CV Lattes
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Universidade Estadual de Campinas (UNICAMP). Instituto de Matemática, Estatística e Computação Científica (IMECC) (Institutional affiliation from the last research proposal) Birthplace: Brazil
I am a Bachelor's degree in Applied Mathematics from the Federal University of Amazonas (2015), a Master's degree in Mathematics from the Federal University of Amazonas (2017) and a PhD in Applied Mathematics from the University of São Paulo (2023) with a research period at the Technische Universitat Dresden in Germany between September of 2020 and December of 2021. In 2024, he won the award for Best Doctoral Thesis in Applied Mathematics by SBMAC. I worked as an Assistant Professor at UFAM in 2016 and 2017. Between 2022 and 2025, I worked as a Data Scientist in the area of seismic data processing. Currently, I'm a post-doc researcher at University of Campinas. I have experience in the area of Applied Mathematics, working mainly on the following topics: optimization, optimization under the second order cone, qualification condition, global convergence, quadratic optimization, principal component analysis and combinatorial optimization. (Source: Lattes Curriculum)
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It is well-known that some optimization algorithms may not generate AKKT sequences, as shown for the Newton method in [Math. Program. 160:547-555, 2016]. In some cases, instead of applying the pure Newton method, using the scaled method can solve this problem. In this project, we will investigate other optimization methods that enjoy the property of converging to feasible points that also…
This project deals with the general nonlinear optimization problem in euclidean space with twice continuously differentiable function. Relating to second-order necessary optimality condition, there is a gap between conditions that can be proved (theoretical) and conditions that can be attained by an iterative algorithm (practical), in the sense that the theoretical ones are at the present…
In this BEPE proposal for a long-time stay at Technische Universität Dresden, we are interested in studying strong second-order optimality conditions for nonlinear programming and second-order constraint qualifications associated to them. To the best of our knowledge, no algorithm has been shown to converge to a point at which the strong conditions hold. We are interested in approaching t…
| 1 / 1 | Ongoing scholarships in Brazil |
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