Maria d'Errico

photo I have a PhD in experimental high energy physics from the University of Padova (2011), with a thesis on the search for a high-mass Higgs boson produced in p p-bar collisions. During my formation I spent two years (2008-2009) at Fermi National Accelerator Laboratory (Chicago, USA) as an International fellow, working on the data analysis for the CDF experiment which included Monte-Carlo simulations and the use of multi-variate techniques for signal reconstruction in large background environments.

In the last few years I became interested in Statistical Physics and its wide reach. Since I started my activity in SISSA I worked on understanding the effects of financial speculation on food commodity markets, characterizing their equilibrium and dynamics by means of data mining techniques. In collaboration with Alessandro Laio (SISSA), Guido Chiarotti (ISC-CNR, Roma) and Claudio Tebaldi (Bocconi, Milano), we developed a stylized model of production and exchange of a food commodity [1].

Since 2014, in collaboration with Alessandro Laio and Alex Rodriguez, I have been working on disentangling complexity patterns in biological systems, with the aim of understanding how complex ecological systems are driven toward specific organizations. We performe cluster analyses using a new unsupervised and adaptive density estimator [2] and a generalized version of a recently developed clustering approach [3] in order to automatically recognize sets of data points organized in clusters, regardless of the dataset characteristics (i.e. space dimensionality, shape of the clusters, distance metrics). The final goal is to derive a reduced network model in which the nodes are the resulting clusters, with the links quantifying the intensity of their mutual interaction. Possible applications include food-web, mutualisms and host-parasite networks.

[1] M. d'Errico, A. Laio, C. Tebaldi and G. Chiarotti, "The impact of financialization on agricultural commodity production and farm liquidity risk management" (In preparation).
[2] M. d'Errico, A. Laio, E. Facco and A. Rodriguez, "An accurate and unsupervised density estimator for highly inhomogeneous datasets" (In preparation).
[3] A. Rodriguez, A. Laio, Science, 2014, 344, 1492-1496.