ADACIS'25: The 2025 IEEE International Conference on Advances in Data-Driven Analytics and Intelligent Systems Sousse Sousse, Tunisia, November 20-22, 2025

Scope

The IEEE International Conference on Data-Driven Analytics is a cutting-edge event that brings together experts, researchers, and industry leaders to showcase the latest advancements in information technology and data science. The conference will have a technical program structured around a series of sessions featuring keynote speeches, panels, and presentations by leading experts and researchers in their respective fields. The program will include a diverse range of topics related to data-driven analytics, such as Big Data, Data Mining, Machine Learning, Data Security, and other aspects of data processing.

The conference is intended for a wide audience that includes academics, researchers, professionals, and industry leaders in the fields of Fintech, E-health, Industry 4.0, educational systems and Agriculture. The program is designed to appeal to those who are interested in the latest advancements in information technology and data science and who are seeking to expand their knowledge and stay up to date with the latest trends and developments.

Attendees will have the chance to engage in lively discussions and hands-on workshops, led by experts in their respective fields. The conference will feature a diverse range of speakers, including both academic researchers and industry professionals, who will share their knowledge and expertise on the latest developments in data-driven analytics. The technical program will be organized into several sessions, each focused on a particular topic, and attendees will have the opportunity to choose which sessions they wish to attend.

In addition to the technical program, the conference also offers attendees the opportunity to participate in a gala dinner and cultural visit, while adhering to a well-managed schedule. The conference provides a platform for networking and collaboration, as well as a chance to explore cutting-edge technologies and their applications across various domains.

Tracks

The conference will be structured around six key areas:

• Area 1: Data-driven models and Intelligent Systems

  • This area will track advanced data-based models, methods and frameworks to efficiently extract relevant insights. Topics of interest include but are not limited to:

    • Big data trends to process huge heterogeneous data
    • Data science modelsLarge Language Models (LLMs)
    • Data integration architectures
    • Inferences models
    • Intelligent systems design, development and implementation
    • Distributed Intelligent systems
    • Intelligent systems for Sustainable development
    • Intelligent Systems for Renewable Energy
    • Intelligent systems for computer security
    • Cloud computing for scalable data analytics
    • Ethical AI and explainable machine learning in decision-making
    • Applications
• Area 2: Data-driven analytics for Business
  • This area will cover topics related to the application of data-driven analytics in financial technology. Topics of interest include but are not limited to:
    • AI-driven innovations in supply chain management and logistics
    • Data-driven strategies for digital transformation in business
    • Predictive modeling and forecasting
    • Customer behavior analysis and segmentation
    • Operational efficiency and process optimization
    • Risk management and mitigation strategies
    • The microstructure of modern financial markets: algorithmic /high frequency trading, market liquidity, dark trading, blockchain settlements etc.
    • Behavioural economics
    • FinTech and decision making
    • Open banking , insurTech, SupTech, PayTech and embedded FinTechMicro
    • FinTech and Financial Inclusion
    • FinTech and Sustainable Finance
    • FinTech and Gender
• Area 3: Data-driven analytics for E-health
  • This area will cover topics related to the use of data-driven analytics in healthcare. Topics of interest include but are not limited to:
    • Drug discovery;
    • Computational biology;
    • Health informatics;
    • Telehealth;
    • Sensor informatics and medical imaging;
    • QSAR / QSPR modeling;
    • Disease diagnosis and treatment prediction;
    • Medical image and signal analysis;
    • Healthcare resource allocation and optimization;
    • Electronic health records analysis;
    • Patient outcome prediction.
• Area 4: Data-driven analytics for Industry 4.0
  • This area will cover topics related to the application of data-driven analytics in the context of Industry 4.0. Topics of interest include but are not limited to:
    • Data-driven decision making in Industry 4.0
    • Data analytics for smart manufacturing
    • Data analytics for supply chain optimization
    • Big data analytics for Industry 4.0
    • Data-driven quality control
    • Data analytics for energy management in Industry 4.0
    • Data analytics for predictive maintenance
    • Machine learning for Industry 4.0
    • Blockchain - AI and robotics for enhancing productivity
• Area 5: Data-driven analytics for Education
  • This area will cover topics related to the application of data-driven analytics in the field of education. Topics of interest include but are not limited to:
    • Artificial Intelligence in Education;
    • Learning Analytics for adaptive learning;
    • Scalable Data Driven architectures for Smart Learning;
    • e-Assessment;
    • Development of AI and new roles for teachers;
    • Best practices and case studies on smart teaching and learning;
    • Ethical implications of AI in education and data privacy concerns;
    • Gamification and AI-driven engagement strategies.
• Area 6: Data-driven analytics for Agriculture
  • This area will cover topics related to the application of data-driven analytics in the field of Agriculture. Topics of interest include but are not limited to:
    • Predicting and mitigating climate change impact through data analytics
    • Predictive modeling of crop yield and quality using sensor data
    • Crop health monitoring with satellite and drone imagery and sensor data
    • Holistic farm management through data integration
    • Visualization tools for complex agricultural data
    • Resource management through data-driven analytics
    • Ethical and privacy considerations in agricultural data collection and use
    • Sharing and integration of agricultural data across stakeholders
    • Evaluation and improvement of agricultural data platforms and tools
    • Data-driven solutions for global food security
    • Blockchain for transparency in agricultural supply chains

