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2018-12-03, CfP: 'Social data and medical data analytics'
Special Track at the IEEE Computer-Based Medical Systems 2019, June 5-7, Cordoba, Spain. For more information, please check the official website!
2017-06-27, CfP "Entropy-based Data Mining".
Together with Ernestina Menasalvas (UPM, Spain), we are preparing a special issue on entropy and data mining in the MDPI's journal Entropy. If you have used entropy-based measures to classify things; or if you have designed a new classification algorithm based on entropy, have a look at the Call for Papers. Please real all the details here!
2016-12-28, Open PhD position.
We have an open PhD position, on data analysis for safety in aviation. Please real all the details here! P.S.: You do not need to apply through LinkedIn, just send an email to the included address.
2016-11-28, COST action call for STSM.
We have recently launched a call for Short Term Scientific Missions, inside the COST Action I'm part of. If you are interested in multi-scale modelling in biology and medicine, please check this link!
2016-05-23, Complex networks, data minign and causality
During the last weeks, I've published two papers that may be of interest to all complex systems researchers - and beyond.
The first one is a large review on the combined use of complex network theory and data mining. Not only do complex network analysis and data mining share the same general goal, that of extracting information from complex systems to ultimately create a new compact quantifiable representation, but they also often address similar problems too. In spite of this, a surprisingly low number of researchers turn out to resort to both methodologies, and one may then be tempted to conclude that these two fields are either largely redundant or totally antithetic. In this review, we challenge this perception, show how this state of affairs should be put down to contingent rather than conceptual differences, and that these two fields can in fact advantageously be used in a synergistic manner. The review starts by presenting an overview of both fields, and by illustrating some of their fundamental concepts. A variety of contexts in which complex network theory and data mining have been used in a synergistic manner are then presented. Finally, all discussed concepts are illustrated with worked examples through a series of hands-on sections, which we hope will help the reader to put these ideas in practice. If you ever wonder how a real-world problem can be tackled by these two techniques, you should definitively read this review!
The second paper tackles a rather disturbing problem. We know that correlation is not causality - or, at least, you should know it! Following this idea, many causality metrics have been proposed in the literature, all sharing a same drawback: they are defined for time series. In other words, the system (or systems) under analysis should display a time evolution. Associating causality to the temporal domain is intuitive, due to the way the human brain incorporates time into our perception of causality; nevertheless, such association creates some rather important problems. For instance, suppose one is trying to detect if there is a causality relation between the workload of an ATC controller, and the appearance of loss of separation events. These events are only defined at one point in time: one can detect an instance of a loss of separation, and check the corresponding workload; afterwards, do the same for another event; and so forth. At the end, the researcher would get two vectors of features, which do not encode any temporal evolution - in other words, consecutive values are not correlated. So, in this situation, how can we detect if a true causality (and not just a correlation) is present? In this work I propose a novel metric able to detect causality within static data sets, by analysing how extreme events in one element correspond to the appearance of extreme events in a second one. The metric is able to detect non-linear causalities; to analyse both cross-sectional and longitudinal data sets; and to discriminate between real causalities and correlations caused by confounding factors.
If you are interested in these ideas, feel free to have a look at these two papers:
M. Zanin et al., Combining complex networks and data mining: why and how. Physics Reports (2016), pp. 1-44. http://authors.elsevier.com/a/1T3yF_8QfbYE-k.
M. Zanin, On causality of extreme events. PeerJ. Also available at: http://arxiv.org/abs/1601.07054
2016-02-22, New software available
I've added several software libraries, complementing several papers that I've recently published. Feel free to use them in any of your researches - of course, citing the corresponding paper! Please refer to the software page for further information.
2015-04-24, Call for Papers, Complexity Science and Transportation Systems ‘15.
Satellite Meeting at the Lipari School on Complex Systems 2015, Lipari Island, July 12th-18th 2015. Following the events organized at the ECCS ’11 in Vienna, ECCS ’12 in Brussels ECCS ’13 in Barcelona and ECCS ’14 in Lucca, we announce the Call for Papers for a half-day Satellite Meeting “Complexity Science and Transportation Systems” within the Lipari summer school on Complex Systems. The aim of this Satellite Meeting is to create a space for exchanging state-of-the-art results and ideas about (i) how different Complex Systems tools such as complex networks, percolation theory, self-organized criticality or agent based modeling can be used to understand the internal dynamics of transportation systems, (ii) how to model the relationships between different transportation modes, and (iii) how to improve efficiency and performance of such systems. More information can be found here.
2015-02-23, New Interactive Papers section.
A new section is now available: the Interactive Papers! Here I'm going to publish those results that cannot easily be expressed in a static image, like interactive maps, high-dimensional and time-evolving graphs. Feel free to play with the data your way!
2014-05-02, CfP - Computation beyond the Boolean world.
We are organizing a Research Topic in the journal Frontiers in Computational Neuroscience, about non-classical computation paradigms and their relation with brain dynamics. Check the CfP is you are interested!
2013-03-08, New software for fast motifs enumeration.
A new software section has been added. As a first item, you can find a software for the enumeration of 3-nodes motifs, which outperforms comparable algorithms in medium-size dense networks. Have a look at it!
2012-09-05, Optimization of network reconstructions.
If you work in the field of network representations of biomedical data (e.g., EEG and MEG), you should not miss our latest publication in Nature Scientific Reports. You can download it here.
2012-08-23, A review on Permutation Entropy published!
After several months of work, we have finally published a review about Bandt and Pompe Permutation Entropy: you can download it from here.
2011-09-06, 2011-09-06, Complex Networks Analysis of Obstructive Nephropathy Data on Physics Today
My last paper published, "Complex Networks Analysis of Obstructive Nephropathy Data", in collaboration with Stefano Boccaletti, has been included in the section Physics Updates of the journal Physics Today.
The resume can be found in the Physics Today website!
2011 09 01, CFTS Program published!
The Program and the Abstract Booklet of the Complexity and the Future of Transportation Systems Satellite Meeting has been published.
For further information, check the Meeting website!
2011 03 17, CfP: Complexity and the Future of Transportation Systems.
Fabrizio Lillo (University of Palermo, Santa Fe Institute, and Scuola Normale Superiore) and I are organizing a Satellite Meeting in the European Conference on Complex Systems 2011, titled Complexity and the Future of Transportation Systems.
The aim of this one day Meeting is to create a space for exchanging state-of-the-art results and ideas on this interesting topic, i.e., how different Complex Systems tools, as complex networks, percolation theory, self-organized criticality and agent base modeling, can be used to understand the internal dynamics of transportation systems and improve their performance.
If you are interested in this topic, check the Meeting website!
2011 01 01, Start of the new website.
Here we are, with the second version of this website! I hope to keep it more updated in the future, with papers and contributions published around the world. The whole structure has been reorganized, with a special focus on the researches I am performing in my work... Hope you find it useful!