Alberto Pinto (mathematician)

He is a researcher of the Laboratory of Artificial Intelligence and Decision Support, Institute for Systems and Computer Engineering LIAAD, INESC TEC.

[4] During this time Pinto met a number of the leaders in dynamical systems, notably Dennis Sullivan and Maurício Peixoto, and this had a great impact on his career.

With de Melo he proved the rigidity of smooth unimodal maps in the boundary between chaos and order extending the work of Curtis T. McMullen.

This appeared in the research article "Global Hyperbolicity of Renormalization for Smooth Unimodal Mappings" published at the journal Annals of Mathematics (2006) and was based in particular in the previous works of Sandy Davie, Dennis Sullivan, Curtis T. McMullen and Mikhail Lyubich.

He has contributed across a remarkably broad area of science including optics, game theory and mathematical economics, finance, immunology, epidemiology, and climate and energy.

[9] He edited with David Zilberman[10] the volume entitled "Optimization, Dynamics, Modeling and Bioeconomy I" (2015) that will appear at Springer Proceedings in Mathematics & Statistics series.

[11] Pinto with Michel Benaïm founded the Journal of Dynamics and Games (2014) of the American Institute of Mathematical Sciences (AIMS) and they are the editors in chief.

[1][13] Pinto has made numerous significant scientific research contributions that are recognized internationally in the field of dynamical systems, game theory and applications.

Citing the words of Jacob Palis and Enrique Pujals[15] in the preface of Pinto–Ferreira–Rand's Springer monograph: "All the smooth conjugacy classes of a given topological model are classified using Pinto's and Rand's HR structures".

Pinto and Rand's Nonlinearity paper proved the existence of a universal constant 2.11 that is the degree of smoothness of the conjugacy between infinitely renormalizable unimodal maps.

Pinto's paper in JDG created new models to study the appearance of sudden social and political disruptions using the replicator equation in the theory of planned behavior.