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 models
    • Data integration architectures
    • Inferences models
    • Descriptive analytics methods
    • Predictive analytics methods
    • Prescriptive analytics methods
• 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:
    • The microstructure of modern financial markets: algorithmic / high frequency trading, market liquidity, dark trading, blockchain settlements etc.
    • Behavioural economics in financial technology;
    • FinTech and decision making;
    • Alternative data (structured and unstructured datasets);
    • Peer to peer lending and investment strategy;
    • New exchange traded financial derivatives;
    • Financial stability risks from the development of FinTech ;
    • FinTech regulation (RegTech);
    • Open banking , insurTech, SupTech, PayTech and embedded FinTech;
    • Micro 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
• 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.
• 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 indexed by SCOPUS.

Workshops

As part of the conference, we are proud to offer six informative and engaging workshops. These workshops will cover a range of cutting-edge topics, including and not limited to Data Science, Deep Learning, Trading, Learning Analytics, and Greentech.

The call for workshop proposals will be launched soon.

General chairs

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

Steering committee

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

TPC chair

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

TPC

• Dr. João Carvalho, University of Aveiro, Portugal
• Dr. Dora Simões, University of Aveiro, Portugal
• Dr. Mohsen  Maraoui, University of Monastir, Tunisia
• Dr. Imen berguiga, Sousse University, Tunisia
• Dr.  Hanine Mohamed, University of Chouaib Doukkali, Morocco
• Dr. El Bhiri Brahim, EMSI Rabat, Morocco

Track chairs

Data-driven models, Algorithms and Frameworks

• Dr. Salma Mouline, University of Mohammed V, 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. Minaoui Khalid, University of Mohammed V, Morocco
• Dr. André Monteiro, University of Aveiro, Portugal

Data-driven analytics for Industry 4.0

• Dr. Jamal Bakkas, University of Cadi Ayyad, Morocco
• Dr. Imran Ashraf, University of Gyeongsan, Republic of Korea

Data-driven analytics for Education

• Dr. Abderrahman Chekry, University of Cadi Ayyad, Morocco
• Dr. Dora Simões, University of Aveiro, Portugal

Data-driven analytics for Agriculture

• Dr. Soufiane Hourri, Cadi Ayyad University, Morocco
• Dr. Karim Fathallah, University of Manar, Tunisia

Contact information

If you have any questions or queries on ADACIS’23 please send email to adacis2023@uca.ac.ma