Mathematics and Computer Science

Domain

Mathematics and Computer Science

Discipline

Computer science

Presentation of the Doctoral Training

The doctoral training of the Computer Science Department is part of the overall framework outlined by the President of the Republic to ensure the development of Algeria in all sectors, however varied they may be. With the aim of implementing the outlined project, the Ministry of Higher Education and Scientific Research has defined a set of sectors in which research must be intensified, making these sectors battle horses. In order to meet the requirements of the Ministry, the Oran1 Ahmed Ben Bella University, through the Faculty of Exact & Applied Sciences and the Department of Computer Science, offers a Doctoral Training in perfect harmony with the recommendations of the supervisory authority. Reading the various supervision proposals shows that the axes of this training are varied. So, we can cite :

1-Artificial Intelligence and all the areas in which it can be applied;

2- Agriculture or precisely Smart-Farming which consists of determining effective means, which can be intelligent, which could give a high yield of the haciendas in terms of quality, quantity and economic cost;

3-Health. This area is of paramount importance, as progress in this sector is directly reflected in the citizen, who is a vital asset in society ;

4- Education. Works in this sector are not insignificant, given that education at all levels must produce generations who will carry Algeria on their shoulders;

5-Technology. This sector, as important as it is, is central to the battle for development, as it is the foundation upon which the success of previous sectors rests. In this context, we can encounter topics on security, cybersecurity, optimization, and networking, among others.

From what has just been put forward, among the objectives expected by this doctoral training, we can cite:

a- To train future executives with a high level of knowledge. This training will provide our future doctors with sufficient knowledge to be able to take the initiative and solve the problems they will face in their professional lives.

b- To enable future doctors to integrate into socio-professional life through the university. This will offer them a theoretical and practical framework through the practical and experimental part of their projects.

c- Prepare future doctors so that they can enter the university by participating in educational activities.

d- Provide doctoral students with scientific rigor so they can analyze problems and determine how to achieve objectives based on current means.

e- Allow doctoral students to deepen their knowledge in several fields. These include, among others: industrial computing, embedded computing, parallel computing, multi-objective optimization, task scheduling, monitoring, bio-inspired, biological computing, medical computing, project management, not forgetting the legislative framework for applications.

f- Offer doctoral students the opportunity to work on cross-disciplinary areas.

g- Helping doctoral students to get involved in current areas of data science, by addressing numerous aspects related to modelling, dynamic data mining, processing, sharing, visualization, information retrieval, classification, clustering, prediction and decision-making by making information easier to exploit, use, secure and enhance in intelligent decision-making systems.

We emphasize that the university works actively and tirelessly in training high-level researchers and executives because its share in the progress of our country is indisputable.

The doctoral training of the Computer Science Department of Oran1 Ahmed Ben Bella University consists of five specialties, four of which are supported by laboratories affiliated with the Computer Science Department, while the fifth is supported by the department itself since the teachers who participate in the supervision of this specialty are not members of these laboratories. Given the high number of teachers in the Computer Science Department and their long and experienced careers, our doctoral training is rich in diverse skills in all areas of computer science research. These skills cover industrial computing, embedded systems, parallel systems, artificial intelligence, data science, food safety, computer security and other aspects. This wealth of skills means that the proposed projects are linked to each other implicitly as well as explicitly.

From all that has just been highlighted, our doctoral training is in perfect harmony with the global strategy outlined.

Presentation of the five specialties

Specialty

Data Science

The Data Science specialty is a recent specialty, which has developed with the rise of data in the world. It comes from the intersection of the fields of data extraction, also called data mining, and statistical analysis. The Data Science specialty aims to equip doctoral students with the technical and analytical skills necessary to work effectively with data sets. The proposed topics will address fundamental, theoretical and practical aspects of all areas of data science that are highly topical. The corresponding research themes fall within the framework of the national reference framework of priority research axes, specifically in the main axis ²Technological Development² and sub-axis ²Artificial Intelligence².

We emphasize that the following research projects are related to this specialty and provide doctoral students with a pleasant working environment.

1. MAPSPADES: Mapping and Monitoring Spatiotemporal Desertification Patterns in the Steppic Belt of Algeria EO AFRICA R&D Research Projects

https://www.eoafrica-rd.org/research/research-projects-2023-2024/

2. Erasmus+ Project CUPAGIS " New curricula in Precision Agriculture using GIS technologies and sensing data "--- (EACEA): 597962-EPP-1-2018-1-EE-EPPKA2-CBHE-JP---https://www.cupagis.eu/

3. SEEDNAA. Spatial Data Infrastructures and Earth Observation Education and Training for North-Africa Erasmus + CBHE 610328-EPP-1 -2019-1-BE-EPPKA2-CBHE-JP https://seed4na.eu/ Type: Erasmus+ CBHE

Number of teaching places offered to foreign students

Three (04) places

Specialty

Embedded Systems Engineering and Parallelism

The Embedded Systems and Parallelism Engineering specialization covers the diverse aspects of computer science. Embedded systems are autonomous, operating in real time to perform specific tasks. These systems include both hardware and software. They must take into account limited constraints such as batteries and energy consumption. Embedded algorithms are state-of-the-art technology, and take into account the environment in which they run. Parallel systems in particular, and distributed systems in general, actually encompass all aspects of computing, as they run on parallel devices as well as distributed across the Internet. Parallel algorithms must be robust, and must ensure the functionality of the systems in which they run. In this way, this specialty spans all aspects of computer science, since it calls on aspects of software architecture, parallel algorithms, diagnostics, multi-criteria decisions, distributed algorithms, information retrieval, learning, pattern recognition, high-performance computing, hybridization of optimization methods, advanced aspects of metamodeling and model transformation. All the thesis topics on offer relate to strategic areas of national priority, namely: Artificial intelligence, Food safety by further developing precision or intelligent agriculture to improve crop quality and quantity (market gardening or arboriculture), Citizen safety by developing innovative solutions in the field of Smart-cities, Citizen health by implementing approaches and methods using artificial intelligence techniques, machine learning, deep learning and federated learning.

