Research Projects
At USAL, we are dedicated to advancing knowledge and innovation through a wide array of research projects that address critical challenges across various disciplines. Our main topics of focus include Computer Sciences, Health Sciences, Education, and Management. This page highlights our current research initiatives, showcasing the collaborative efforts of our talented teams who are committed to pushing the boundaries of discovery. Each project is a testament to our university’s focus on interdisciplinary research and our commitment to fostering an environment where creativity and inquiry thrive. We invite you to explore the diverse projects and meet the dedicated teams driving these initiatives forward.
Education Axis
| Researcher(s) | Moustapha Fortunanto, Yasser Fadlallah, and Hussein Ziab |
| Description | The purpose of this study is to investigate how a robot-based STEM approach affects students’ academic achievement. We aim in our study to identify the main promoted motivation that constructs the performance improvement of the student in case it exists. The study will compare student performance before and after applying our adopted robot-based STEM interdisciplinary approach, and measure the improvement in academic achievements, especially in Math and Science. It will try to figure out the main factors or motivations that help the student to be more involved in Math and/or Science.   The main outcome of this project is the improvement of academic achievement in Math and Science of students that have a tendency for science, as well as some conclusion for the students who aren’t into Math and/or Science. |
| Researcher(s) | Fadwa Murdaa |
| Description | In an attempt to establish a speaking center ( let's Talk) at USAL this spring, the study attempts to pilot the effectiveness of customized individual plans for learners. This starts with need analysis for each student, then devising an individualized work plan, giving students room to practice their speaking with an Advanced speaker, conferencing with students, providing feedback and building on output. It is expected that students become aware of their linguistic needs and independently monitor their progress. Eventually, with spaced practice and feedback, they will be able to improve their overall speaking skills |
| Researcher(s) | Iman Freij |
| Description | This research will assess the current use of Information and Communication Technology (ICT) in Al-Mabarrat schools, identifying challenges and providing recommendations for future improvements. Through surveys, interviews, and classroom observations, the study will evaluate the infrastructure, digital skills of teachers and students, and how ICT supports teaching, learning, and administration. It will also examine barriers to effective ICT integration, such as resource limitations and insufficient training. The findings will inform practical recommendations aimed at enhancing ICT resources, teacher training, and curriculum integration to foster a more effective and inclusive digital learning environment. |
| Collaboration(s) | Al-Mabarrat Institution |
| Researcher(s) | Ghinwa Khazaal, Yasser Fadlallah, Moustapha Fortunanto |
| Description | Our research aims to study the impact of educational platforms on the acquisition of scientific skills by students in middle school. We will focus on the "Tabshoura" platform, in a context that allows us to compare its effect on the acquisition of scientific skills when used by fourth and fifth-grade students without teacher intervention versus with teacher guidance. The shift from traditional to online teaching happened rapidly, without preparation or training, making access to online resources more essential than ever. In this context, educational platforms offering digital content aligned with the Lebanese curriculum have been established, providing a fertile ground for education in the event of school closures due to challenging conditions in our country. The entry of these new methods into our lives prompts us to question the changes in the teacher's role. The primary role of the life and earth sciences teacher in facilitating the acquisition of scientific skills by students remains significant, despite access to a wealth of open and freely available resources that enable learning on a wide range of subjects. |
| Researcher(s) | Randa Farhat Kanj and Mona El-Abed |
| Description | This study seeks to explore the correlation between special education teachers' perceived job satisfaction and two key factors: (1) their socio-demographics and (2) their self-efficacy. A total of 205 special education teachers from five different states in Lebanon participated in the study by completing online questionnaires. The tools used for data collection included:
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| Researcher(s) | Hussein Ziab, Hussein Alaaeddine |
| Description | The rapid spread of technological devices among students has introduced new distractions, reducing engagement in physical activities essential for mitigating health risks such as obesity and related conditions. Despite advancements in physical education in Lebanon, there remains a notable lack of motivation among students to participate in these classes. This lack of interest, sometimes shared by parents, manifests as neglect or disinterest in attending physical education sessions. Many students report feelings of boredom or reluctance, attributing their disinterest to factors such as dissatisfaction with the curriculum established by the Ministry of Education and Higher Education, the readiness of schools to deliver this curriculum effectively, and criticism of current teaching methods and the format of classes. While numerous studies have examined similar issues in nearby countries and in the West, no systematic research has yet been conducted in Lebanon to establish credible, data-driven insights. This project therefore seeks to fill this gap by exploring the factors affecting student motivation in physical education classes within Lebanese schools. The study aims to identify reasons for low motivation to participate in physical education classes and develop practical recommendations to address these factors within Al-Mabarrat schools. Expected outcomes include creating an intervention plan based on the findings and evaluating its effectiveness in improving motivation to participate in physical education classes. The project will also assess the impact of this intervention on increasing students’ willingness to engage in extracurricular physical activities, with a focus on students aged 12. By identifying key factors and implementing solutions, this project aims to enhance physical education engagement, promoting healthier lifestyles and supporting students' overall well-being. |
