- Master's of Science and Information Technology at University of Quebec in Outaouais
- Graduate Diploma in Software Engineering at Pontifical Catholic University of Minas Gerais
- Undergraduate degree in Telematics at Federal Institute of Education, Science and Technology of Ceará
- Convolutional neural network-based object detection with limited embedded computational resources
- Alumni: CREATE Uninhabited aircraft systems Training, Innovation and Leadership Initiative
- Evaluating Compact Convolutional Neural Networks for Object Recognition Using Sensor Data on Resource-Constrained Devices
- Path protection and Failover strategies in SDN networks
- Intent-based VPN and its future in SDN
- Test-driven development: Benefits, techniques and limitations (PT)
- OpenDaylight Network Intent Composition elected committer and reviewer
- Code contributions: here and here
- Kubernetes contributions
- Cloud Native Telecom Initiative (CNTi)
- Mentor at Ladies Learning Code Quebec city
- Ottawa Open Source Networking Meetup 2018: OpenDaylight 101
- Open Networking Summit 2016: Path protection and failover strategies in SDN
- Open Networking Summit 2016: Intent-based VPNs and its future in SDN
- Pycon Canada 2015: Networks and innovation: a lot of programming inside
- Université Laval - Gestion du cycle de vie d’un site Web dans Azure
- Microsoft Certified Solutions Associate: Web Applications (Charter)*
- Microsoft Certified Solutions Developer: App Builder (Charter)*
- Microsoft Certified Solutions Developer: Web Applications
- Microsoft Specialist: Programming in HTML5 with JavaScript and CSS3
- Microsoft Certified Professional: Microsoft Certified Professional
- Abalone regression: This repository uses the Abalone dataset to work on a regression problem to predict the age of abalones. Models used: Linear Regression, Decision Tree, and Random Forest.
- Saude++ : A public health management system in a smart city.
- Predictive maintenance: This project leverages machine learning models to forecast when a server is about to fail by analyzing its CPU usage. This allows for predictive maintenance and avoids costs associated with server failures and services disruption.