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11. Other Relevant Topics in AI:

Important Dates

Submission
Deadline

May 31, 2025

June 23, 2025

June 30, 2025

Authors
Notification

August 15, 2025

Camera-ready
Deadline

August 31, 2025

Keynote Speakers

Prof. Habib Zaidi

Head of PET Instrumentation & Neuroimaging Laboratory at Geneva University Hospital,
and Professor at the medical school of Geneva University, Switzerland.

Title of Talk: Adventures in deep learning-powered Multimodality Medical Imaging Wonderland

Abstract : Positron emission tomography (PET), x-ray computed tomography (CT), magnetic resonance imaging (MRI), and their combinations (PET/CT and PET/MRI) provide powerful multimodality techniques for in vivo imaging. This talk presents the fundamental principles of multimodality imaging and reviews the major applications of artificial intelligence (AI), in particular deep learning approaches, in multimodality medical image analysis. It will inform the audience about a series of advanced developments recently carried out at the PET instrumentation & Neuroimaging Lab of Geneva University Hospital and other active research groups. To this end, the applications of deep learning in five generic fields of multimodality medical imaging, including imaging instrumentation design, image denoising (low-dose imaging), image reconstruction, quantification and segmentation, radiation dosimetry, and computer-aided diagnosis and outcome prediction, are discussed. Deep learning algorithms have been widely utilized in various medical image analysis problems owing to the promising results achieved in image reconstruction, segmentation, regression, denoising (low-dose scanning), and radiomics analysis. This talk reflects the tremendous increase in interest in quantitative molecular imaging using deep learning techniques in the past decade to improve image quality and to obtain quantitatively accurate data from dedicated standalone (CT, MRI, SPECT, PET) and combined PET/CT and PET/MRI imaging systems. The deployment of DL-powered methods when exposed to a different test dataset requires ensuring that the developed model has sufficient generalizability. This is an important part of quality control measures prior to implementation in the clinic. Novel deep learning techniques are revolutionizing clinical practice and are now offering unique capabilities to the clinical medical imaging community. Future opportunities and the challenges facing the adoption of deep learning approaches and their role in molecular imaging research are also addressed.

Speaker's Short Bio

Short Bio
Habib Zaidi is Chief physicist and head of the PET Instrumentation & Neuroimaging Laboratory at Geneva University Hospital and a full Professor at the medical school of the University of Geneva. He is also a Professor at the University of Groningen (Netherlands), the University of Southern Denmark (Denmark), and Óbuda University (Hungary). His research is supported by the Swiss National Foundation, the European Commission, private foundations, and industry (Total 11 M+ US$) and centres on hybrid imaging instrumentation (PET/CT and PET/MRI), computational modelling and radiation dosimetry, and deep learning. He was a guest editor for 14 special issues of peer-reviewed journals and serves as founding Editor-in-Chief (scientific) of the British Journal of Radiology (BJR)|Open, Deputy Editor for Medical Physics, and is on the editorial board of leading journals in medical physics and medical imaging. He has been elevated to the grade of fellow of the IEEE, AIMBE, AAPM, IOMP, AAIA, and the BIR. His academic accomplishments in the area of quantitative PET imaging and artificial intelligence-powered multimodality imaging have been well recognized by his peers since he is a recipient of many awards and distinctions among which the prestigious (100’000$) 2010 Kuwait Prize of Applied Sciences (known as the Middle Eastern Nobel Prize) and the 2023 John Mallard Award given by the International Organization for Medical Physics for innovative developments of high scientific quality. Prof. Zaidi has been an invited speaker of over 250 keynote lectures and talks at an international level, has authored over 455+ peer-reviewed articles (h-index=81, more than 24400 citations) in prominent journals, and is the editor of four textbooks.

Prof. Eyad Elyan

Founder and head of the Interactive Machine Vision research group,
School of Computing, Robert Gordon University, UK.

