The International Conference of Mathematics and Data Science (ICMDS’25) is a multidisciplinary, peer-reviewed conference that offers a platform for the exchange of cutting-edge research, the presentation of innovative ideas, and the discussion of future trends in Artificial Intelligence and data science. ICMDS’25 brings together academic researchers, scientists, and professionals to share their latest findings, explore collaborative opportunities, and contribute to the advancement of both theoretical and applied aspects of the fields.
ICMDS’25 will be held in hybrid format. Participants will have the option to present their work in person at ENCG, Casablanca, Morocco, or online.
Aim and Objective
Data science and artificial intelligence serve as the foundation for advancements in economic and financial domains, providing critical insights into market dynamics, risk assessment, and investment strategies. With rapid technological progress and the increasing availability of big data, AI-driven mathematical models continue to reshape financial systems, economic policies, and decision-making processes. Recently, novel themes in applied mathematics and AI have emerged as transformative forces in modern finance and economic Modeling.
This conference aims to highlight research trends at the intersection of AI, data science, and financial mathematics that are revolutionizing predictive analytics, automated decision-making, and financial risk management. While staying true to the foundational principles of applied mathematics, the conference will emphasize cutting-edge topics such as quantitative finance, algorithmic trading, risk assessment, actuarial science, and econometrics. It will also explore the impact of machine learning, deep learning, natural language processing, reinforcement learning, and intelligent optimization on financial markets, fraud detection, portfolio management, and economic forecasting.
By fostering collaboration among researchers, data scientists, practitioners, and industry experts, this conference seeks to drive innovation, enhance financial Modeling techniques, and accelerate advancements in AI-driven economic and financial analytics.
Call for Papers Launch : 15Â Mai 2025
Full-Abstract Submission Deadline : 15 August 2025Â 30Â September 2025
Full-Text Paper Submission Deadline : 30 August 2025Â Â 15 October 2025
Acceptance Notification/Rejection (on/before) : 15 September 2025Â Â 05 October 2025
Early Bird Registration : Before 12 Octobre 2025
Camera Ready Submission : 30 September 2025Â 15 October 2025
Late Registration :Â Â After 12 October 2025
Conference Dates : 23 – 25 October 2025
Learning Theory: Approximation Theory and algorithmic
Deep Learning Models and Architectures
PDE and Deep Learning
Statistical Analysis and Data Mining for Machine Learning
Computer Vision and Pattern Recognition
Natural Language Processing and Text Mining
Reinforcement Learning and Autonomous Systems
Optimization Algorithms and Metaheuristic Techniques in Economics
Swarm Intelligence and Nature-Inspired Optimization in Finance
Evolutionary Computation and Genetic Algorithms in Financial Modeling
Multi-objective Optimization and Pareto Front Analysis in Economics
Optimization for Machine Learning and Data Science in Finance
Predictive & Prescriptive Analytics in BI
NLP & AI-Driven Insights
Real-Time Data Science & Streaming Analytics
Automated Business analytics and Decision Making
AI Ethics, Risks & Governance in Business Intelligence
Industry Case Studies & Future Trends
Mathematical Formulation and Analysis of Inverse Problems
Imaging Reconstruction Techniques
Tomography and Medical Imaging
Seismic Imaging and Geophysical Inverse Problems
Signal Processing and Remote Sensing
Mathematical Modeling and Simulation for Complex Systems
Computational Fluid Dynamics and Heat Transfer
Financial Mathematics and Quantitative Finance
Graph Theory and Network Analysis
Game Theory and Decision Making
Cybersecurity and Cryptography
High-Performance Computing and Parallel Processing
Mathematical Biology and Bioinformatics
Biomedical Imaging and Intelligent Diagnostic Systems
Telehealth and Remote Medicine: Challenges and Opportunities
Health Informatics and Clinical Information Systems
Artificial Intelligence in Biotechnology
Big Data Analytics for Public Health and Personalized Medicine
Neural Networks and Deep Learning in Life Sciences
Biomedical Instrumentation and Smart Healthcare Devices
Recent Advances in Biotechnology and Clinical Applications
Learning Theory: Approximation Theory and algorithmic
Deep Learning Models and Architectures
PDE and Deep Learning
Statistical Analysis and Data Mining for Machine Learning
Computer Vision and Pattern Recognition
Natural Language Processing and Text Mining
Reinforcement Learning and Autonomous Systems
Mathematical Formulation and Analysis of Inverse Problems
Imaging Reconstruction Techniques
Tomography and Medical Imaging
Seismic Imaging and Geophysical Inverse Problems
Signal Processing and Remote Sensing
Optimization Algorithms and Metaheuristic Techniques
Swarm Intelligence and Nature-Inspired Optimization
Evolutionary Computation and Genetic Algorithms
Multi-objective Optimization and Pareto Front Analysis
Optimization for Machine Learning and Data Science
Mathematical Modeling and Simulation for Complex Systems
Computational Fluid Dynamics and Heat Transfer
Financial Mathematics and Quantitative Finance
Graph Theory and Network Analysis
Game Theory and Decision Making
Cybersecurity and Cryptography
High-Performance Computing and Parallel Processing
Mathematical Biology and Bioinformatics
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DIRECTOR OF ENCG CASABLANCA, HASSANÂ II UNIVERSITY, MOROCCO.