Computer Science and Mathematics Axis
| Researcher(s) | Yasser Fadlallah |
| Description | The topic of wireless caching in cellular networks has been widely investigated recently. Caching techniques and solutions have been applied to different types of networks. However, the implementation of most solutions in practical scenarios still faces significant challenges. This research project aims to address practical coded caching schemes while considering realistic assumptions that help in implementing coded caching in practice. Different algorithms will be proposed that improve the performance of coded caching given realistic scenarios such as erroneous channel, user mobility, variable popularity, etc. |
| Collaboration(s) | Faculty of Engineering, Lebanese University Saint-Joseph University (USJ). |
| Researcher(s) | Ahmad Fadlallah |
| Description | The Internet of Things (IoT) plays a significant role in the digital transformation across various sectors by enabling data collection, analysis, and automated control through the interconnection of sensors, devices, and instruments. Ensuring the security of IoT networks is increasingly critical for the IT community. However, as IoT devices expand in scale and scope, the challenge grows to secure their communication without compromising performance. A comprehensive intrusion detection approach is essential for protecting IoT networks across domains like transportation, energy, and smart factories. Traditional monitoring mechanisms are difficult to implement, especially in heterogeneous environments where nodes have diverse characteristics. Key areas like smart cities and the future of industry must integrate new sensors and actuators with existing equipment without exposing IoT networks to frequent attacks. The goal of this project is to develop real-time anomaly detection and even prediction mechanisms tailored to IoT specifications. This project seeks to apply complex network analysis tools and machine learning algorithms to detect and predict anomalies and intrusions across IoT networks efficiently. Complex networks, which have gained traction in scientific fields such as digital technology, healthcare, and ecology, offer valuable insights through advanced modeling, mathematical indices, and graphical approaches. Despite the potential of complex networks in analyzing IoT, they have been underutilized in IoT security against malicious intrusions. Some prior work has used IoT network properties to train supervised machine learning classifiers for anomaly detection. This project aims to be the first to integrate complex network measurements and IoT network characteristics as input features for machine learning classifiers, providing a new approach that combines complex network modeling with machine learning and deep learning algorithms. This innovative approach will not only detect security anomalies with high accuracy but also account for both the macroscopic network behavior and specific node characteristics, enhancing IoT network security. |
| Collaboration(s) | LINEACT, CESI Strasbourg, France. Faculty of Sciences, Lebanese University. |
| Researcher(s) | Ahmad Fadlallah |
| Description | This research project centers on developing robust methods for detecting cyberattacks against Cooperative Intelligent Transport Systems (C-ITS), with an emphasis on securing Vehicle-to-Vehicle (V2V) communication. C-ITS networks are essential to the safety and efficiency of future transportation systems but are vulnerable to a range of cyber threats that can disrupt secure routing and compromise the integrity of shared data. One critical threat is the Sybil attack, where an adversary creates multiple false identities, exploiting the C-ITS identification mechanism to manipulate network behavior and launch other malicious activities. Additionally, routing table poisoning is a prevalent issue, where malicious nodes transmit falsified routing data, undermining network security and stability. Detecting such attacks is complex due to the distributed, dynamic nature of C-ITS and the diversity of threats it faces. This project aims to tackle these challenges by analyzing existing C-ITS standards and security measures, developing a simulation environment to replicate normal and attack scenarios, and collecting and analyzing simulation data. Machine learning techniques will be leveraged to model and identify patterns indicative of cyberattacks, enabling the proposal and evaluation of new, efficient detection algorithms. Ultimately, this research seeks to enhance the security and resilience of C-ITS networks, paving the way for their safe deployment in future transportation systems. |
| Collaboration(s) | Telecom ParisTech - France |
| Researcher(s) | Ayman El-Zein |
| Description | A graph is a set of vertices related by edges. A digraph is an oriented graph. The outneighbors (resp. inneighbors) of a vertex in a digraph are the vertices that are dominated (resp. dominates) by the vertex. The outdegree (resp. indegree) of a vertex is the number of its outneighbors (resp. inneighbors). The second outneighbors of a vertex are the outneighbors of its outneighbors excluding its outneighbors. The second outdegree of a vertex is the number of its second outneighbors. Sullivan (2006) conjectures that in any digraph there exists a vertex having a second outdegree greater than or equal to its indegree. I'm working on this conjecture.The expected outcomes of the project are:
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| Collaboration(s) | KALMA Laboratory, Lebanese University |
Scholarship Programs
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