Title of Talk: Practical and Affordable AI: Strategies and Practical Lessons for Sustainable Digital Transformation in Developing Regions

Abstract : Artificial intelligence and machine learning have transformed industries worldwide. Despite this unprecedented progress, developing regions often lag in AI adoption due to infrastructure limitations and resource constraints. This presentation addresses the need for practical AI implementation strategies tailored to emerging economies. The focus will be on fostering data-driven, AI-powered solutions that cross disciplinary boundaries to enhance quality of life. The talk will open with an overview of AI and the current generative AI landscape and trends. Then, key components for successful digital transformation will be outlined. Following this, real-world case studies from multiple sectors will be presented with emphasis on the Oil and Gas Industry. Through these, attendees will gain both theoretical insights and practical tips for initiating and implementing AI-driven solutions with relatively limited resources. The presentation concludes with an overview of challenges, opportunities, and a comprehensive roadmap for digital transformation across various domains, providing the audience with practical lessons to start and manage the AI journey and drive innovation.

Speaker's Short Bio

Short Bio
Eyad is a renowned researcher in Machine Learning and AI and leads Robert Gordon University’s Machine Vision research Group. He has pioneered the development of AI-driven solutions across different domains and helped businesses to intelligently transform existing practices. Following his completion of a PhD in 3D modelling and human face recognition at the University of Bradford, he joined Robert Gordon University School of Computing as a lecturer in 2009. He then progressed to be a Senior Lecturer in 2015 and a Reader in 2018. In 2020, he was promoted to full Professor in AI. His research is focused on applied computer vision and machine learning. He collaborates extensively with various industries across the UK, actively contributing to the creation of state-of-the-art AI solutions to optimise and digitally transform their operations. Notable examples of his work are his pioneering contribution to the development of an end-to-end solution for processing and analysing Piping and Instrumentation Diagrams (P&ID) between 2017 and 2019. By leveraging advanced technologies for the automatic analysis and processing of complex documents and P&ID diagrams, the project successfully transformed complex and unstructured diagrams into actionable insights , as well as his work on developing AI-driven solutions for remote inspections of Oil and Gas Assets.
Elyan is a Fellow member of the British Higher Education Academy and serves as the Scotland Data Lab Innovation Centre Ambassador. He plays a lead organizing role in various national and prestigious international events, reviewing for many leading international journals in the area of artificial intelligence, computer vision, and machine learning, and is a reviewer for research councils such as EPSRC. He has given numerous talks in the area of Machine Learning, AI, and Big Data Analytics, supervised seven PhD students to successful completion, and examined more than fourteen PhD students at different UK universities.
With a track record encompassing over 100 publications in AI and Machine Learning, supervision of 12 successful PhD completions, and leadership on more than 30 innovative industry projects, he was recognised with the UK Knowledge Transfer Partnership Academic of the Year award in 2023 , an award that is given to individuals for their exceptional skills and commitment in knowledge translation, leadership, team building, and mentoring. In 2024, he was shortlisted as a finalist for the Scottish Knowledge Exchange Award for his contribution to knowledge exchange and innovation in Scotland.

Dr. Imed Zitouni

Director of Engineering - GenAI, ML & Search, Google, USA.

Title of Talk: The LLM Revolution: Shaping Digital Transformation with Generative AI

Abstract : Large Language Models (LLMs) are revolutionizing artificial intelligence and profoundly impacting digital transformation across all industries. This presentation provides a focused overview of the trajectory from traditional Language Models (LMs) to the cutting-edge LLMs driving the generative AI revolution. We will examine the historical context, key technological advancements, and the unique capabilities of LLMs, including their ability to process and generate human-like text at scale. Special attention will be given to how breakthroughs in neural network architectures and the availability of vast datasets have fueled this progress. Furthermore, the session will initiate a discussion on the potential impact of these technologies on digital transformation research, development, and information processing.

