About
I am a first-year PhD student in Computer Science at LIP (École Normale Supérieure de Lyon - Inria), started January 2026. My doctoral research, supervised by Eddy Caron, Olivier Barais and Christian Perez in the Avalon team, focuses on automated, secure and resilient deployment of virtualized infrastructures - developing a methodology for dynamic security orchestration in cloud environments, using model-driven engineering and LLMs to automate security rule generation and deployment.
Before my PhD, I spent over two years as a Machine Learning Research Engineer at Inria, where I built end-to-end computer vision pipelines, federated gait analysis systems, and web tracking analysis tools. I hold an Engineering degree + Master's from ESI Algérie, Algeria's top computer science school, which I entered via the national competitive entrance exam.
I enjoy bridging theory and practice, most of my projects ship as real, deployed applications.
- PositionPhD Student (Year 1)
- LabLIP (École Normale Supérieure de Lyon - Inria)
- StartedJanuary 2026
- LocationLyon, France
- Emailm.bechorfa@gmail.com
- LinkedInelaminebechorfa
- GitHubb-elamine
- StatusOpen to collaborations
Experience
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Jan 2026
- presentPhD Student Current
LIP (École Normale Supérieure de Lyon - Inria) - Lyon, France
Doctoral research on automated, secure and resilient deployment of virtualized infrastructures. Developing a methodology for dynamic security orchestration in cloud environments. Supervised by Eddy Caron, Olivier Barais and Christian Perez, Avalon team.
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Nov 2022
- Feb 2025ML Research Engineer
Inria - Lyon, France
- Built a full computer vision pipeline for price detection: YOLOv8 banner detection → Tesseract OCR → bounding-box price-label matching, deployed on Android with CameraX + ONNX Runtime
- Designed a web + Android app for gait anomaly detection using autoencoders & statistical methods (TensorFlow, ReactJS, Flask, Java), deployed on Linux servers
- Developed browser extensions for HAR file collection and web tracking analysis across AdBlocking scenarios, evaluating privacy, utility, and energy impact
- Designed a backdoor attack challenge on ML models using spatiotemporal data
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Apr 2022
- Sep 2022ML Research Intern
Inria / INSA - Lyon, France
- Built a full gait analysis pipeline (statistical modeling in Jupyter), deployed as a mobile app for patients and a web dashboard for clinicians
- Implemented a Federated Learning pipeline for activity classification on mobile devices with secure model aggregation via a central server
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Feb 2022
- Apr 2022Network & Security Engineering Intern
Sonatrach - Oran, Algeria
- Optimized network traffic analysis with ELK stack for real-time log aggregation & visualization
- Implemented deep learning models for network anomaly detection and threat identification
- Built a ReactJS/Django dashboard for real-time log and anomaly analysis
Education
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Jan 2026
- presentPhD in Computer Science In progress
LIP (École Normale Supérieure de Lyon - Inria) - France
Research on automated, secure and resilient deployment of virtualized cloud infrastructures. Avalon team, supervised by Eddy Caron, Olivier Barais and Christian Perez.
-
2017 - 2022
Engineering Degree + Master's (M2) in Computer Science
École Supérieure d'Informatique (ESI) - Algeria
- Specialization: Architecture of Computer Systems
- Laureate of the national competitive CS entrance exam (2019)
- 2 years preparatory classes in mathematics & CS · 3 years advanced cycle
-
2017
Baccalauréat Scientifique - Technical Mathematics
Algeria
Graduated highest honours.
Publications
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A Smartphone-Based Architecture for Prolonged Monitoring of Gait
IEEE 1st International Conference on AI in Medicine and Healthcare (AIMHC 2024) - Laguna Hills, CA, USA · IEEE Xplore
Selected Projects
Cloud Security Knowledge Space
Interactive visualization of cloud security categories and perspectives, developed as part of PhD research on security orchestration in cloud infrastructures. Live demo on GitHub Pages.
MyKnowledgeRAG
Personalized RAG chatbot using OpenAI embeddings + FAISS that answers questions from your own CV, thesis, GitHub repos, and papers - fully local processing for privacy.
Optimized Price Detection - Android
YOLOv8 quantization for fast mobile inference. Pipeline: banner detection → Tesseract OCR → price-label matching via bounding box geometry. Full Android deployment with CameraX + ONNX Runtime + SQLite.
Federated Gait Analysis System
Android app for post-stroke rehabilitation: Federated Learning for privacy-preserving activity classification (TensorFlow), gait metrics via autocorrelation. Clinically validated with Hospices Civils de Lyon. Published at IEEE AIMHC 2024.
PharmaYou
Web application for pharmacy management and patient services, built with JavaScript.
Network Log Anomaly Dashboard
Real-time log analysis using the ELK stack with deep learning anomaly detection and threat identification. ReactJS + Django front-end, built during internship at Sonatrach.
Technical Skills
Languages
- Python
- Java
- C++
- JavaScript
- SQL / Bash
ML / AI
- TensorFlow / Keras
- PyTorch
- YOLOv8 / OpenCV
- Scikit-learn
- ONNX Runtime
Tools & Infra
- Git / GitLab
- Docker / CI-CD
- Linux / SysAdmin
- Flask / Django
- ELK Stack
Teaching
- 2024 - now Web Development & JavaScript Frameworks (Workshops) CS Year 2
- 2024 - now Object-Oriented Programming in C++ (Workshops) CP Year 2
- 2024 - now Digital Signal Processing with Python (Workshops) CP Year 1
- 2025 - now Pentesting - Cours & TD M2 DSI
Taught as lecturer at CESI Lyon and ISFA - Université Lyon 1.
Contact
I'm happy to discuss research ideas, collaborations, or projects at the intersection of cloud security, secure deployment, and applied ML.
Feel free to reach out by email - I usually reply quickly xD
- m.bechorfa@gmail.com
- linkedin.com/in/elaminebechorfa
- github.com/b-elamine
- Lyon, France (UTC +2)