Thiago V.
Back-end and Systems Engineer

Skills

Node.js

Microsoft Sql Server

Python

Mysql

Amazon Aws

Angular

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Bio

Holds a Doctorate in Computer Science from the Federal University of Rio Grande do Norte (UFRN) with extensive experience in Python and proficiency in additional technologies such as Node.js, Java, and SQL. Currently operates in a mid-level developer role.

Backend Developer
4/1/2022 - Present

Developed expertise in migrating on-premise systems to fully cloud-based solutions using AWS. Gained proficiency in Python and C# for developing code and creating effective solutions. Engaged extensively with both relational and non-relational databases to ensure data integrity and optimal performance. Contributed significantly to defining and implementing cloud architecture, ensuring seamless integration and functionality in the cloud environment.
FullStack Developer
9/1/2020 - 4/1/2022

Served as a Fullstack Developer, managing both the development of new features and maintenance of the Municipal Transparency Portal for the Municipal Prefecture. Demonstrated technical expertise in creating and refining applications to ensure data transparency and accessibility for public use. Conducted auditing tasks and generated automated reports, contributing significantly to the accuracy and reliability of financial and operational data. Utilized extensive database querying skills to support the Municipal General Controllership (CGM), ensuring data integrity and responsiveness to oversight requirements.
Research Fellow
8/1/2017 - 3/1/2022

Conducted advanced research in Systems and Computing as a PhD research student in the Graduate Program in Systems and Computing (PPgSC). Focused on pioneering approaches in Machine Learning and Data Analysis, with a specific emphasis on supervised learning techniques and probabilistic and statistical models. The doctoral project involved developing an innovative method for integrating the opinions of various classifiers within a committee of classifiers, showcasing expertise in ensemble learning and sophisticated model combination strategies.
Research Fellow
7/1/2011 - 5/1/2017

Served as a Researcher at LabTEVE, focusing on the development of a serious game to assist in the rehabilitation of stroke patients. Applied advanced machine learning techniques to interpret electromyographic data via sensors, enabling real-time gesture recognition through a trained neural network. Integrated recognized gestures to facilitate patient interaction within the game environment. Expanded technical expertise in neural networks, real-time data processing, and sensor technology, contributing significantly to the field of virtual rehabilitation.

Systems and Computing at Federal University of Rio Grande do Norte
2017 - 2022
Computer Science at Federal University of Paraíba
2010 - 2015
Decision Models and Health at Federal University of Paraíba
2015 - 2017