He has a degree in Mathematics from UNESP (2001), a master's and doctorate in Computational Mathematics from ICMC-USP (2004 and 2008), with a sandwich internship at the University of Porto, Portugal. He completed his postdoctoral studies at ICMC-USP in 2009. He is currently a full professor at the Department of Mathematics and Computing at FCT-UNESP and vice-coordinator of the Postgraduate Program in Applied and Computational Mathematics. He is deputy editor of the Applied Mathematics Collection published by the Brazilian Mathematical Society-SBM. He coordinated a Fapesp Young Researcher Project and Universal Aid from CNPq. He received an honorable mention from the Odelar Leite Linhares Prize in 2009 for the best doctoral thesis at SBMAC. He supervised two master's theses awarded by SBMAC. In 2019 he was approved as Principal Researcher at CEPID / FAPESP (Center for Mathematical Sciences Applied to Industry). Currently working as a visiting researcher at the Artificial Intelligence Institute in Dynamic Systems, University of Washington. His research involves computational mathematics, computational fluid dynamics and artificial intelligence. More recently he has been developing data-driven methods for constructing reduced-order methods in complex fluid systems. (Source: Lattes Curriculum)
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The focus of this proposal is the transfer of mathematical knowledge to other areas of science, technology and industry, through a structured research center specially tailored for this purpose. All mathematical knowledge is ultimately applicable, if not directly, through other areas of knowledge. In some areas the application of mathematics is almost immediate. However, the practical imp…
The study of high order numerical methods for transient flows is proposed in this research project. Based on the recent progress obtained by the candidate, it will be developed efficient methodologies to solve technologic and scientific problems which allow the use of different boundary conditions, a wide range of Reynolds numbers and the application of the Newtonian and Viscoelastic flui…
In this research project, mathematical models adopted in drug-controlled release systems will be investigated. The numerical methods will beapplied to better understand the effectiveness of treatments associated with diseases that affect the retina and choroid. Based on recent work by supervisor and collaborators, including ophthalmologists, the fellow will usean already validated mathema…
Computational simulations of complex problems governed by differential equations have been significantly improved with advances in Artificial Intelligence (AI) techniques, which can be combined with classical numerical methods. In the current proposal, different AI techniques will be investigated, such as Machine/Deep Learning (ML/DL), Physics Informed Neural Network (PINN), Convolutional…
In this project we will investigate the least squares method for approximating discrete data. Initially, classic Linear Algebra topics will be analyzed, such as orthogonalization, matrix decompositions, eigenvalues and eigenvectors, etc. After this stage, the student will implement the most known techniques for computationally solving the least squares methods for data approximation. Last…
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In this project we will investigate the combination of Sparse Identification Non-linear Dynamics (SINDy) and AutoEncoders (AE) for studying viscoelastic fluid flows. SINDy is a valuable tool for identifying the governing equations of a system based on observational data, while AE can generate reduced-order models that make solving fluid flow problems more computationally efficient. This c…
This proposal sets out a research plan to investigate data-driven, machine learning and numerical methods for dealing with non-Newtonian fluid flows, as for instance, viscoelastic fluids. While the application of machine learning has been already considered as an important tool in fluid mechanics researches for Newtonian fluids, the construction and application of frameworks for non-Newto…
In this project, we will study numerical strategies for dealing with complex topological changes in viscoelastic fluid flows. Based in a combination of the Marker-And-Cell method (MAC) with the front-tracking scheme, we will incorporate the constitutive equations, that describe the viscoelastic flow, into a finite difference in-house code. This code was recently developed for solving axis…
| 1 / 1 | Ongoing research grants |
| 2 / 1 | Completed research grants |
| 17 / 14 | Completed scholarships in Brazil |
| 1 / 1 | Ongoing scholarships abroad |
| 2 / 2 | Completed scholarships abroad |
| 23 / 19 | All research grants and scholarships |
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