Stefano Tognazzi

We envisage a revolutionary change in the approach to spambot detection: instead of taking countermeasures only after having collected evidence of new spambOT mischiefs, in a near future techniques will be able to anticipate the ever-evolving spammers. Expand

We propose and experiment with a novel genetic algorithm for the synthesis of online accounts. Expand

In this paper, we experiment with a novel ad-hoc genetic algorithm that allows to obtain behaviorally evolved spambots. Expand

We develop a genetic algorithm for CRNs called influence networks, which can be used to model a variety of biological systems including cell-cycle switches and gene networks. Expand

We investigate the relationship between centrality measures and model reduction techniques, such as lumpability of Markov chains, which seek to reduce a model into a smaller one that can be processed more efficiently, while preserving information of interest. Expand

We present backward invariance, which relates DAE variables that have equal solutions at all time points (thus requiring them to start with equal initial conditions) and extend the line of research on backward-type bisimulations developed for Markov chains and ordinary differential equations. Expand

We extend backward differential equivalence on ODEs to a notion of equivalence that relates DAEs variables that have equal solutions at all time points. Expand

Multi-Layer Networks (MLN) generalise the traditional, single layered networks, by allowing to simultaneously express multiple aspects of relationships in collective systems, while keeping the description intuitive and compact. Expand

This paper explores the use of Binary Decision Diagrams (BDDs) in Conformant Planning. Expand