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Valentina Sessa
Associate Professor (Chargée d'enseignement recherche) - HDR
Mines Pairs - PSL - CMA (Centre de Mathématiques Appliquées), Sophia Antipolis, France
email: sessa.valentina@gmail.com/valentina.sessa@minesparis.psl.eu
I was born in Avellino, Italy, in 1983.
I received the Master degree in automatic control engineering and the PhD degree in information engineering from University of Sannio, Benevento, Italy, in 2010 and 2013, respectively. In 2012 I was a visiting student at INRIA Rhône-Alpes, France.
After one year of Postdoctoral Fellowship at the Department of Engineering, University of Sannio, I had a postdoctoral position at IMPA (Instituto Nacional de Matemática Pura e Aplicada), Rio de Janeiro, Brazil.
From August 2015 to June 2017, I was Assistant Professor at the Department of Electronic and Telecommunications Engineering at State University of Rio de Janeiro (UERJ), Brazil, where I taught two courses: Automatic control and Mathematical model for electrical engineering.
From October 2018 to December 2020, I was Ingénieur de recherche at Mines ParisTech, Sophia Antipolis, where I collaborate on the European Project, called Clim2Power.
My current research interests include analysis of nonsmooth dynamical systems, in particular, piecewise linear and complementarity systems; modelling and control of power electronic converters; numerical algorithms for complementarity problems; global optimization. Lately, I got interest also for machine learning applied to energy problems.
Recent updates:
Amir Tavakoli (co-supervised with Sophie Demassey) awarded with EDSTIC Doctoral Prize in COP/ELEC/SN specialities (thesis)
Habilitation à Diriger des Recherches (HDR) defended on September 6, 2024 (slides)
Guest editor for: Applied Set-Valued Analysis and Optimization (ASVAO) - Submission deadline for papers: May 31, 2024 Closed
PhD Position: Mathematical programming with equilibrium constraints: models and algorithms for nonconvex optimization - Application deadline: May 30, 2024 Closed
Ongoing Project: Matrices, Optimization, and Randomness with Applications in Data Science - MATH- AmSUD