Systems Engineer · Researcher · PhD
I design and study software where performance, reliability, energy efficiency, and long-term maintainability meet real-world constraints.
Migrating a mature Windows-based C++ codebase to Linux while establishing a long-term cross-platform engineering strategy.
The work covers architecture, build infrastructure, CI/CD pipelines, containers, environment automation, and software delivery for large-scale production systems.
During my PhD, I studied how computational workloads can be executed more efficiently by modeling and optimizing the relationship between performance, resource usage, and energy consumption.
My research included analytical energy models, workload characterization, resource allocation, DVFS, and DPM for shared-memory parallel systems.
Research and tooling for understanding the scalability and behavior of parallel applications through performance counters and measurement-based analysis.
This work included automated assessment of parallel scalability, workload fingerprinting, comparison, and visualization.
University of Mons (UMONS), Belgium
2018 — 2024
My doctoral research focused on energy-efficient high-performance computing and how workload characteristics, system resources, and execution strategies influence performance and power consumption.
The core objective was to create approaches that allow computational systems to use resources more intelligently without compromising application performance.
Low-level software, Linux, system behavior, resource management, and infrastructure design.
Parallel applications, scalability, performance analysis, and efficient workload execution.
Understanding bottlenecks, measuring system behavior, and making software more effective.
Energy modeling, DVFS, DPM, efficient resource allocation, and sustainable software design.
MDPI Electronics · 2022
MDPI Energies · 2022
IEEE IPDPS · 2019
HPCS · 2019
My engineering work sits close to the system level, where software meets operating systems, hardware constraints, infrastructure, and production realities.
OMP
Working on large-scale software engineering with a strong focus on Linux, C++, cross-platform systems, and production infrastructure.
University of Mons · Belgium
Research in energy-efficient high-performance computing with emphasis on modeling power and performance trade-offs in computational workloads.
NPAD · Federal University of Rio Grande do Norte
Worked with HPC cluster administration and tools to improve the experience of researchers and users in a Linux-based environment.
Honorable Mention
39th Annual ACM ICPC World Finals · 2014
Hands-on AI Workshop
2020 · Mons, Belgium
Quarterfinalist
Latin American Robotics Competition · 2016
A scientific software system for visualization of parallel scalability trends.
BR 51 2019 002345-5
Developed using Python and Django.
A scientific software system for analysis of parallel applications.
BR 51 2019 002391-9
Developed using C++.
University of Mons · Belgium
Federal University of Rio Grande do Norte · Brazil
Federal University of Rio Grande do Norte · Brazil
Abstractions are useful, but understanding what happens underneath them is essential when performance and reliability matter.
Good engineering starts with evidence, metrics, and a deep understanding of actual system behavior.
Software that works today is not enough; it must be maintainable, testable, and operable for years.
Interesting ideas become valuable when they survive real systems, constraints, and user demands.
Have an interesting systems problem, research challenge, or engineering opportunity?
Get in touch.
Natal, Rio Grande do Norte, Brazil