Research

Goal: The development of an effective CAD system based on deep learning, an innovative and promising technology in recent years.

Members: Pr. Amroune Mohamed, Pr. Hakim Bendjenna, Pr. Abdallah Meraoumia, Dr. Issam Bendib, Dr. Haouam Med Yassine, Dr. Salima Bourougaa, Dr. Othmani Iman, Dr. Haouam Lotfi, Hama Soltani (PhD student).

Starting Date: 2022 | Duration: 3 years

Full Description: In view of the increase in the number of mammograms in recent years, various research studies have been carried out either to automatically detect lesions – i.e. micro-calcifications or masses – in the images using computer-aided detection systems to provide a second opinion about the lesion detected through computer-aided diagnosis systems. This has led to the design of several mammographic image processing methods. The goal of this project is the development of adequate and effective CAD (Computer Aided Diagnosis) system based on deep learning approach which is considered as an innovative and promising technology in recent years.

Goal: To develop a diagnostic aid system based on AI techniques to address time and precision challenges.

Members: Pr. Hakim Bendjenna, Dr. Gasmi Mohamed, Mr. Ghenai Charaf Eddine (PhD student).

Starting Date: 2022 | Duration: 4 years

Full Description: Artificial intelligence has permeated all domains, especially those in which the human mind is strongly compelled to think and experiment. It represents a current topic in anatomical pathology, explaining the exponential increase in its involvement, particularly in medical detection and diagnosis. This will induce a future transformation of the pathologist profession and will change the role of anatomical pathology in the healthcare system. Since machines have demonstrated a level of maturity and accuracy in diagnostic results that surpasses that of a human being, we aim to develop a diagnostic aid system based on AI techniques to address the issues of time and precision. This project aims to utilize artificial intelligence to enhance and expedite the diagnosis of diseases through digitized slides of anatomical pathology. It will considerably ease patient management through the digitization of diagnostic processes based on the use of various antibodies. We propose a tele-diagnostic and expertise system among pathologists.

Goal: To develop a system for detecting neural diseases based on handwriting analysis.

Members: Dr. Taher Mekhaznia, Dr. Bennour Akram, PhD students: Asma Aoun Allah, Tag Samir, Souli Yassine, Mahmoudi Rachid, Benredjem Sabrina, Boudraa Merouane, Kaber Nour El Houda.

Starting Date: 2022 | Duration: 4 years

Full Description: Neural cells are irreplaceable, and the loss of control over muscles due to neural diseases leads to movement disorders. The project aims to detect early signs of diseases like Alzheimer’s and Parkinson’s through handwriting analysis. This approach allows early detection, preventing the disease's proliferation. Handwriting is sensitive to changes in human behavior due to depression, fatigue, etc., and can serve as an early detection tool for specialists.

Goal: To develop AI tools that assist healthcare professionals in accurately diagnosing pulmonary diseases.

Members: Dr. Akram Bennour, PhD students: Gaham Oussama, Farah Hamza.

Starting Date: 2023 | Duration: 4 years

Full Description: This project focuses on leveraging AI and machine learning algorithms to assist in pulmonary disease diagnosis. The innovative AI tools developed will optimize the healthcare process and improve diagnostic accuracy. The project will be conducted in modules, with intermediate objectives and experimental phases, ensuring continual progress toward better patient outcomes.

Goal: To develop an intelligent and scalable system for monitoring and inspecting corrosion in industrial infrastructures.

Members: Dr. Mohamed Yassine Haouam, Dr. Merzoug Soltane, PhD student Touat Hamad Zineb.

Starting Date: 2023 | Duration: 4 years

Full Description: The detection and monitoring of corrosion are essential for reducing the lifecycle cost of industrial infrastructures. This project aims to develop an intelligent system that extends the life of equipment, reduces maintenance costs, and minimizes human intervention in dangerous situations. The system will be scalable, adaptive, and able to conduct efficient monitoring of corrosion across various platforms.

Goal: To develop intelligent systems that predict and diagnose cardiovascular pathologies using machine learning.

Members: Dr. Issam Bendib, Pr. Mohamed Amroune, Dr. Mohamed Yassine Haouam, PhD students: Ali Adjal, Fares Soufiane Mazouni, Faycel Merzag.

Starting Date: 2023 | Duration: 4 years

Full Description: Cardiovascular diseases (CVDs) are a leading cause of mortality and impose a significant burden on the healthcare system. This project uses machine learning and deep learning techniques to predict cardiovascular diseases early, providing valuable tools for healthcare professionals. The system will collect data on cardiac pathologies and related diseases from Algerian patients to aid in early detection and treatment.

Goal: To design a secure E-Government model that satisfies authentication and access control through biometric systems.

Members: Dr. Laimeche Lakhdar, Dr. Haouam Med Yassine, PhD students: Makhlouf Ziad Eddine, Gharbi Abdelhakim, Toureche Amina, Kenaza Rabah, Khemane Ameur, Ferik Brahim.

Starting Date: 2022 | Duration: 4 years

Full Description: Algeria’s E-Government ranking is improving, and this project aims to strengthen it by developing a secure, deep learning-based biometric authentication model. The focus is on ensuring secure access to government services, improving data protection, and increasing public trust in digital government systems.

Goal: To explore and apply fixed point theory in various mathematical and economic models.

Members: Dr. Khaled Berrah, Dr. Nabti Abderrazek, PhD students: Sadi Saleh, Hadjadj Randa, Chettouh Kamilia.

Starting Date: 2023 | Duration: 4 years

Full Description: Fixed point theorems are essential tools for proving the existence and uniqueness of solutions in mathematical models. This project will focus on applying these theorems to dynamic systems and economic problems, including the analysis of the Algerian economy using dynamic system models.

Goal: To study the existence, stability, and explosion of solutions to nonlinear evolution problems and establish new conditions regarding the interaction between damping and source terms.

Members: Pr. Boumaza Nouri, Saker Meriem (PhD student), Khaoula Merzoug (PhD student).

Starting Date: 2022 | Duration: 4 years

Full Description: The problem in this research axis is to study the existence, stability, and explosion of solutions to posed problems (nonlinear evolution problems) and to search for new conditions on the interaction between the damping term and the source term.

Goal: To explore conditions that promote system stabilization towards equilibrium and investigate causes of system destabilization, including finite-time explosion.

Members: Pr. Mesloub Fatiha, Pr. Zarai Abderrahmane, Benzahi Mourad (PhD student), Merah Ahlem (PhD student), Toualbia Sarra (PhD student).

Starting Date: 2021 | Duration: 4 years

Full Description: The proposed problems constitute a major research axis. Initially, it involves testing existing techniques and methods on new problems that naturally arise in various application domains. Subsequently, improving conditions and extending results to other, more general situations by modifying existing methods, and potentially establishing new techniques capable of solving the problems under investigation. The question of local existence, while it may pose technical complications and serves as the initial step before proceeding further, in our opinion, does not necessarily constitute a major contribution. Rather, our primary interest lies in the preference for exponential stabilization of the system towards equilibrium and the conditions favoring system destabilization, particularly finite-time explosion.