6^th Artificial Intelligence Doctoral symposium
AID'2025

Scope and Topics

The Laboratory of Research in Artificial Intelligence (LRIA) of the department of Artificial Intelligence and Data Science (IASD) at the University of Science and Technology Houari Boumediene (USTHB) organizes the 6th Artificial Intelligence Doctoral symposium (AID'2025) to be held on November 9-10, 2025, in Algiers, Algeria at USTHB.
The AID'2025 is open to all PhD students conducting research in Artificial Intelligence (AI) as well as in Quantum Computing, which is gaining increasing importance in solving complex and large-scale problems. AID'2025 will place a particular emphasis on innovative research at the intersection of AI and quantum technologies. The symposium offers a unique opportunity for doctoral students to present their research, receive feedback from domain experts, and interact with other researchers in a dynamic and supportive environment. A selection of the best papers will be presented during oral sessions. The event will also feature invited talks from prominent researchers in both AI and Quantum Computing.
Prospective authors are cordially invited to submit papers in all areas related to Artificial Intelligence and Quantum Computing including, but not limited to, the following topics :

Where

In Algiers, Algeria at USTHB

When

November 09-10, 2025

CFP

Call For Papers

Honorary Chair

• Prof. Emerit. Habiba ZERKAOUI-DRIAS, LRIA, USTHB, Algeria

General Chair

• Dr. Lyes ABADA, LRIA, USTHB, Algeria

Co-General Chair

• Dr. Naila Aziza HOUACINE, LRIA, USTHB, Algeria

Program Committee Chair

• Dr. Ilyes KHENNAK, LRIA, USTHB, Algeria

Steering Committee

• Prof. Saliha AOUAT, LRIA, USTHB, Algeria
• Prof. Hamid AZZOUNE, LRIA, USTHB, Algeria
• Prof. Dalila BOUGHACI, LRIA, USTHB, Algeria
• Prof. Habiba DRIAS, LRIA, USTHB, Algeria
• Prof. Samir KECHID, LRIA, USTHB, Algeria
• Prof. Feryel SOUAMI, LRIA, USTHB, Algeria
• Dr. Lyes ABADA, LRIA, USTHB, Algeria
• Dr. Djamila DAHMANI, LRIA, USTHB, Algeria

Program Committee Co-Chair

• Dr. Lyes ABADA, LRIA, USTHB, Algeria

Program Committee

• Dr. Lyes ABADA
• Dr. El-Amine AMEUR
• Prof. Saliha AOUAT
• Prof. Hamid AZZOUNE
• Dr. Sadjia BABA-ALI
• Prof. Nadia BAHA-TOUZÈNE
• Dr. Fatma Zohra BELLALA
• Dr. Khadidja BELLATAR
• Dr. Lamia BERKANI
• Dr. Ikram BIDA
• Prof. Dalila BOUGHACI
• Dr. Lokmane CHEBOUBA
• Dr. Djamila DAHMANI
• Dr. Yassine DRIAS
• Dr. Adel GOT
• Prof. Allel HADJALI
• Dr. Kamel Eddine HERAGUEMI
• Dr. Célia HIRECHE
• Dr. Naila Aziza HOUACINE
• Dr. Selma KALI-ALI
• Prof. Nadjet KAMEL
• Prof. Samir KECHID
• Dr. Meriem KHELIFA
• Dr. Ilyes KHENNAK
• Dr. Abdelmadjid LAHRECHE
• Dr. Nacéra LAICHE
• Dr. Naoual MEBTOUCHE
• Dr. Imane MESSAOUDI
• Dr. Hadjer MOULAI
• Dr. Hamid NECIR
• Dr. Messaouda NEKKAA
• Dr. Tahar RAFA
• Dr. Abdellah REZOUG
• Dr. Zahia TAMEN
• Dr. Hanane TEBBI
• Prof. Farouk YALAOUI
• Prof. Emerit. Habiba ZERKAOUI-DRIAS

Organizing Committee Chairs

• Dr. Mohamed AIT MEHDI
• Dr. Widad Hassina BELKADI
• Dr. Naoual MEBTOUCHE
• Ms. Célia KHELFA

Organizing Committee (PhD Students, USTHB)

