Amine Barrak

PhD at University
of Québec

I am Amine Barrak, a Ph.D. candidate at the University of Québec, specializing in Distributed Machine Learning on Serverless Computing. My extensive teaching and research experience spans cryptography, cloud technologies, and the intersection of AI with security in diverse applications.

Academic Background

PhD in Computer Science (2021 - Present)
University of Québec, Québec, Canada
Thesis: “Optimized Training and Enhanced Resilience in Distributed ML: A Serverless Peer-to-Peer Architectural Approach”
Research Area: Distributed Machine Learning on Serverless Computing
Current GPA: 3.65/4.0
Awards: Tuition Fee Exemption Scholarship

MSc in Software Engineering (2016 - 2019)
Polytechnique Montréal, Montréal, Québec, Canada
Thesis: “Just-in-time detection of protection-impacting changes on WordPress and MediaWiki”
Research Area: Security Vulnerabilities of Privilege Protection Changes
GPA: 3.80/4.0
Awards: Tunisia National Excellence Scholarship

Teaching Experience

University of Québec, Department of Computer Science and Mathematics

  • Cryptography (8INF854) - Graduate Course
    Summer 2024 (54 students), Summer 2022 (17 students)
    Explored cryptographic protocols and applications, including quantum cryptography and elliptic curve cryptosystems.

  • Cloud Computing (8CLD202) - Undergraduate Course
    Fall 2023 (22 students)
    Covered cloud infrastructure technologies (Kubernetes, Docker), CI/CD processes, and cloud services (IaaS, PaaS, SaaS).

  • Cloud System Design/Architecture (8INF876) - Graduate Course
    Fall 2023, Fall 2022 (60 students total)
    Delivered lectures on distributed system design, communication protocols, and web services (REST, GraphQL, SOAP).

Recognitions:

  • Recognized by the Department for teaching excellence.
  • Completed certified training on “Teaching Pedagogy”.

Professional Experience

IoT Data Analysis / ML & Cloud Internship
July 2022 – July 2024 | Mitacs Internship, IdeoConcept Inc
Project: IoT Devices and Data Analysis for Machine Learning Purposes
Responsibilities: Analyzed IoT data, proposed cloud architecture solutions, and explored multi-cloud strategies.

AI for fair and diverse Hiring Initiative Juin 2022 – December 2022 | CTO, DIVRSE Inc. Projet: AI-Driven Engine for Fair and Diverse Recruitment Processes Responsibilities: Developed an AI-powered tool to optimize diverse hiring practices, contacted and negotiated with companies to use their APIs, integrating these with our strategic approach and recruited and led a dynamic team to work on the platform development.

NLP on Archaeological Data Internship
September 2021 – January 2022 | ÉTS Montréal
Project: Textual Analysis of PDFs and Unsupervised Grouping of Textual Documents
Responsibilities: Extracted and cleaned data from PDFs, applied unsupervised clustering algorithms, developed automation website.

ML on Time Series dataset Internship
April 2021 – September 2021 | CRIM Inc.
Project: Analysis of Energy Consumption and Network Traffic of Compromised IoT Devices
Responsibilities: Analyzed datasets, classified devices, identified impactful metrics.

NLP & BERT Fine-tuning Internship
July 2020- March 2021 | Airudi Inc.
Project: Matching Resumes with Job Descriptions
Responsibilities: Data extraction, unsupervised clustering, and website development.

ML Pipeline Evolution Internship
February 2020- September 2020 | Polytechnique Montréal
Project: ML Tracking and Co-evolution with Source Code Artifacts
Responsibilities: Explored DVC tools, classified files, tracked ML pipeline evolution.

ML Build Failure Internship
January 2019- September 2020 | Polytechnique Montréal
Project: Study and Analysis of Build Failures
Responsibilities: Handled imbalanced data, analyzed code/test smells, developed predictive models.

Technical Skills

Data Processing and Machine Learning: Pandas, Numpy, Seaborn, Scikit-learn
Deep Learning Frameworks: Pytorch, Tensorflow, Keras
Programming languages: Python, Java, Go, C++ , C#, Javascript
Database Development: PL/SQL, NoSQL
Big Data Framework: Hadoop , spark, kafka
Full Stack Development Frameworks: Django, Angular, .NET, Jhipster, ReactJs and SpringBoot
Testing: JUnit, Mockito, Selenium
Methodologies & Practices: Agile ( Scrum ), SOLID principles
Cloud, DevOps & CI/CD: AWS, Docker, Git, Jenkins, Kubernetes, Terraform, Ansible

Contact

mabarrak@uqac.ca

amine.barrak@polymtl.ca

aminebarrak@gmail.com

+1 (514) 638-5871