PRESIDENT OF HASSAN II UNIVERSITY, MOROCCO.
Professor Expert in social policies and Frugal Social sustainable Smart Cities and Territories
DEAN OF THE FACULTY OF HEALTH SCIENCES, INTERNATIONAL UNIVERSITY OF CASABLANCA, MOROCCO.
DEAN OF THE BUSINESS SCHOOL INTERNATIONAL UNIVERSITY OF CASABLANCA, MOROCCO.
INTERIM PRESIDENT OF SULTAN MOULAY SLIMANE UNIVERSITY, MOROCCO.
HASSAN IIÂ UNIVERSITY, CASABLANCA, MOROCCO.
SULTAN MOULAY SLIMANE UNIVERSITY, BENI MELLAL, MOROCCO.
Professor Expert in social policies and Frugal Social sustainable Smart Cities and Territories
Title of the talk : Frugal Social Sovereign AI paving the way towards Sustainable Development in Africa
Sheffield Hallam University , United Kingdom
Institute of Technology, Rochester, NY, USA
Pau et des Pays de l'Adour University, France
Aix-Marseille University, France.
International University of Casablanca, Morocco
Université Marie et Louis Pasteur-UTBM, France
Title of the talk : Data Science and AI in Economic and Management Sciences: From Analysis to Decision Architecture.
Nantes Université
Title of the Talk: Semi-Analytical Methods for Solving Inverse Problems
Caen University, France
Pr. Aawatif HAYAR is Expert in social policies and Artificial Intelligence driven inclusive sustainable smart cities and territories. Strategic Advisor at Presidency of University Mohammed VI Polytechnic on Artificial Intelligence driven Smart Cities in charge of AI Powered Smart Campus project@UM6P. Former Minister of Solidarity, Social Inclusion and Family 2021-2024. Aawatif Hayar was appointed President of the University Hassan II of Casablanca-Morocco From June 2019 till October 2021 and is the second female in the history of Morocco to occupy this position. She received, with honors, as the First Moroccan, the degree of “AgrĂ©gation” in Electrical Engineering from Ecole Normale SupĂ©rieure de Cachan in 1992. She received the “DiplĂ´me d’Etudes Approfondies” in Signal processing Image and Communications and the degree of Engineer in Telecommunications Systems and Networks from ENSEEIHT de Toulouse in 1997. She received with honors the Ph.D. degree in Signal Processing and Telecommunications from Institut National Polytechnique in Toulouse in 2001.Â
She was research and teaching associate at EURECOM’s Mobile Communication Department from 2001 to 2010 in Sophia Antipolis-France. Aawatif Hayar has an HDR (Habilitation à Diriger la Recherche) from University Sud Toulon Var from France on Cognitive Wideband Wireless Systems on 2010 and an HDR on Green Téléommunication from University Hassan II Casablanca on 2013. Aawatif Hayar has Professor position at the engineering school ENSEM of University Hassan II Casablanca since 2011. She is also member of Casablanca “Avant-garde” City think-tank and Chair of Frugal Social Smart City Casablanca IEEE Core Smart Cities project. Her research interests includes fields such as cognitive green communications systems, UWB systems, smart grids, digital for development, e-governance, open data for citizens, frugal social smart cities, social policies, Artificial Intelligence powered smart cities and Territories.
