CES-Lab

Computer & Embedded Systems Laboratory

Pioneering research in embedded systems, IoT, AI, and cloud computing for intelligent systems of tomorrow.

500+
Publications
10K+
Citations
50+
PhDs Defended
20+
Ongoing Projects
Latest
🚀 CES-Lab secures TND500K funding for AI in Healthcare project 📄 New publication in IEEE Transactions on Industrial Informatics 🏆 PhD student wins Best Paper Award at IEEE Conference 🤝 International collaboration with MIT announced

About CES-Lab

The Computer & Embedded Systems Laboratory (CES-Lab) is a premier research center at ENIS, University of Sfax, dedicated to advancing cutting-edge technologies.

Our Identity

An official research laboratory of the National School of Engineers of Sfax (ENIS), University of Sfax, recognized for excellence in computer engineering and embedded systems.

Our Mission

Conduct fundamental and applied research to solve complex challenges in embedded systems, IoT, AI, and cybersecurity, bridging academia and industry.

Collaboration

Fostering national and international partnerships with academia, research centers, and industry to drive innovation and technology transfer.

Research Impact

46
Faculty Members
18
PhD Students
25+
Active Projects
15
International Partners

Research Areas

Our multidisciplinary research spans cutting-edge domains with real-world applications

Embedded Systems

Design and optimization of real-time, low-power embedded systems for industrial automation and smart applications.

FPGA Real-time OS ARM

IoT & Networks

Connected devices, sensor networks, edge computing, and IoT platforms for smart cities and Industry 4.0.

LPWAN 5G/6G Edge AI

AI & Data Science

Machine learning, deep learning, computer vision, and signal processing for intelligent decision systems.

Deep Learning Computer Vision NLP

Cybersecurity

Secure embedded systems, blockchain, cryptography, and privacy-preserving technologies.

Blockchain Zero Trust Quantum Safe

Featured Research Project

DeepHealth: AI-powered diagnostic system for early disease detection using edge computing and federated learning.

TND450K Funding
2022-2025 Timeline

In collaboration with CHU Sfax

Our Team

A diverse team of researchers, faculty, and students driving innovation forward

Faculty Members

46

13 Professors

33 Assistant Professors

Leading research and supervision

Researchers

18

2 Post-Doctoral

16 PhD Students

Full-time research focus

Students

21+

16 PhD Candidates

5 Master Students

Training future experts

Team Expertise

Software Engineering
Networking
AI/ML
Security

Research Projects

Nationally and internationally funded projects driving innovation

PEJC Projects

National

Joint Research Projects Program

  • Driver Behavior Analysis

    2020–2022 • AI for road safety

  • AI & Blockchain Healthcare

    2022–2024 • Secure medical data

  • Smart Agriculture IoT

    2023–2025 • Precision farming

TND1.2M Total Funding 4 Projects

VRR Projects

International

Valorization & Research Results

RASD Project

Cost-effective fluid leak detection and localization system using acoustic sensors and machine learning.

2022–2025
Timeline
Industrial applications in oil & gas sector

MobiDoC

EU Funded

Mobility & Doctoral Training

Industry 4.0

Smart manufacturing and digital twins

High Performance Computing

Parallel computing and GPU acceleration

Generative AI

Large language models and content generation

4 Partner Countries
Tunisia, France, Germany, Italy
TND3.5M+
Total Funding
12
Active Projects
8
Industrial Partners
15+
International Collaborations

Recent Publications

Cutting-edge research published in top-tier conferences and journals

IEEE Transactions
2024

Federated Learning for IoT Edge Devices with Differential Privacy

A novel approach to privacy-preserving machine learning in distributed IoT networks.

Citations: 42 Impact Factor: 8.5
ACM Conference
2023

Real-time Anomaly Detection in Industrial IoT Using Edge AI

Edge computing framework for predictive maintenance in Industry 4.0 environments.

Best Paper Award
Springer Journal
2023

Blockchain-Based Secure Data Sharing for Healthcare IoT

Decentralized architecture ensuring data integrity and patient privacy.

Citations: 28
500+
Total Publications
10K+
Total Citations
25+
IEEE Transactions
15
Best Paper Awards
8.2
Avg. Impact Factor

Contact Us

Get in touch for collaborations, research inquiries, or more information

Email Contact

Primary contact method

For general inquiries:

ces@enis.tn

Prof. Mouna BAKLOUTI

Laboratory Director

Response Time

Typically within 24-48 hours

Send Email Directly

ENIS, Sfax

+216 74 274 862

Mon-Fri 9AM-5PM

ceslab.org

Our Location

CES-Lab at ENIS, University of Sfax

CES Laboratory

National School of Engineers of Sfax (ENIS)

University of Sfax, Tunisia

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