The following research projects are supported by this specialty :

1- Project Manager: ZekriLougmiri. Under the code C00L07UN310120220006 «Optimization Information Retrieval and Learning » 2022-2025

2- Project Manager: Loukil Lakhdar. Under theCode PRFU n°C00L07UN310120220005 "Evaluation of hydrodynamic and thermal constraints on fish activity in irrigation basins for the optimization of agro-fish production ", 2022-2025.

3- Project Manager: BENYAMINA AbouEl Hassane.Under thecode C00L07UN310120220010 «Using Artificial Intelligence to process acoustic data: Application to wild boar detection »2022-2025

4- Project Manager: Samy Touil. Under the code D04N01UN440120230001 « Precision agriculture for water resource management and a modern, sustainable ecological transition». 2023-2026

Partnershipprojectsbetweenthe Laboratoire des Architecture Parallèle, Embarquées et Du Parallélisme LAPECI and the laboratoryUDBKM.

National intersctorial Research PNR :

 Two Projects

1 - Theme “Integrated, efficient and intelligent management of bio-treated agricultural wastewater”, 2023-2025.

2- Theme: «Ecological Solutions and Integrated Water Resource Management (Eco-GIRE)»: 2023-2025

Number of teaching places offered to foreign students

Two(02) places

Specialty

ArtificialIntelligence and itset Applications

The Artificial Intelligence and its Applications specialization focuses on the practical, hands-on use of the most advanced AI techniques to solve real-life problems in diverse fields such as: citizen health, transportation, education, industry and more. These applications illustrate how AI is being used in a wide variety of fields to improve efficiency, accuracy and decision-making. By integrating AI techniques into practical applications, it is possible to solve complex problems and open up new opportunities in a wide range of sectors. Cette spécialité se focalise sur les trois aspects suivants :

1. Theoretical foundations of AI :

a- Study of the mathematical and algorithmic foundations of AI;

 b- Understanding and mastering these methods

2. Practical applications:

a-Exploring practical applications of AI in various fields such as pattern recognition, prediction, planning, optimization, decision-making, etc…

b- Intelligent systems implementation

3. Ethics and responsibility:

a- Study the ethical, social and legal implications of using AI, including data privacy, algorithmic discrimination, liability for autonomous decisions, etc…

b- Study of good design practices to ensure that the intelligent systems developed are used responsibly.

The following research projects are supported by this specialty :

1. Project Manager: HAMDADOU Djamila. decision support system dedicated to pharma-covigilance SIAD_PHARM 03/02/2022.

2. Project Manager: Belalem Ghalem: Respiratory pathology via artificial intelligence. 20/10/2021.

Number of teaching places offered to foreign students

Five (06) places

Specialty

Computer Systems

The Computer Systems specialization fits into the same profile as the Computer Science department's other specializations. The subjects proposed in this specialization fall within the scope of health and the citizen, as well as transportation. It also covers the field of agriculture, calling for IoT through the control of sensors that monitor in real time the various parameters that affect the crop, such as water salinity and temperature. These fields have a broad spectrum of problem-solving and solution applicability.

Number of teaching places offered to foreign students

Three (04) places

Specialty

Computer Systems and Networks

The ″Computer Systems and Networks” specialization is multi-disciplinary, combining skills in three main areas of applied computer science:

a- Software engineering, information systems and security.

b- Emerging networks and wireless sensor networks.

c- Modelling and diagnostics of dynamic systems.

In the field of systems, we will be testing new non-deterministic (probabilistic) and formal approaches to modelling and software engineering for information system design, as well as approaches to information system security that have not yet been tackled upstream, i.e. at the design stage. By using UML Sec, UML Profile and formal specification approaches, we can diagnose the system as early as the modelling phase. In the field of networks, in particular wireless sensors, and capitalizing on the experience of laboratory members in this field, the aim is to design and develop platforms based on the new hardware acquired, in order to validate ad hoc energy-saving protocols for edge recognition and monitoring. The quality of service aspect of transporting complex data flows (multimedia) in ad-hoc networks dedicated to critical monitoring applications is also an objective of this training program. Work in progress is in the final stages of completion, and will need to be taken over to continue the research. Finally, in the Dynamic Systems field, the aim is to exploit the monitoring and fault tolerance approaches developed in the laboratory a few years ago, in cooperation with a foreign laboratory, with a view to applying them to industrial systems. A cross-cutting theme will also be to propose topics that will see the application of these tools to the monitoring of wireless sensor networks. The laboratory's skills in automation and robotics will be put to good use in building benchmarks on the laboratory's own hardware (robots), in order to continue developing problems and testing them on well-known, dedicated software (Omnet++, Matlab, Siemens PCS7, etc.).