Rust software engineer @ Vaultree and M.Sc candidate @ Universidade Federal de Ouro Preto.
My research interests are focused on cyber security, databases, and distributed systems. Currently, I am working on secure federated learning (FL) protocols with fully homomorphic encryption (FHE).
◉ 12/2022 – Current: Rust Software Engineer at
Vaultree
(Remote)
At Vaultree’s engineering team, I contribute to the development of
always-encrypted database management solutions for different SQL flavors.
The Vaultree's FFDUE (Fully Functional Data-in-use Encryption) technology provides a
Software Development Kit (SDK) that enables businesses to efficiently work with
fully encrypted databases. In that sense, I've been accumulating experiences developing
database drivers (JDBC, Python DB API, Rust Clients, etc) and different management products to
onboard and evolve customers' database schemas. The tools include
database migration, database replication, shell REPL and TUI environments and more.
◉ 03/2022 – 12/2022: Performance Engineer at Dell Technologies (Remote)
At Dell, I developed tools to assess Non-Functional Requirements (Performance – Capacity –
Scalability – Availability – Reliability – etc) of the Dell's Finance
Services. For that purpose, I worked developing Python automations using Flask, Dynatrace, Docker, SQL,
etc. Also, I had to use NeoLoad to run stress tests in order to collect metrics that were automatically
processed afterwards in order to generate official performance reports.
◉ 10/2019 – 08/2021: Undergraduate Research Fellow at Universidade Federal de Ouro Preto
As a research fellow, I worked on the areas of Information Retrieval (IR) and Machine Learning (ML). The
main contributions of my work were: (i) a research on Learning To Rank (LTR) techniques for multi-label text
classification problems, (ii) the development from scratch of an end-to-end textual search engine for
educational and research purposes, and (iii) the development of a focused web page crawler based on genre and
content.
◉ 03/2019 – 10/2019: Java Full Stack Engineer at Fundação Gorceix
At Fundação Gorceix, I worked as a full-stack Web Developer in a private project of the company.
Throughout the development process, I worked with Java 9 using the MVC pattern based on the Spring Framework.
I also had experiences with SQL databases (MySQL and SQLServer), front-end implementation using jQuery, Ajax,
and Bootstrap.
◉ lt.rs - Learning to Rank for Rustaceans
`lt.rs` is a Learning to Rank library written in Rust and based on the
famous RankLib library. The main goal of this project is to provide a
simple, fast, and memory-safe Learning to Rank library which
implements a wide variety of LTR models. Currently, lt.rs supports
only the AdaRank model. The source code can be found here:
https://github.com/marcosfpr/ltrs.
◉ ATRI: Experimental Information Retrieval Tool
The Atri project is an experimental search engine, implemented
from scratch. In this project, a few classic IR models were implemented
to calculate similarity between the documents of a collection and a user query: Boolean,
Vector Space, Probabilistic, BM25, Belief Network, Extended Boolean, Generalized
Vector Space, DFRee, and PL2. In addition, ATRI allows the creation of
a benchmarking environment for reproducible evaluation of the
effectiveness and performance on IR through automatic creation of
ensembles, visualization of effectiveness metrics, and support to
scientific collections.
https://github.com/marcosfpr/atri_ui.
◉ SEALy: Microsoft SEAL bindings for Rust and Python.
SEALy is a project that aims to create FFI bindings from the famous SEAL library for Rust and Python. The main
goal of this project is to provide a simple and fast way to install SEAL for both programming languages.
The SEALy bindings are a continuation from the `seal_fhe` crate, with the support for the CKKS scheme and the
addition of new features like batch encoders, that allow us to overcome the size barriers of the ciphertext
tensors and create AI applications easily with high-dimensional encrypted ciphertext.
The project is still in development and the source code can be found here:
https://github.com/marcosfpr/sealy.
◉ FedHE: Flower Federated Learning Strategies with FHE.
This project is an implementation of Federated Learning strategies using the Flower framework and the SEALy
library. The main goal of this project is to provide a simple and fast way to implement Federated Learning
strategies with Fully Homomorphic Encryption.
With this project, we can easily train a model in a federated way without sharing plaintext gradients
to the 3rd party server. The project is still in development and the source code can be found here:
https://github.com/marcosfpr/fedhe.
◉ 2023 – Current Masters Degree in Computer Science at Universidade Federal de Ouro Preto, Ouro Preto, MG.
◉ 2018 – 2022: Bachelor of Computer Science at Universidade Federal de Ouro Preto, Ouro Preto, MG.
◉ 2015 – 2017: Technical and high school at Instituto Federal de Minas Gerais (IFMG), Ouro Preto, MG.
◉ Júnior, Marcelo Trajano Alves, Marcos Felipe Pontes Rezende, and Guilherme Tavares de Assis. "DEVELOPMENT OF A FOCUSED WEB PAGE CRAWLER BASED ON GENRE AND CONTENT." WWW/INTERNET 2021 AND APPLIED COMPUTING: 77.