About

I am Danilo R. Souza, a mathematician (B.Sc., M.Sc., and Ph.D. in Mathematical Optimization from the Federal University of Goias - UFG) and a researcher working in Continuous Optimization, Multiobjective Optimization, and Inverse Problems.

I completed a postdoctoral position in Applied Mathematics at USP (2024), with emphasis on inverse problems (including EIT - Electrical Impedance Tomography, electric potential problems, and conductivity problems with internal measurements). My current research is strongly connected to seismic inversion and Full Waveform Inversion (FWI), with a special interest in large-scale stochastic optimization for elastic FWI.

Location: Campinas-SP, Brazil
Areas: Mathematical Optimization, Stochastic Optimization, Multiobjective Optimization, Derivative-Free Methods, Inverse Problems, FWI and EFWI
Applied interests: Computational geophysics, numerical methods, HPC, and multi-language pipelines (Julia/Python/C)

Research Lines

Multiobjective Optimization and Numerical Methods

I have worked on the development and analysis of methods for multiobjective optimization, with attention to nonsmooth, composite, and/or weak-regularity settings. A recurring axis is the design of algorithms with strong practical performance and a sound theoretical basis (when possible), using metrics and performance profiles on broad benchmark sets.

Large-Scale Stochastic Optimization for FWI

I am currently developing a research plan on large-scale stochastic optimization for Elastic Full Waveform Inversion (FWI), including mini-batch strategies, stochastic noise control, and integration with simulation/gradient pipelines in HPC environments.

Inverse Problems

Recent experience includes inverse problems in applied mathematics, including EIT and conductivity problems with different types of measurements. I am interested in how modeling, regularization, parameterization choices, and uncertainty affect both theory and computational performance.

Teaching and Academic Work

I have experience in teaching and in preparing instructional material for different mathematics audiences. I also work on academic documentation and evaluation-oriented texts for faculty applications and selection processes, with emphasis on clarity, structure, and alignment with institutional criteria.

Software and Scientific Computing

I develop scientific software mainly in Julia and co-founded VectorOptimizationGroup with L. F. Prudente and Pedro Assuncao Filho, focusing on multiobjective/vector optimization:

MOSolvers.jl - solvers for multiobjective optimization
MOProblems.jl - collection and organization of benchmark problems
MOMetrics.jl - metrics and evaluation utilities (currently private)

Topics and Keywords

multiobjective optimization, stochastic optimization, large-scale optimization, derivative-free methods, composite optimization, inverse problems, EIT, full waveform inversion, elastic FWI, HPC, Julia, scientific computing, performance profiles