Speaker's Short Bio

Short Bio
Dr. Imed Zitouni is a distinguished technology expert with over two decades of experience specializing in artificial intelligence, particularly in natural language processing (NLU), information retrieval, and speech recognition. He joined Google in 2019, where he leads initiatives applying NLU, Knowledge Graph, Encoder, and generative models to enhance Google Search capabilities with large language models (LLMs). Prior to his tenure at Google, from 2012 to 2019, Zitouni played a pivotal role at Microsoft. There, he spearheaded the NLU and Conversation Engine capabilities for the Cortana Smart speaker and was responsible for the Bing Measurement group, which defined user metrics and enabled A/B experimentation. Between 2004 and 2012, Zitouni served as a Senior Research Lead at the IBM Watson Research Center. His work there focused on various AI challenges, including information extraction and healthcare applications for the groundbreaking Watson initiative. Earlier in his career, he spent six years as a research scientist at Bell Labs, Lucent Technologies, contributing to speech recognition and dialog systems for DARPA projects. Imed Zitouni holds an M.Sc. and Ph.D. from the University-of-Nancy1 and INRIA in France, as well as an MEng degree in Computer Science from ENSI, Tunisia. His impactful contributions to AI have garnered significant recognition, including being named one of the "30 Leading Arab Experts in AI" by MIT Technology in 2022 and receiving the Tunisian AI Awards 2024 from the Tunisian AI Society. He is a prolific author, with two books and over 100 patents and scientific papers to his name.

Committees

Honorary Chair

Pr. Aly Mohamed Salem Boukhary
President, Nouakchott University, Mauritania

Organizing Committee

Mohamed Abdel Wedoud M'hamed(Chair)
Vice-Dean of Faculty of Sciences and Techniques, Nouakchott University, Nouakchott, Mauritania

CHEIKH Sidi(Vice-Chair)
Faculty of Sciences and Techniques, Nouakchott University, Nouakchott, Mauritania

Members

HIMEIDY Mohamed
Faculty of Sciences and Techniques, Nouakchott University, Mauritania

AHMED Sidi Mohamed
Faculty of Sciences and Techniques, Nouakchott University, Mauritania

CHEIKH Ahmed Salem
Faculty of Sciences and Techniques, Nouakchott University, Mauritania

DIAKITE Mohamed Lamine
Faculty of Sciences and Techniques, Nouakchott University, Nouakchott, Mauritania

EL BENANY Mohamed Mahmoud
Faculty of Sciences and Techniques, Nouakchott University, Nouakchott, Mauritania

MOHAMED SALECK Fatimetou
Faculty of Sciences and Techniques, Nouakchott University, Nouakchott, Mauritania

MOHAMEDEN Ahmed
Faculty of Sciences and Techniques, Nouakchott University, Nouakchott, Mauritania

MOHAMEDOU EL GHOTOB Cheikh Tourad
Faculty of Sciences and Techniques, Nouakchott University, Mauritania

SALIHI Mohamed Lamine
Faculty of Sciences and Techniques, Nouakchott University, Mauritania

SID’AHMED Marième
Faculty of Sciences and Techniques, Nouakchott University, Mauritania

SIDI El Veth
Faculty of Sciences and Techniques, Nouakchott University, Mauritania

Med Vall Zeyad
Faculty of Sciences and Techniques, Nouakchott University, Mauritania

Exhibitions Committee

MOHAMEDOU EL GHOTOB Cheikh Tourad(Coordinator)
Faculty of Sciences and Techniques, Nouakchott University, Mauritania

Logistics Committee

Fatimetou Mohamed-Saleck(Coordinator)
Faculty of Sciences and Techniques, Nouakchott University, Mauritania

Scientific Committee

Steering Board

MOHAMED ELHADJ Yahya (Chair)
DAHD, Arab Center for Research and Policy Studies, Qatar

ABDUL-MAGEED Muhammad
University of British Columbia (Canada)& Mohamed bin Zayed University of Artificial Intelligence (UAE)

DERICHE Mohamed
College of Engineering and Information Technology, Ajman university, UAE

JEMNI Mohamed
LaTICe, University of Tunis, Director of ICT (ALECSO), Tunisia

KOUBAA Anis
College of Engineering, Alfaisal University

KOUZOU Abdella
Ziane Achour University of Djelfa, Djelfa, Algeria

MEZIANE Farid
College of Science and Engineering, University of Derby, UK

NANNE Mohamedade Farouk
Faculty of Sciences and Techniques, Nouakchott University, Mauritania

