Research

Exploring boundaries:
advancing data science at the intersection of disciplines

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Latest publications

Towards a global machine learning based impact model for tropical cyclones

Mersedeh Kooshki Forooshani, Marc van den Homberg, Kyriaki Kalimeri, Andreas Kaltenbrunner, Yelena Mejova, Leonardo Milano, Pauline Ndirangu, Daniela Paolotti, Aklilu Teklesadik, Monica L. Turner
Natural Hazards Earth System Sciences, 309–329, 24, 1, (2024)

Estimating household contact matrices structure from easily collectable metadata

Lorenzo Dall’Amico, Jackie Kleynhans, Laetitia Gauvin, Michele Tizzoni, Laura Ozella, Mvuyo Makhasi, Nicole Wolter, Brigitte Language, Ryan G. Wagner, Cheryl Cohen, Stefano Tempia, Ciro Cattuto
Plos One (2024)

What does a text classifier learn about morality? An explainable method for cross-domain comparison of moral rhetoric

Enrico Liscio, Oscar Araque, Lorenzo Gatti, Ionut Constantinescu, Catholijn Jonker, Kyriaki Kalimeri, Pradeep Kumar Murukannaiah
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics, 14113–14132, 1, (2023)

Unraveling the COVID-19 hospitalization dynamics in Spain using Bayesian inference

Alberto Aleta, Juan Luis Blas-Laína, Gabriel Tirado Anglés, Yamir Moreno
BMC Medical Research Methodology, 23, 24, (2023)

The Thin Ideology of Populist Advertising on Facebook during the 2019 EU Elections

Arthur Capozzi, Gianmarco De Francisci Morales, Yelena Mejova, Corrado Monti, André Panisson
WWW ’23: Proceedings of the ACM Web Conference 2023, 2852–2862, (2023)

The Pursuit of Peer Support for Opioid Use Recovery on Reddit

Duilio Balsamo, Paolo Bajardi, Gianmarco De Francisci Morales, Corrado Monti, Rossano Schifanella
Proceedings of the International AAAI Conference on Web and Social Media, 17, (2023)

Towards a global machine learning based impact model for tropical cyclones

Mersedeh Kooshki Forooshani, Marc van den Homberg, Kyriaki Kalimeri, Andreas Kaltenbrunner, Yelena Mejova, Leonardo Milano, Pauline Ndirangu, Daniela Paolotti, Aklilu Teklesadik, Monica L. Turner
Natural Hazards Earth System Sciences, 309–329, 24, 1, (2024)

Estimating household contact matrices structure from easily collectable metadata

Lorenzo Dall’Amico, Jackie Kleynhans, Laetitia Gauvin, Michele Tizzoni, Laura Ozella, Mvuyo Makhasi, Nicole Wolter, Brigitte Language, Ryan G. Wagner, Cheryl Cohen, Stefano Tempia, Ciro Cattuto
Plos One (2024)

At ISI Foundation, fundamental and applied research is carried out with an interdisciplinary, problem-driven approach. The scientific activity of the Foundation focuses on the frontiers of data science, computational modeling and their impact on society, integrating ideas and tools from multiple interrelated fields that span Complex Systems Science, Network Science, Artificial Intelligence, and Computational Social Science.

The Foundation stands as a crossroads of disciplines and expertise, advocating for the exchange and integration of knowledge and embracing an approach that transcends, by design, established disciplinary boundaries.

ISI Foundation facilitates and supports dialogues between data owners (industry, public administration, citizens), knowledge actors, and impact stakeholders (global agencies, public administration, nonprofits), fostering collaborative efforts to uncover knowledge and design innovative solutions for outstanding challenges in public health and sustainable development.

The researchers of the Foundation pursue their own path of inquiry with broad freedom, exploring the subject areas and topics they deem most promising to tackle the complex challenges of our times.

Artificial intelligence

Computational Social Science

Health

Network science

Sustainable development

Other fields

respicast

Social Impact
and sustainable development

Scientists at ISI Foundation investigate problems where quantitative knowledge has the potential to positively impact society. This includes leveraging both conventional and unconventional data sources to identify societal challenges, and employing a combination of mathematical modeling and artificial intelligence to conceptualize various scenarios and drive effective policies. Focus areas include, but are not limited to, public health, inequality and poverty, gender equality, humanitarian response, the quality of democracy, the future of cities, human mobility, and the various facets of sustainable development.

Each of these impact directions is daunting and requires access to relevant domain expertise. To this end, the Foundation leverages its institutional and professional network to weave collaborations and partnerships to access relevant datasets and domain expertise, and to direct its research along directions that matter. Capitalizing on its culture of rigorous mathematical modeling of complex systems, the Foundation aims at producing explainable research output, to better support responsible and inclusive decision-making.

Related Projects

Computational and mathematical modeling for envisioning a better future

The Foundation’s approach is deeply rooted in the mathematical modeling culture derived from statistical physics and complex systems science. It integrates ideas and modern methods from data science, network science, and artificial intelligence. These combined skills facilitate the development of new ways to understand the progression of socio-technical systems. Integrating heterogeneous data layers into computational frameworks, the foundation focuses on the assessment of the impact of decisions and policies, which are instrumental in shaping strategies for improved societal outcomes.

Central to the ISI Foundation culture is the creation of models that are both explainable and transparent to support decision-making in the face of uncertainty and complex relations between decisions and outcomes.

Public Health

Health is a crucial domain where the effectiveness of research directly impacts collective societal well-being. Through its initiatives, the ISI Foundation has emerged as an international reference for the study and modeling of epidemics and pandemics and for devising effective policy responses. Its pioneering expertise is centered on computational and digital epidemiology, along with the design and development of comprehensive disease monitoring and forecasting tools. These tools are adopted by European and global health agencies, including the European Center for Disease Control and the World Health Organization.

Related Projects

Lagrange Project

Lagrange Laboratory

CRT Foundation, a co-founding partner and main funder of the institute, supports the work of ISI Foundation through a targeted initiative, the Lagrange Project, that comprises research, training and community building actions. The research and innovation component of the Lagrange Project is the Lagrange Laboratory and is organized in four broad interdisciplinary areas: Computational and Digital Epidemiology, Computational Social Science, Data for Social Impact and Sustainability, Complex Systems and Data Science.

Horizon Europe

European Projects

An active role in research, innovation, and collaboration

ISI Foundation takes part in many collaborative projects supported by the European Commission’s competitive funding frameworks for research and innovation, and it is the recipient of targeted tenders by European agencies. Over the course of the last decade, the partnership network of the Foundation has comprised more than 150 partners across most EU countries, creating a lasting network of exchanges that has brought many of those partner institutions to visit the city of Turin, and has provided young researchers with international career opportunities.

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