The Artificial Intelligence and Applications Laboratory

Introduction to the Laboratory
The Artificial Intelligence and Applications Laboratory is a research unit affiliated with the Faculty of Exact Sciences at the university. It provides an advanced scientific environment for researchers and doctoral students to address all challenges in the field of artificial intelligence, as well as all aspects of designing complex systems, from modeling to implementation. The laboratory is distinguished by its modern technical equipment and hosts numerous research teams, making it a platform well-suited for scientific exchange and research collaboration.

PR.Abdelkader Laouid
Director of the Artificial Intelligence Laboratory and its Applications
Objectives of the laboratory and the objectives of each research team
The Artificial Intelligence and Applications Laboratory aims to provide research opportunities to develop or improve solutions related to the challenges facing our environment. Additionally, the laboratory seeks to offer an advanced research and educational environment for researchers and doctoral students by providing the necessary tools and mechanisms for this purpose.
- • Team 1 strives to adapt traditional algorithms and apply them to networks suffering from significant resource constraints. Today’s world is interconnected with various types of mobile devices that offer numerous advantages but often face challenges related to energy, computational power, and limited storage units., ..
- • Team 2 aims to leverage artificial intelligence tools, methods, and techniques, as well as advanced information systems, to provide solutions and designs for applications in the agricultural sector in the Wadi and Southern regions.
- • Team 3 seeks to develop metaheuristic algorithms to study and analyze complex systems across multiple fields. The research focuses on using metaheuristics as tools for analyzing and designing complex dynamic systems, in addition to employing them to solve challenging mathematical optimization problems (NP-hard). Research applications span areas such as artificial intelligence, big data, energy, transportation, computer vision, smart cities, and the Internet of Things. Emphasis is also placed on developing hybrid models that combine multiple algorithms to achieve optimal performance in cloud and fog computing environments., .NP-difficile), ., ..
Description of the importance of laboratory equipment
The laboratory includes several modern equipment and technologies that encourage innovation and contribute to enhancing the research and educational environment, thereby improving the quality of research and scientific experiments. Some of these equipment include:,.:
- High-performance computers dedicated to research, design, and software modeling in the field of artificial intelligence.
- A 3D printer for creating initial models and prototypes of robots and producing essential components for projects and research in a tangible form.
- A drone for collecting images and geographic data crucial for training algorithms and models, as well as applying algorithms in real time., .
- A smart board for delivering interactive lessons and participating in national and international conferences.
Various chips, sensors, and electronic components for building specialized hardware and testing ideas realistically on a small scale.

Activities of the laboratory in collaboration with other entities
- Participation of doctoral students affiliated with the laboratory in the International Conference on Pattern Analysis and Intelligent Systems (PAIS '24), held on April 24-25, 2024, at the University of Chahid Hamma Lakhdar - El Oued. PAIS ’24 ..
Organization of a training workshop for doctoral students in the department titled "Unleashing the Power of Blockchain Technology Capabilities" on January 29, 2024, supervised by Dr. Noureddine Al-Asla, a professor at the Higher School of Artificial Intelligence - Algiers.

The human composition of the laboratory
First Research Team
Team Leader:
Name: Laouid Abdelkader
Rank: Professor
Specialization: informatique
Professional Email: [email protected]
Phone Number:0669124780

Name | Rank | Specialization | Professional Email | Phone Number | Personal Photo |
Madilh Essassi | Assistant Professor B | informatique | [email protected] | 0664611833 | |
Khalifa Abdel Nasser | Assistant Professor B | informatique | [email protected] | 0674199613 | |
Obeid Mohammed Nadhir | PhD Student | informatique | [email protected] | 0675463228 | |
Miloudi Amara | PhD Student | informatique | [email protected] | 0782837281 | |
Second Research Team | PhD Student | informatique | [email protected] | 0657843108 |
Second Research Team
Team Leader:
Name: Meftah Sharaf Eddine
Rank: Professor
Specialization: informatique
Professional Email: [email protected]
Phone Number:0661896380

Name | Rank | Specialization | Professional Email | Phone Number | Personal Photo |
Karthiu Ismail | Assistant Professor A | informatique | [email protected] | 0661667166 | ![]() |
Bali Muadh | Assistant Professor A | informatique | [email protected] | 0665510957 | ![]() |
Barjouh Shafiq | Assistant Professor B | informatique | [email protected] | 0699430284 | ![]() |
Righi Thabit | PhD Student | informatique | [email protected] | 0656669789 |
Third Research Team
Team Leader:
Name: Ben Ali Abdelkamel
Rank: Assistant Professor A
Specialization: informatique
Professional Email: [email protected]
Phone Number:0664425417