Members

ABDELALI Ahmed
National Center for AI, SDAIA, KSA

ABDELOUAFI Meziane
Faculty of Sciences, Mohammed First University, Morocco

AL-KHATIB Wasfi
King Fahd University of Petroleum and Minerals, KSA

AL-MUBAID Hisham
University of Houston-Clear Lake, USA

AL-SALEHI Abdulrahman
COMSATS University Islamabad, Pakistan

AZROUR Mourade
Faculty of Sciences and Technics, Moulay Ismail University, Morocco

BEN ABDALLAH BEN LAMINE Sana
ENSI, University of Manouba, Tunisia

BEN NASER Hashmi
Imam Muhammad Bin Saud Islamic University, KSA

BEN ROMDHANE Karim
Zitouna University, Tunisia

BEN SAID Ahmed
Qatar University, Qatar

BIHA Sidi
ESP, Mauritania

BOUAHADDA Hanen
Faculté des sciences de Tunis FST, Tunisia

CHAFFAR Soumaya
University of Prince Mugrin (UPM), KSA

CHEIKH Sidi
Faculty of Sciences and Techniques, Nouakchott University, Mauritania

Scientific Committee (continuation)

CHEIKH TOURAD Mohamedou
Faculty of Sciences and Techniques, Nouakchott University, Mauritania

DADI El Wardani
National School of Applied Sciences, Abdelmalek Essaadi University, Morocco

DEMBA Moussa
Institut Supérieur du Numérique (Sup Num), Mauritania

DHIB Cheikh
Institut Supérieur du Numérique (Sup Num), Mauritania

DIAKITÉ Mohamed Lamine
Nouakchott University, Mauritania

EJBALI Ridha
Faculty of Sciences, University of Gabes, Tunisia

EL AOUN Moustapha
Ecole Supérieure Polytechnique (ESP), Mauritania

ELHAYEK Ahmed
University of Prince Mugrin (UPM), KSA

GUESSOUM Ahmed
National School of Artificial Intelligence, USTHB University, Algeria

HARRAG Fouzi
College of Sciences, Ferhat Abbas University, Algeria

IDRIS Salim
Damascus University, Syria

JABBAR Rateb
Qatar University, Qatar

KRAIEM Naoufel
College of Computer Science, King Khalid University, KSA

LACHGAR Mohamed
Cadi Ayyad University, Morocco

LAKHOUAJA Abdelhak
Faculty of Sciences, Mohammed First University, Morocco

MAZROUI Azzeddine
University Mohammed First, Morocco

MOHAMED BABOU Hafedh
Ecole Supérieure Polytechnique (ESP), Mauritania

MOHAMED DILLA Mohamed El Hacen
Institut Supérieur de Génie Industriel (ISGI), Mauritania

MOHAMED MAHMOUD El Benany
Faculty of Sciences and Techniques, Nouakchott University, Mauritania

MOHAMEDEN Ahmed
Faculty of Sciences and Techniques, Nouakchott University, Mauritania

MOUHNI Naoual
FST Errachidia, Moulay Ismail University of Meknes, Morocco

OULD ELHASSEN AOUEILEYINE Mohamed
SupCom, Cartage University, Tunisia

OUTFAROUIN Ahmad
Ibn Zohr University, Morocco

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Scientific Committee (continuation)

PALUMBO Fabrizio
Oslo Metropolitan University, Norvège

SAFAA El Ouahabi
Polydisciplinary Faculty of Nador, Mohammed First University, Morocco

SAKLY Houneida
National School of Computer Sciences, University of Mannouba, Tunisia

SALEH Hussain
Damascus University, Syria

SI LHOUSSAIN Aouragh
ENSIAS, Mohamed V University, Morocco

SOUFAN Othman
University of Prince Mugrin (UPM), KSA

TOURAD DIALLO Mamadou
Institut Supérieur du Numérique (Sup Num), Mauritania

YOUSFI Abdellah
Faculty of Law, Economics and Social Sciences, University of Mohamed V, Morocco

