Irene Malvestio received both her bachelor’s degree in Physics and her master’s degree in Theoretical Physics from the Università degli Studi di Padova. Her bachelor’s thesis was a study on the robustness of complex networks. Her master’s thesis was titled “Validation of statistical models of spatial flows” and was supervised by Prof. Amos Maritan. Irene completed the work for her thesis at the University of Bristol, where she was a visiting student in the Department of Engineering Mathematics, working under the supervision of Prof. Filippo Simini. Her research aimed to develop a set of statistical methods based on nonparametric regression and scaling techniques that allows understanding of whether a given class of models is compatible with a set of observed flows. In 2015 Irene started her PhD research project, titled “Using nonlinear interdependence measures to detect directional couplings in networks” which is jointly supervised by Prof. Ralph G Andrzejak at Universitat Pompeu Fabra and Prof. Thomas Kreuz at the University of Florence.
Irene Malvestio, Thomas Kreuz, and Ralph G. Andrzejak “Robustness and versatility of a nonlinear interdependence method for directional coupling detection from spike trains” Phys. Rev. E 96, 022203 (2017) LINK
Satuvuori E., Mulansky M., Bozanic N., Malvestio I., Zeldenrust F., Lenk K., Kreuz T. “Measures of spike train synchrony for data with multiple time scales” 2017 Journal of Neuroscience Methods (287) 25-38 LINK
Andrzejak R. G., Ruzzene G., and Malvestio I. “Generalized synchronization between chimera states” Chaos 27, 053114 (2017) LINK
Irene Malvestio, Thomas Kreuz, Florian Mormann, Ralph G. Andrzejak “Using a non-linear interdependence approach to detect directional coupling from spike trains” Neuroscience 2017, Washington DC, WA United States, November 2017. Poster
Irene Malvestio, Thomas Kreuz, Ralph G. Andrzejak “Versatility of a nonlinear interdependence method for directional coupling detection from spike trains” 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Jeju island, South Korea. July 2017. Poster
Irene Malvestio, Thomas Kreuz, Ralph G. Andrzejak “Nonlinear interdependence detection from spike trains” XXII National Conference on Statistical Physics and Complex Systems, University of Parma, June 2017. Talk
Irene Malvestio, Marc Grau, Eero Satuvuori, Gloria Cecchini, Rok Cestnik: ” Inferring network connectivity: open questions and some answers”. 2nd COSMOS Workshop, Amsterdam, Dec. 2016 (Talk)
Laiou P., Malvestio I. and Andrzejak R. G. “The asymmetric state similarity criterion: a versatile feature to detect directional couplings from signals” Advances in the collective behaviour of complex systems. University of Potsdam, Potsdam, Germany. September 2016. Poster.
Malvestio I. and Andrzejak R. G. “Robustness to noise of couplings detection method between spike trains” Barcelona Computational and Systems Neuroscience (BARCCSYN). Barcelona, Spain. June 2016. Poster
Malvestio I. and Andrzejak R. G. “Detecting couplings between spike trains with noise” International Conference on Biological Oscillations. Lancaster, UK. April 2016. Poster
Malvestio I. and Andrzejak R. G. “Detecting unidirectional couplings between point processes” Doctoral Student Workshop. Universitat Pompeu Fabra, Barcelona, Spain. March 2016. Poster