widely considered, discussed, and experimented in the strategies making it possible to alleviate the lockdown and to return to a quasi-normal functioning of society. However, the current leading modeling framework for evaluating contact tracing is highly stylized, lacking important features and heterogeneities present in real-world contact patterns that are relevant for epidemic dynamics.

Social media may limit the exposure to diverse perspectives and favor the formation of groups of like-minded users framing and reinforcing a shared narrative, that is, echo chambers. However, the interaction paradigms among users and feed algorithms greatly vary across social media.

Humans can effortlessly perform many kinds of task at the same time, such as walking, talking and responding to their surroundings, all of which presumably involve extensive simultaneous computations. On the other hand, they are radically constrained in their ability to perform other kinds of task concurrently, such as planning a grocery list while simultaneously carrying out multidigit mental arithmetic. As recent work has suggested, these fundamental features of human cognitive function may be explained by a tradeoff between two kinds of use of parallel distributed computing in network architectures: the first focuses on incorporating a variety of interacting constraints in the learning and processing of complex representations (“interactive parallelism”); the second kind, in contrast, focuses on the capacity of a network to carry out multiple processes independently (“independent parallelism”).

Public opinion polarization is on the rise, as suggested by data collected across a variety of political and ethical issues. Opinions on different topics can also be correlated: Individuals advocating rights for transgender people, for example, are likely to also support same-sex couples. Strikingly, data shows correlations also between unrelated topics, such as rights of transgender people and the debate about whether the U.S. should build a wall at the border to Mexico.

Since 2008, every Autumn has been marked by the celebration of the Lagrange-Fondazione CRT Award, promoted by the Fondazione Cassa di Risparmio di Torino and coordinated with the scientific advice of Fondazione ISI.

Organized by the Complex Systems Society, the Conference on Complex Systems is the most important annual meeting of the international complex systems community. CCS 2020 will be online, from 7 to 11 December on Zoom, and several ISI Foundation researchers will join its main programme and satellite sessions.

Can your Facebook friendships help in predicting your next phone call? While network science is a pivotal tool to characterize the structure of real world complex systems, link prediction algorithms can help to reconstruct networks from incomplete data sets and to forecast future interactions in evolving networks. Facebook, indeed, is a good example of how the second task may be routinely applied on online social networks.

Big Data, salute e impatto sociale: Fondazione ISI alla Biennale Tecnologia di Torino

ISI Foundation partner of Periscope, a new H2020 project funded by the European Commission to understand social, economic, behavioural and mental health related aspects of the COVID-19 pandemic

I modelli epidemiologici predittivi sono modelli matematici che individuano alcuni parametri chiave e, analizzando i dati disponibili, propongono scenari possibili sull’andamento di un'epidemia. Prima dell'arrivo del Covid-19, questi modelli erano conosciuti soprattutto dagli addetti ai lavori: gli scienziati che li sviluppavano e i sistemi sanitari che li utilizzavano per la prevenzione e il controllo delle epidemie (come avvenuto con successo, per esempio, nei casi di Ebola e Zika).

Low-dimensional embeddings, from classical spectral embeddings to modern neural-net-inspired methods, are a cornerstone in the modeling and analysis of complex networks.

Lunedì 12 ottobre saranno presentati i risultati del lavoro degli otto borsisti Lagrange attualmente al lavoro presso OGR, dove Fondazione ISI e Fondazione CRT hanno stabilito un centro focalizzato su "Data Science for Social Good".

È online “Eventi e Covid-19”, piattaforma che stima il rischio di presenza del virus in eventi collettivi

Covid doesn't stop WiDS . For the third consecutive year, ISI Foundation is one of the 75+ locations worldwide hosting the Stanford Women in Data Science conference. The event for women leadership and innovation will take place online, Monday 28th September.

ISI Foundation is joining NetSci 2020, the flagship conference of the Network Science Society, taking place online from 17 to 25 September, with a strong participation in satellite symposiums and main conference talks.

Se vogliamo una vita normale dobbiamo imparare a vedere l’invisibile e capirne i rischi. Solo così il virus sarà sempre in un angolo. Il vero coraggio non è fare finta di niente, immaginare che tutto sia tornato alla normalità. E’ guardare negli occhi il nemico e rispettarlo

The complexity of many biological, social and technological systems stems from the richness of the interactions among their units. Over the past two decades, a great variety of complex systems has been successfully described as networks whose interacting pairs of nodes are connected by links.

From ending hunger and poverty to overcoming gender inequalities, from ensuring quality education to tackling sustainability issues, the 17 Sustainable Development Goals (SDGs) adopted by all United Nations Member States in 2015 constitute a roadmap of the broad set of challenges that our society is facing today.

Le simulazioni al computer permettono di anticipare e seguire la trasmissione di malattie nel mondo, suggerendo le mosse per affrontare patogeni in grado di scatenare crisi sanitarie globali 

Populations of mobile agents, such as animal groups, robot swarms, or crowds of people, exhibit fascinating collective behaviors as a result of the spread of information, like a potential threat or opportunity.

The annual KDD conference is the premier interdisciplinary conference bringing together researchers and practitioners from data science, data mining, knowledge discovery, large-scale data analytics, and big data. The 26th edition of KDD is being held as a virtual conference, with online talks and panels, from 23rd to 27th August 2020.

An interacting group of people, the collectively active neurons in the brain, or the transportation system of a city. These are examples of complex systems, which are all intrinsically dynamical. They can be commonly interpreted as a set of entities, which interact over time and form a network structure coding the architecture of the system in hand.

Mobile data collection, data analysis through artificial intelligence,  the use of satellite imagery in creating detection models to identify informal settlements and calculating poverty, and - as it's happening in the COVID-19 global crisis - the development of new models to predict and evaluate the evolution of a pandemic emergency and the effects of public health interventions.

On February 21, 2020, a cluster of SARS-CoV-2 cases was officially reported in the province of Lodi, marking the beginning of the COVID-19 pandemic in Italy.

What can digital and computational approaches reveal about the relationships between mortality, fertility, mobility, and the spread of COVID-19?

Cities are not gender-neutral, nor is urban mobility. In a new paper out in Humanities and Social Science Communications, an international team of researchers, including ISI Foundation Ciro Cattuto, Laetitia Gauvin, Michele Tizzoni, Stefaan Verhulst and Simone Piaggesi, analyzes call detail records for a large cohort of anonymized mobile phone users, to reveal a gender gap in mobility.

Sometimes it takes a lot of time. After eight years working at the interface of topological data analysis and network theory, ISI  Foundation Senior Research Scientist Giovanni Petri has led an international team of researchers, including former ISI Junior Researchers Alice Patania and Iacopo Iacopini, to compile, elaborate and present one of the first complete overviews of the emerging field of networks beyond pairwise interactions.

Why do Trump supporters support Trump? How was his political campaign able to attract a large support, ultimately reshaping the U.S. political landscape?