ZERROUKI Taha
ESI, Bouira University, Algeria

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Workshops Committee

EL BENANY Med Mahmoud(Coordinator)
Faculty of Sciences and Techniques, Nouakchott University, Nouakchott, Mauritania

Session Committee

Ahmed Mohameden(Coordinator)
Faculty of Sciences and Techniques, Nouakchott University, Mauritania

Registration Committee

EL Veth Sidi(Coordinator)
Faculty of Sciences and Techniques, Nouakchott University, Nouakchott, Mauritania

Communication Committee

Sidi Mohamed Ahmed(Coordinator)
Faculty of Sciences and Techniques, Nouakchott University, Mauritania

Submission

Click the icon to download the Call for Papers

Call for Papers
We are soliciting original contributions that align with the conference's objectives and topics, illustrating the latest research advancements and practical implementations of artificial intelligence (AI) and machine learning (ML) technologies, with a particular emphasis on their potential to drive positive change in developing countries.

Click the icon to download the Paper Template

Submission guidelines
• Contributions should not have been published elsewhere or be under consideration for publication.
• Contributions should be written in English and formatted using Springer style template.
• Contributions should be submitted in full length, between 8 and 15 pages, via the submission system.
• Contributions will be rigorously peer reviewed and checked against any kind of plagiarism.

About this Book Series

Publication
I2COMSAPP'25 proceedings will be published by Springer (confirmed):
• All accepted and presented papers will be included in the Conference Proceedings and published by Springer in its Scopus-indexed Lecture Notes in Networks and Systems (LNNS) book series (Scopus, Web of Science, SCImago, INSPEC, etc.). The 1st edition was successfully published by Springer in the same book series ( https://link.springer.com/conference/i2comsapp ).
• Selected outstanding papers will be invited to submit an extended version to some reputable journals, which will be indicated later.

Click to submit your paper

Workshops

Workshop 1 CANCELLED

Harnessing AI for Academic Excellence: A Guide for Economics and Law

The workshop aims to foster meaningful dialogue among faculty in Economics and Law about integrating AI into educational practice, highlighting its benefits and potential applications. It will offer strategies to enhance student learning through AI while ensuring adherence to Academic Integrity policies specific to these fields. The facilitator will utilize active learning approaches such as small-group debates, case studies relevant to Economics and Law, and interactive discussions to encourage collaboration and engagement. Participants will be guided to reflect on their teaching methods, exchange ideas with peers, and collaboratively apply AI-driven innovations to their teaching. Ethical considerations, particularly relevant to Economics and Law, will be a focal point of the workshop. Discussions will address issues such as ethical use of data, potential biases in AI algorithms, and preserving the essential human elements of teaching amidst technological integration. Participants will contemplate these ethical dimensions and develop strategies to navigate them responsibly. Finally, attendees will use AI tools to design a course module in their disciplines, which includes crafting learning outcomes, selecting appropriate pedagogical strategies, and aligning assessment tools—incorporating AI effectively in their course design process.

Presenters:

Cheikh Ould Moulaye, Ph. D., Senior Instructor, University of Manitoba, Canada.

Workshop 2

Emerging Trends in Large Language Models

Large Language Models (LLMs) are revolutionizing how humans interact with technology, transforming fields ranging from education and healthcare to creative arts and industry. With unprecedented abilities to comprehend, generate, and reason through human language, LLMs open new possibilities for innovation, problem-solving, and productivity. As these models rapidly evolve, understanding the emerging trends and capabilities becomes crucial to unlocking their full potential across diverse domains. This comprehensive workshop dives deeply into the most exciting and influential developments shaping today’s LLM landscape. Participants will explore advanced reasoning techniques that allow models to handle complex problems, multimodal capabilities enabling integration across text, audio, and visual modalities, and state-of-the-art methods in prompt engineering that maximize model effectiveness. Practical, hands-on sessions will showcase retrieval-augmented generation (RAG), instruction tuning, external tool integration, and extended context windows, highlighting how these innovations substantially improve model accuracy, coherence, and applicability. Additionally, the workshop introduces agent-based systems and agentic workflows, illustrating how LLMs can autonomously orchestrate multiple tasks, reason over outcomes, and collaborate dynamically with other AI systems or external APIs. Participants will learn to design, deploy, and optimize LLM-driven agents capable of achieving complex objectives in real-world applications. Tailored to researchers, developers, and industry professionals, this workshop offers both theoretical insights and practical skills, empowering attendees to lead the next wave of AI-driven innovation.