• Ms. Imane AMEUR
• Ms. Anfel AMIRAT
• Mr. Riad BOUARROUDJ
• Ms. Maria DJADI
• Mr. Laib Mohamed DJOUNAID
• Mr. Mehdi EL BAR
• Mr. Oualid Khaled FERFERA
• Ms. Maya HOUACINE
• Mohamed Lamine MIRA
• Ms. Ibtihel REZAIGUIA
• Mr. Abdelkrim SAHNOUNE
• Ms. Sonia ZEMMOUR

Prof. Sadok BEN YAHIA, University of Southern Denmark

Title

Sustainable urban mobility in the era of Agentic AI

Abstract

The rapid increase in urban populations has led to a significant rise in mobility demands in urban areas, posing a substantial challenge to the development of sustainable cities. This population growth has created an unprecedented burden on the transport infrastructure. In this respect, traffic congestion in cities is one of the inherent barriers to sustainable urban mobility development, as it increases energy use and Greenhouse Gas (GHG) emissions, which additionally magnify economic losses and reduce the overall quality of life.
In this talk, we explore innovative urban planning, investment in efficient public transportation systems, and the adoption of innovative mobility technologies, such as Intelligent Traffic Management (ITM) methods that leverage Artificial Intelligence (AI) design schemes like Large Language Models (LLMs) to accommodate growing populations while fostering efficient and inclusive urban environments. Starting with the efficient public transport sector, we will present an LLM-based Agentic ReAct Bus Eco-Driving Framework (LARBEF) with Reinforcement Learning (RL) as an agent equipped with Vehicle-to-Everything (V2X) communication technology to reduce various public bus types (Conventional Diesel, Electric, and Plug-in Hybrid Electric Buses) energy consumption and emissions by integrating real-time critical parameters, such as road slope, passenger load, ambient temperature, traffic lights, and queue length. For the ITM, we will present a Model Context Protocol-Based Agentic ReAct Large Language Model for Adaptive Traffic Signals (MARLATS) framework based on adaptive Traffic Management, with an RL agent equipped with V2X, to enhance energy consumption, emissions measures, traffic performance, and economic performance in large-scale cities.

Biography

Sadok BEN YAHIA Full Professor at the University of Southern Denmark (SDU) since September 2023. Before joining SDU, he was a full professor at the Technology University of Tallinn (TalTech) since January 2019. He obtained his HDR in Computer Sciences from the University of Montpellier (France) in April 2009. His research interests mainly focus on trustworthy & safe LLM-based AI systems and their application to urban mobility in smart cities (e.g., information aggregation & dissemination, traffic congestion prediction), Recommendation Systems, and fake content fighting.

Prof. Houari SAHRAOUI, Department of computer science and operations research, University of Montréal Canada

Title

No Size Fits All: Goal-Driven Alignment of LLMs for Software Engineering Tasks

Abstract

Large Language Models (LLMs) have shown remarkable capabilities in software engineering tasks ranging from modeling assistance to code generation. Yet, their effectiveness depends critically on alignment, ensuring that model outputs meet the objectives, constraints, and preferences of developers and organizations. This keynote will explore the challenges of aligning LLMs for software engineering, focusing on the tension between pretraining objectives and downstream alignment goals. I will discuss different strategies for alignment, including fine-tuning approaches and advanced prompting techniques, and highlight their strengths and limitations in practice. Through concrete examples such as preference-based code generation and domain-modeling assistance with LLMs, the talk will illustrate how alignment can improve relevance, usability, and trustworthiness of AI-powered software engineering tools. Finally, I will outline open research questions and opportunities for building next-generation aligned models that better serve the needs of software engineers and the broader software ecosystem.

Biography

Houari Sahraoui is a Professor at the GEODES software engineering lab within the Department of Computer Science and Operations Research at the Université de Montréal. He is also a Vice-Dean at the Faculty of Arts and Sciences. He earned his Ph.D. in Computer Science from Pierre & Marie Curie University (LIP6) in 1995, specializing in Artificial Intelligence. His research focuses on AI for Software Engineering, including software automation, model-driven engineering, digital twins, and generative AI for code and modeling tasks. He has published over 200 papers in top venues, earning multiple Best Paper and ACM SIGSOFT Distinguished Paper Awards as well as the IEEE TCSE 10-Year Most Influential Paper Award. He has held several leadership roles in the software engineering community, serving as General Chair of ASE, MODELS, and VISSOFT, Program Chair of VISSOFT and MODELS, and Program Committee member for numerous top-ranked IEEE and ACM conferences. He has also served as Associate Editor for three journals including Springer Software and System Modeling, and is a founding member of CS-Can | Info-Can, the Canadian society of computer science.