« Frugal Social Sovereign Artificial Intelligence paving the way towards Sustainable Development in Africa  », Prof. Aawatif Hayar, Expert in social policies and Frugal Social sustainable Smart Cities and Territories, Former Minister of Solidarity, Social Inclusion and Family
Sustainable development and artificial intelligence (AI) are converging today as two essential levers for building a more balanced and resilient future. AI, through data collection, analysis, and predictive capabilities, enhances productivity, optimizes the management of natural resources, and promotes inclusive human development. By integrating AI into sustainable development strategies, it becomes possible to accelerate and monitor successful combining of economic performance, social inclusion, and environmental preservation.
Unlike heavy models that are data or computation intensive and aim for full automation, the “Frugal and Social Artificial Intelligence” approach places the human dimensio at the center of the development process. It prioritizes efficiency, low complexity, energy optimization, and local relevance and ownership. Its goal is to design solutions that strengthen and augment human capabilities, putting them at the service of human well-being.
This philosophy fits perfectly with African realities and cultures, where development challenges require tools that are efficient, inclusive and adapted to the concrete needs of populations, while preserving social cohesion and territorial anchoring.
Mohamed Quafafou
Aix-Marseille University
We are witnessing a profound shift to the Artificial Intelligence (AI) era, a transformation as consequential as the industrial and digital revolutions. Unlike traditional computational systems, AI enables machines to perform tasks that require perception, reasoning, and adaptation, capabilities once regarded as uniquely human. This shift is driven by advances in machine learning, deep neural networks, natural language processing, and computer vision, supported by unprecedented computational power and vast datasets.Â
The AI era is defined not only by automation but by intelligence enhancement, where human creativity and decision-making are enhanced through predictive analytics, generative models, and adaptive systems. Its influence spans every domain: medicine, education, finance, industry, and immersive technologies such as VR, AR, and MR. At the same time, it forces us to confront critical questions of ethics, equity, and governance, as innovation increasingly reshapes the foundations of social and economic life.
Subjectivity in Data-Centric AI refers to the inherent human influence and biases that arise throughout the data lifecycle, from collection to labeling, preprocessing, and interpretation. Unlike purely algorithmic biases, subjectivity results from human decisions that shape what data is gathered, how it is represented, and how it is used to train and evaluate AI systems. At the data collection stage, subjectivity emerges through selection bias, where certain populations, contexts, or features are overor under-represented. Human judgment influences which variables are deemed important, which measurements are taken, and which are excluded. In data labeling, subjectivity appears in annotation bias, as labels often reflect personal, cultural, or institutional interpretations rather than objective truths. This is especially evident in areas such as sentiment analysis, medical diagnosis, or facial expression recognition, where perceptions differ between annotators. During preprocessing and cleaning, subjective choices determine how missing values are handled, which outliers are removed, and how data is normalized, all of which can affect model outcomes.Â
Even in defining “ground truth,” humans impose assumptions that may not universally apply. Moreover, decisions about data augmentation, sampling, and balancing involve trade-offs between fairness, accuracy, and representativeness, again shaped by human judgment. In the evaluation and deployment phases, subjectivity manifests itself in selecting performance metrics (e.g., precision vs. recall) and interpreting results. These choices can prioritize certain values, such as efficiency, equity, or interpretability, over others, depending on human or institutional goals.
Ultimately, subjectivity in Data-Centric AI highlights that data is not neutral: it reflects human perspectives, contexts, and priorities. Recognizing and managing this subjectivity is crucial for building trustworthy and responsible AI systems. This requires transparency in data documentation, diversity in data teams, participatory design approaches, and continuous auditing of data pipelines. By integrating human awareness and ethical reflection into data processes, Data-Centric AI can move toward more inclusive, fair, and contextually grounded intelligence.
Financial Inclusion in the era of data science: The case of Microfinance
Microfinance has proven to be a strong catalyst for financial inclusion by reaching out to the underbanked societies. One possibility of doing so is through the joint liability framework. Yet joint liability is not free from credit default as it often involves the free riding element of group members and several behavioural issues often unnoticed by the microlenders.