Submission Guidelines

1. Only original contributions will be accepted. Papers must be written in English and not have been published before, and not be under review for any other conference or publication.
2. Manuscripts should respect IEEE template (6 pages) including figures, tables, and references.https://www.ieee.org/conferences/publishing/templates.html
3. All papers accepted will be published in the conference proceedings and are expected to be published by IEEE Xplore, subject to meeting IEEE Xplore's scope and quality requirements.
4. The conference will check plagiarism for all the articles before prior publication, if the plagiarism rate is exceeding 25%, the article will be rejected and the author will be informed accordingly.
5. Authors of selected papers will be invited to extend the paper for expected publication in international journals and in edited books.

Feel free to download and share the pdf version of the call for papers.

Honoree General chair

• Dr. Lotfi BELKACEM, President of the University of Sousse (USO), Tunisia

General chair

• Dr. Dalel Kanzari, University of Sousse, Tunisia

Steering committee

• Dr. Rui Marques , University of Aveiro, Portugal
• Dr. Essalih Mohamed, University of Cadi Ayyad, Morocco
• Dr. Dalel Kanzari, University of Sousse, Tunisia
• Dr. Kurosh Madani, University of Paris-Est Créteil Val de Marne, France

Program committee chairs

• Dr. Kurosh Madani, University of Paris-Est Créteil Val de Marne (UPEC), France
• Dr. Maha Khemaja, University of Sousse, Tunisia

Track chairs

Data-driven models models and Intelligent Systems

• Dr. Othmane Alaoui Fdili, University of Cadi Ayyad, Morocco
• Dr. Sami Achour, University of Sousse, Tunisia

Data-driven analytics for Fintech

• Dr. Yosra Ben Said, University of Sfax, Tunisia
• Dr. Sonia Makni, University of Sousse, Tunisia

Data-driven analytics for E-health

• Dr. Nahla Ben amor, University of Tunis, Tunisia
• Dr. João Carvalho, University of Aveiro, Portugal

Data-driven analytics for Industry 4.0

• Dr. Gonçalo Carnaz, University of Aveiro, Portugal
• Dr. Jamal Bakkas, University of Cadi Ayyad, Morocco

Data-driven analytics for Education

• Dr. Imène Berguiga, University of Sousse, Tunisia
• Dr. Abderrahman Chekry, University of Cadi Ayyad, Morocco

Data-driven analytics for Agriculture

• Dr.Hanine Mohamed, Chouaib Doukkali University, Morocco
• Dr. Christophe Sabourin, Paris-Est Créteil University, France

Contact information

If you have any questions or queries on ADACIS’25 please send email to adacis2023@uca.ac.ma