Over his career, Matteo Brilli has steadily built a multifaceted experience in several aspects of microbiology, genomics, systems biology, and bioinformatics.
Since the very early stages of his studies, Matteo started
programming capability, which later on he further developed up to the point of currently
being a proficient programmer in multiple languages (Matlab, R, Java). These competencies led him to build
up a portfolio including several pieces of software (Brilli et al., 2008, Brilli et al., 2006, Chiodi et al. 2019). Over his postdoctoral appointments, which he held in Florence (Italy),
Cambridge (UK), and Lyon (France), he continued gaining new experiences in multiple fields of
bioinformatics, from network science to mathematical modeling of dynamic systems (Klein et al. 2012, Berthoumieux et al., 2013).
Matteo has been involved in several comparative genomics studies for symbionts (Brilli et al. 2018, Otten et al. 2018, Galardini et al. 2013) and pathogens (Piazza et al.
2018 a and b) and is first author of a pioneering study implementing a dual-multi-omics study of the grapevine-Plasmopara viticola pathosystem (Brilli et al. 2018).
Matteo is currently leading a group at the University of Milan, where he holds a position as Assistant Professor. He is currently using machine learning and dynamical modeling approaches to integrate genomics and metagenomics data with additional information aiming at the disclosure of associations between
environmental or host factors and the resident microbial communities. In a short period of time, the group has already developed a tool exquisitely useful in metagenomics analyses, SeqDex, allowing the deconvolution of genomic sequences in mixed NGS samples (Chiodi et al. 2019).

Systems biology
dynamical systems
modelling
machine learning
comparative genomics