This presentation would bridge this gap by discussing the recent findings of microfinance research tackling kinship and social ties and their impact on loan defaults. The study used the traditional logit framework but then benchmarked with different Machine learning models. The results from the study were, then , used, as part of a work extension, to develop a New Fuzzy framework for microfinance institutions to use as part of their credit loan assessment strategies. Â
Dr Adil EL Fakir
Sheffield Business School
Sheffield Hallam University, UK
Jaafar Gaber as a featured speaker for the keynote “Data Science and AI in Economic and Management Sciences: From Analysis to Decision Architecture.” His talk will explore how data science is reshaping decision-making in economics and management, moving beyond traditional analysis toward intelligent, adaptive decision systems.
Jaafar Gaber will highlight the ongoing shift from prediction to causality (Causal AI), from performance to explainability (XAI), and from observation to simulation through digital twins and intelligent agents. Using real-world cases in inflation, supply chain, finance, marketing, and human resources, he will demonstrate how AI is transforming both research and practice.
Beyond tools and methods, his keynote raises a vital question: what is the role of economists and managers in the age of algorithms? Are they replaceable, or do they evolve into architects of augmented decisions, uniting meaning, computation, and responsibility? This reflection invites institutions and organizations to prepare for a new era—one where data not only describes the world but actively shapes it.
Title: PDEs on Graphs in Data Science: Practical Applications in Health, Industry, and Cultural Heritage Valorization
Abstract: I will begin by presenting several inverse problems in image processing and data classification, and their solutions using PDEs on graphs.
Then, I will present practical applications in the fields of healthcare, industry, and the enhancement and preservation of historical and cultural heritage.
The talk of Abdeljalil Nachaoui “Semi-Analytical Methods for Solving Inverse Problems.” His presentation will highlight innovative applications of semi-analytical approaches to address complex and ill-posed inverse problems in biomedical engineering and heat transfer.
Professor Nachaoui will present a Homotopy Perturbation Method (HPM) developed for the inverse EEG problem, capable of reconstructing neurocortical potentials from scalp measurements with remarkable precision. He will also discuss its application to the inverse Stefan problem, where HPM enables accurate temperature distribution and boundary reconstruction without complex numerical tracking.
Through these examples, Abdeljalil Nachaoui will demonstrate how HPM achieves exceptional computational efficiency and accuracy without relying on regularization techniques. His work offers a unified framework for solving challenging inverse problems, paving the way for new advances in clinical diagnostics and thermal engineering.
K. DARBAN Hassan II University , Casablanca
A. GHAZDALI, SULTAN MOULAY SLIMANE UNIVERSITY
S. KABBAJ Hassan II University , Casablanca
A. LAGHRIB, Sultan Moulay Slimane UniversityÂ
N. ABOUTABIT, Sultan Moulay Slimane University
A. HASSBAOUI, Hassan II University of Casablanca
S. JUIDETTE, Hassan II University , Casablanca
S. JABRAOUI, Hassan II University , Casablanca
L. AFRAITES, Sultan Moulay Slimane University
A. GACIM, Hassan II University , Casablanca
I. ABYABA, Hassan II University, Casablanca
A. LAARIBI, Hassan II University , Casablanca
A. EL HOSSI, SULTAN MOULAY SLIMANE UNIVERSITY
N. HAFIDI, SULTAN MOULAY SLIMANE UNIVERSITY
M. ALLA, HASSAN II University , Casablanca
We offer three types of registrations. Participants should choose between these types at account creation. It is also possible to upgrade from one type to another by contacting us by email.
Account name: ASSOCIATION DES ETUDIANTS ENCG
RIB: 011 780 0000732000038362 35
IBAN: MA64 0117 8000 0073 2000 0383 6235
BIC: BMCEMAMC
early brid from 15 Jul until sep 30, 2025
On-site after sep 30, 2025 until oct 15, 2025
early brid from 15 Jul until sep 30, 2025
On-site after sep 30, 2025 until oct 15, 2025
early brid from 15 Jul until sep 30, 2025
On-site after sep 30, 2025 until oct 15, 2025
Kindly select your mode of participation: oral communication with paper, oral communication without paper, or attendance without presentation
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