Presenters:

Group of expert scientists and professionals from different Universities, MBZUAI and others.

Workshop 3

Building an Artificial Intelligence of Things (AIoT) System

This workshop will guide participants through the complete process of building an AIoT system, from data collection to AI model deployment on edge devices. Participants will learn how to integrate AI with IoT to create intelligent, autonomous, and resource-efficient systems. The session will focus on the synergy between IoT, AI, and Edge Computing, with practical hands-on activities using Edge Impulse, Collab and edge computing platforms.

Presenters:

Dr. Eng. Mohamed Ould-Elhassen Aoueileyine from Innov’COM Lab, SUPCOM, University of Carthage, Tunisia.

Registrations

Conference Registration

For your visa application, please proceed through the following link as soon as you receive the official supporting letter from the conference organizers:
🔗 Application link
Once you’ve submitted your application, kindly share the tracking number with us so we can assist with the follow-up process.

At least one author of each paper must be registered to I2ComsApp Conference. The registration details are indicated below :

Registration Contact :
i2comm2025@gmail.com
Whatsapp: + 222 46 76 88 11
For I2COMSAPP registration fee payment, please make the relevant amount transfer to the following account number :

• From outside Mauritania
Bank name : Banque Islamique de Mauritanie (BIM)
Bank adress : Zone Universitaire N° : 0333 TVZ, Nouakchott, Mauritania
Bank holder name : Association Ibtikar
Compte RIB : 00015 00001 210 095093 01 88
IBAN : MR1300015 00001 210 095093 01 88
SWIFT : BIMMMRMRXXX

Authors

Student

FREE: for those attending the conference.
FEE of 50 USD: for those presenting remotely.

Non-student

100 USD

(≈4000 MRU)

Registration fees include:
• Conference Daily Lunch
• Coffee Breaks
• An attendance certificate in Arabic and English language

Attendees (Non-authors)

Student

75 USD

(≈3000 MRU)

Non-student

150 USD

(≈6000 MRU)

Registration fees include:
• Conference Daily Lunch
• Coffee Breaks
• An attendance certificate in Arabic and English language

Workshops Registration

Student

50 USD

(≈2000 MRU)

Registration fees include:
• Conference Daily Lunch
• Coffee Breaks
• An attendance certificate in Arabic and English language

Non-student

100 USD

(≈4000 MRU)

Registration fees include:
• Conference Daily Lunch
• Coffee Breaks
• An attendance certificate in Arabic and English language

Click to register

Discussion Panels

Future of AI : Predictions from industry leaders

Ethics in AI : An open dialogue with experts

Previous Edition

Edition 2024

Exhibitions

Click the icon to download the Sponsorship Brochure

We invite businesses working in the field of Artificial Intelligence (AI) and machine learning (ML) to showcase their cutting-edge solutions and technologies at the "I2COMSAPP International Conference on Artificial Intelligence and its Applications in the Age of Digital Transformation".This event provides them with a unique platform to exhibit their AI-related products and services, connect with a diverse audience of experts, researchers, and practitioners, and explore potential collaborations and partnerships.
Your participation can help shape the future of AI and its real-world applicationsand contribute to the advancement of AI technologies that are driving positive change in various sectors.

For proposals, please send email to :
1) International Contact (from outside Mauritania): chair@i2comsapp.org
2) Local Contact (from inside Mauritania): mas.infoo23@gmail.com

Accomodation

Sunset Hotel

Single room: 110 euros
Double room: 125 euros

Hotel Website

Nouakchott Hotel

Single room: 109 euros
Double room: 136 euros

Hotel Website

Fasq Hotel

Single room: 225 euros
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Hotel Website

Collaborators

Best Paper Award!

Registration!