EU framework program COST Action IC1408 on “Computationally intensive methods for the robust analysis of non-standard data” – Open Call Full Proposal oc-2014-1-19052 Funded.
Directed by Prof. Prof. Erricos Kontoghiorghes, Cyprus University of Technology. Status: funded

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Real data sets from a wide variety of fields violate the idealized assumptions inherent in standard statistical theory. Robust data analysis methodology aims to mitigate the impact of such violations. Robust methods are usually developed to handle multivariate data. However, monitoring studies often contain information such as functional, set-valued, or different kinds of incomplete data. Robust methods for these complex data types are scarce and involve critical computational challenges. New models, methods and efficient, numerically stable, and well-conditioned robust strategies are essential to improve knowledge extraction from non-perfect and non-standard datasets. Applications include the analysis of climate data, medical monitoring and diagnosis, trading and financial forecasts. The aim is to create an interactive network spanning computing, statistics, machine learning, and mathematics with the necessary expertise required to develop such strategies in close collaboration with end-users. Software and guidelines will be developed. The Action will provide European scientists with cutting-edge data analysis tools which will be suitably disseminated by disparate means such as training schools, conferences and publications. Improved decision-making tools for preventing-mitigating policies will be derived. Thus, scientific, technological and social challenges will be tackled by the creation of a proper framework to coordinate and optimize research efforts.


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Internal Deutsche Bundesbank Project on Digital Currencies and Cyber Risks. Status: approved

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EU framework program ITC FET Open Call FP7-ICT-2009-C FOC Project: Forecast of Financial Crises. Measurements, Models and Predictions. Funded. Directed by Prof. Dr. Guido Caldarelli (CNR, Rome and ETH, Zurich). Status: funded.

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In this project, an interdisciplinary consortium of computer scientists, physicists, economists and policy makers has benn set up to deal with the problem of understanding and forecasting systemic risk and global financial instabilities. By leveraging on expertise in the various disciplines, the aim is to provide a novel integrated and network-oriented approach to the issue. On one hand, a theoretical framework to measure systemic risk in global financial market and financial networks is offered. On the other hand, an ICT collaborative platform for monitoring systemic fragility and the propagation of financial distress across institutions and markets around the world is delivered. Experts will be able to evaluate algorithms and models to forecast financial crises as well as visualise interactively possible future scenarios.


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Swiss National Science Foundation project on OTC Derivatives and Systemic Risk in Financial Networks – Reg. Number CR12I1-127000/1. Funded. Directed by Prof. Dr. Dr. Frank Schweitzer (ETH, Zurich). Status: funded.