Jean-Denis Gabano

Jean-Denis Gabano serves as an Associate Professor specializing in Automatic Control and Systems at the University of Poitiers. He maintains dual affiliations with the Laboratory of Automated Systems Engineering (LIAS) at both ENSIP (École Nationale Supérieure d'Ingénieurs de Poitiers) and ISAE-ENSMA campuses, reflecting his integrated role across these engineering institutions. His research program bridges theoretical control systems with practical industrial applications, particularly in energy storage technologies.

Dr. Gabano's research expertise centers on fractional-order calculus applications for modeling complex physical phenomena. His work primarily focuses on electrochemical systems, particularly battery impedance characterization across time and frequency domains, and thermal system identification. He has developed sophisticated identification algorithms that enable precise modeling of diffusion processes in batteries and heat transfer in thermal systems. His methodological innovations in fractional-order modeling have significant implications for improving battery management systems and thermal control in industrial applications.

Analysis of his publication record reveals a clear research trajectory evolving from fundamental thermal system identification toward increasingly sophisticated battery impedance modeling. His most recent work (2023-2024) demonstrates advanced applications of fractional calculus to lithium-ion battery characterization, addressing critical challenges in impedance spectroscopy and parameter estimation. The interdisciplinary nature of his research connects control theory with electrochemistry and materials science, yielding practical methodologies for energy storage system optimization.

Dr. Gabano leads research within the Automatic Control team at LIAS laboratory, focusing on developing advanced system identification methods using fractional calculus. His research group maintains strong collaborative ties with industry partners, particularly in the energy sector, to translate theoretical developments into practical engineering solutions. Current projects emphasize time-domain identification techniques as alternatives to traditional frequency-domain approaches, potentially reducing testing time for battery characterization while maintaining accuracy.