Special Seminar: Antônio J. Silva Neto

An Overview on Inverse Problems Formulations and Solutions

Abstract:

Parameters or functions used in the modelling of systems and processes, for several relevant applications in engineering and science in general, may be unknown. But, partial experimental data on observable indirect quantities may be available. Using the inverse problem approach there is a link between models and experiments, allowing the determination of the unknowns of interest. The parameters and functions involved in the models present random variations, and the experimental data is always contaminated by random noise. Such characteristics should be taken into account in the formulation and solution of inverse problems. In this talk, inverse problems in engineering and environmental modelling are presented considering different formulation approaches and solution techniques.

Antônio J. Silva Neto is a Full Professor in the Department of Mechanical Engineering and Energy, Polytechnic Institute, Rio de Janeiro State University. He has a diverse international education background in Mechanical/Nuclear Engineering and Applied Mathematics: Ph.D. in Mechanical Engineering (North Carolina State University – NCSU, USA, 1993), with a minor in Computational Mathematics; M.Sc. in Nuclear Engineering (Federal University of Rio de Janeiro – UFRJ, Brazil, 1989); and Mechanical/Nuclear Engineer (UFRJ, Brazil, 1983).

He worked for the Brazilian National Commission on Nuclear Energy, CNEN (1984-1986), Promon Engineering, the largest Brazilian private company in Consulting Engineering (1986-1997), and since 1997 works for UERJ, being a Full Professor since 2013. In 2021 he started a formal institutional cooperation with research groups of SENAI CIMATEC (Manufacturing and Technology Integrated Campus) in Brazil. He is a former president of the Brazilian Society of Computational and Applied Mathematics, SBMAC (2014-2017), and of the Brazilian Association of Mechanical Sciences and Engineering, ABCM (2009-2013).

Professor Silva Neto main current research areas are: Inverse Problems; Heat and Mass Transfer; Radiative Transfer; Computational Intelligence; and Environmental Modelling. He serves as Associate Editor for journals in Engineering and Applied Mathematics: Computational & Applied Mathematics (Springer, Since 2005); Journal of Heat and Mass Transfer (ASME, Since 2019); Journal of Computational Mathematics and Data Science (Elsevier, Since 2021); and International Journal of Data Science and Analytics (Springer, Since 2023).