Numerical Mathematics for Industrial Applications

Dr. Edgar Omar Reséndiz Flores
Tecnológico Nacional de México

This talk is focused on the description of some mathematical methods applied to several cases of study motivated from an industrial context. The application of a generalized finite difference method based on the concept of a reproducing kernel is presented for solving the governing partial differential equations in several physical settings. Optimal variables identification, classification and optimization are shown for several manufacturing processes using a versatile multivariate statistical method and soft computing approaches. Finally, a recently new optimization method for optimization is also described based on swarm intelligence and the concept of a reproducing kernel function.

SHORT BIO

Edgar Omar Reséndiz-Flores is a full time researcher at the División of postgraduate studies and research from the Tecnológico Nacional de México/IT Saltillo and active faculty member of three postgraduate programs. He obtained the Doctoral degree in Mathematics from the Mathematics Department at the Technische Universität Kaiserslauern, Germany, in November 2011. Similarly, he received a Master of Science degree in Industrial Mathematics from the same university in 2005. He obtained his bachelor degree with honors in Applied Mathematics from Faculty of Mathematics at the Universidad Autónoma de Coahuila (U.A. de C), México, in 2001. At the end of his undergraduate studies he obtained several awards such as Nazario Ortiz Garza, Juan Antonio de la Fuente and Mariano Narvaez Glz awards for his outstanding academic record. He received the Mixbaal National Award 2002 to the best thesis in applied mathematics offered by the organizing committee of the National School of Numerical Analysis and Optimization and the Mexican Association of SIAM, MEXSIAM. An honorable mention in the national award Sotero Prieto granted by the Mexican Mathematical Society to the best thesis in mathematics in 2002. Since 2013 he has been member of the Mexican National System of Researchers (SNI) from CONACYT and currently he holds level 2 membership in the area of Mathematics. His scientific work has been focused in Industrial Mathematics in particular in the development and application of meshfree methods for Partial Differential Equation in transport processes, Optimization with PDE constraints, intelligent design in materials science with artificial intelligence and metaheuristic optimization, the development of new metahuristic methods for mono and multi-objective optimization as well as the study and improvement of the Taguchi-Mahalanobis System with machine learning techniques for multivariate industrial manufacturing processes. He is author/coauthor of 30 Scientific papers indexed in the Science Citation Index. He has supervised 3 Doctoral Thesis and 10 master thesis. Recently, he has been guest editor of the research topic “Advances in PDE-constrained optimization and meshfree methods for industrial applications” in the journal “Frontiers in Applied Mathematics and Statistics”.