Name | Rank | Specialization | Professional Email | Phone Number | Personal Photo |
Elzaiz Fawzi | Assistant Professor B | informatique | [email protected] | 0780086823 | ![]() |
Hammoud Maryam | Assistant Professor B | informatique | [email protected] | 0550357304 | |
Yaqoub Mohammed Amin | Assistant Professor B | informatique | [email protected] | 0662748640 | ![]() |
Gaya Sanaa Sahar | Assistant Professor A | informatique | [email protected] | 0665949628 | |
Halouat Hakim Saif Eddine | PhD Student | informatique | [email protected] | 0676538606 | ![]() |
Ben Saleh Hazem | PhD Student | informatique | [email protected] | 0665079947 |
Fourth Research Team
Team Leader:
Name: Abbas Messaoud
Rank: Assistant Professor A
Specialization: informatique
Professional Email: [email protected]
Phone Number:0662307238

Name | Rank | Specialization | Professional Email | Phone Number | Personal Photo |
Bouchrit Ammar | Assistant Professor A | informatique | [email protected] | 0664256208 | ![]() |
Nawi Mohammed Anwar | Assistant Professor A | informatique | [email protected] | 0699562910 | |
Othmani Samir | Assistant Professor A | informatique | [email protected] | 0655989377 | |
samir guediri | PhD Student | informatique | [email protected] | 0664229249 | ![]() |
Elamouri Mohammed Lamine | PhD Student | informatique | [email protected] | 0674347589 | |
Bouhamed Mohammed Mounir | Assistant Professor B | informatique | [email protected] | 0676512199 | ![]() |
The scientific output of the Artificial Intelligence Laboratory.
- Arabic opinion mining using machine learning techniques: Algerian dialect as a case of study
- Rule-Based Arabic Sentiment Analysis using Binary Equilibrium Optimization Algorithm
- Machine learning to classify religious communities and detect extremism on social networks: Ml to crcs and de through text tweets on sns
- Machine/Deep Learning for obfuscated malware Detection
- Categorization of Digital Pathology Image using Deep Learning model
- Tuberculosis Detection Using Chest X-Ray Image Classification by Deep Learning
- Tuberculosis detection using chest X-ray image classification by deep learning
- Pelican Gorilla troop optimization based on Deep feed forward neural network for human activity abnormality detection in smart spaces
- An Intelligent Approach Based on Cleaning up of Inutile Contents for Extremism Detection and Classification in Social Networks
- A secure multi-agent-based decision model using a consensus mechanism for intelligent manufacturing tasks
- A Data Communication Based on Deep Learning Model for Efficient IoT Energy Clustering
- Enhancing Proximal Policy Optimization in the Pendulum-v1 Environment Through Clustering-Based State Space Simplification
- Comparative Analysis and Application of Large Language Models on FAQ Chatbots
- An intelligent agriculture monitoring framework for leaf disease detection using YOLOv7
- Intelligent Image Text Detection via Pixel Standard Deviation Representation
- A nature-inspired partial distance-based clustering algorithm
- Reinforcement Learning Approach for IoT Security using CyberBattleSim: A Simulation-based Study
- Using transformers to classify arabic dialects on social networks
- Techniques intelligentes pour la gestion de la cohérence des Big data dans le cloud
- The KD-GATS algorithm: A way for Optimizing Data Replication with Kruskal-Dijkstra and Genetic Tabu Strategy
- SMART Irrigation System (SMARTIS)—Desert Areas
- A CNN Model for Early Leukemia Diagnosis
- Human Activity Recognition with Anomaly Prediction for E-Health Systems using Lightweight AI
- Artificial Intelligence aware Knowledge Graphs and Deep Learning-Based Diagnostic Prediction Model in Healthcare
- Comprehensive learning TLBO with recursive precedence-based solution construction and multilevel local search for the linear ordering problem
- Improving damage classification via hybrid deep learning feature representations derived from post-earthquake aerial images
- A Hybrid GAN-ANN-Based Model for Diabetes Prediction
- POSTER – Perspectives d’utilisation de l’IA pour détecter et prends soin les TSA
- Intelligent models for early Autism detection from MRI images
- A maintainable and iterative development approach of critical systems with FoCaLiZe
- A rewriting logic based behaviour semantics of discrete event systems models with complex dynamics
- PN2Maude: An automatic tool to generate Maude specification for Petri net models
- An Example of a Dynamic CPN Model to Obtain Routes in the Presence of Obstacles Detected Using Machine Learning Techniques
- A deep-based compound model for lung cancer detection
- Dzchatbot: a medical assistant chatbot in the Algerian Arabic dialect using seq2seq model
- Federated learning for multi-institutional on 3D brain tumor segmentation